IBM SPSS Statistics 27 Core System
User's Guide
IBM
Note
Before using this information and the product it supports, read the information in “Notices” on page
267.
Product Information
This edition applies to version 27, release 0, modication 0 of IBM
®
SPSS
®
Statistics and to all subsequent releases and
modications until otherwise indicated in new editions.
©
Copyright International Business Machines Corporation .
US Government Users Restricted Rights – Use, duplication or disclosure restricted by GSA ADP Schedule Contract with
IBM Corp.
Contents
Chapter 1. Overview.............................................................................................. 1
Windows....................................................................................................................................................... 1
Designated window versus active window............................................................................................ 1
Variable names and variable labels in dialog box lists............................................................................... 1
Data type, measurement level, and variable list icons............................................................................... 2
Auto-Recovery..............................................................................................................................................2
Restore points.........................................................................................................................................2
Finding out more.......................................................................................................................................... 3
Chapter 2. Getting help..........................................................................................5
Chapter 3. Data les.............................................................................................. 7
Opening data les........................................................................................................................................ 7
To open data les................................................................................................................................... 7
Data le types.........................................................................................................................................7
Reading Excel les..................................................................................................................................8
Reading Older Excel Files and Other Spreadsheets ............................................................................. 9
Reading dBASE les............................................................................................................................... 9
Reading Stata les..................................................................................................................................9
Reading CSV Files.................................................................................................................................10
Text Wizard...........................................................................................................................................10
Reading Database Files........................................................................................................................14
Reading Cognos BI data.......................................................................................................................19
Reading Cognos TM1 data................................................................................................................... 21
File information..........................................................................................................................................22
Saving data les......................................................................................................................................... 22
To save modied data les.................................................................................................................. 23
To save data les in code page character encoding........................................................................... 23
Saving data les in external formats................................................................................................... 23
Saving data les in Excel format..........................................................................................................26
Saving data les in SAS format............................................................................................................ 26
Saving data les in Stata format.......................................................................................................... 27
Saving Subsets of Variables................................................................................................................. 28
Encrypting data les.............................................................................................................................28
Exporting to a Database....................................................................................................................... 29
Exporting to Data Collection ............................................................................................................... 34
Exporting to Cognos TM1..................................................................................................................... 35
Comparing datasets...................................................................................................................................37
Compare Datasets: Compare tab.........................................................................................................37
Compare Datasets: Attributes tab....................................................................................................... 38
Comparing datasets: Output tab..........................................................................................................38
Protecting original data..............................................................................................................................38
Virtual Active File....................................................................................................................................... 39
Creating a Data Cache.......................................................................................................................... 39
Chapter 4. Distributed Analysis Mode...................................................................41
Server Login............................................................................................................................................... 41
Adding and Editing Server Login Settings............................................................................................41
To Select, Switch, or Add Servers........................................................................................................42
Searching for Available Servers........................................................................................................... 42
iii
Opening Data Files from a Remote Server................................................................................................ 43
File Access in Local and Distributed Analysis Mode.................................................................................43
Availability of Procedures in Distributed Analysis Mode.......................................................................... 44
Absolute versus Relative Path Specications...........................................................................................44
Chapter 5. Data Editor......................................................................................... 45
Data View................................................................................................................................................... 45
Variable View............................................................................................................................................. 45
To display or dene variable attributes............................................................................................... 46
Variable names.....................................................................................................................................46
Variable measurement level................................................................................................................ 47
Variable type.........................................................................................................................................47
Variable labels...................................................................................................................................... 49
Value labels.......................................................................................................................................... 49
Inserting line breaks in labels..............................................................................................................49
Missing values...................................................................................................................................... 49
Roles..................................................................................................................................................... 50
Column width....................................................................................................................................... 50
Variable alignment............................................................................................................................... 50
Applying variable denition attributes to multiple variables..............................................................50
Custom Variable Attributes..................................................................................................................51
Customizing Variable View...................................................................................................................53
Spell checking ......................................................................................................................................53
Entering data..............................................................................................................................................54
To enter numeric data..........................................................................................................................54
To enter non-numeric data.................................................................................................................. 54
To use value labels for data entry........................................................................................................55
Data value restrictions in the data editor............................................................................................ 55
Editing data................................................................................................................................................ 55
Replacing or modifying data values.....................................................................................................55
Cutting, copying, and pasting data values...........................................................................................55
Inserting new cases............................................................................................................................. 56
Inserting new variables........................................................................................................................56
To change data type............................................................................................................................. 57
Finding cases, variables, or imputations...................................................................................................57
Finding and replacing data and attribute values.......................................................................................57
Obtaining Descriptive Statistics for Selected Variables........................................................................... 58
Case selection status in the Data Editor................................................................................................... 58
Data Editor display options........................................................................................................................59
Data Editor printing....................................................................................................................................59
To print Data Editor contents...............................................................................................................59
Chapter 6. Working with Multiple Data Sources.................................................... 61
Basic Handling of Multiple Data Sources.................................................................................................. 61
Working with Multiple Datasets in Command Syntax...............................................................................61
Copying and Pasting Information between Datasets............................................................................... 61
Renaming Datasets....................................................................................................................................62
Suppressing Multiple Datasets..................................................................................................................62
Chapter 7. Data preparation.................................................................................63
Variable properties.................................................................................................................................... 63
Dening Variable Properties......................................................................................................................63
To Dene Variable Properties.............................................................................................................. 63
Dening Value Labels and Other Variable Properties......................................................................... 64
Assigning the Measurement Level....................................................................................................... 65
Custom Variable Attributes..................................................................................................................65
Copying Variable Properties.................................................................................................................66
iv
Setting measurement level for variables with unknown measurement level..........................................66
Multiple Response Sets............................................................................................................................. 67
Dening Multiple Response Sets......................................................................................................... 67
Copy Data Properties................................................................................................................................. 68
Copying Data Properties.......................................................................................................................68
Identifying Duplicate Cases.......................................................................................................................71
Visual Binning.............................................................................................................................................72
To Bin Variables....................................................................................................................................73
Binning Variables..................................................................................................................................73
Automatically Generating Binned Categories..................................................................................... 74
Copying Binned Categories.................................................................................................................. 75
User-Missing Values in Visual Binning.................................................................................................76
Chapter 8. Data Transformations......................................................................... 77
Data Transformations................................................................................................................................ 77
Computing Variables..................................................................................................................................77
Compute Variable: If Cases..................................................................................................................77
Compute Variable: Type and Label...................................................................................................... 78
Functions....................................................................................................................................................78
Missing Values in Functions.......................................................................................................................78
Random Number Generators.................................................................................................................... 78
Count Occurrences of Values within Cases...............................................................................................79
Count Values within Cases: Values to Count....................................................................................... 79
Count Occurrences: If Cases............................................................................................................... 79
Shift Values................................................................................................................................................ 79
Recoding Values.........................................................................................................................................80
Recode into Same Variables......................................................................................................................80
Recode into Same Variables: Old and New Values............................................................................. 80
Recode into Different Variables.................................................................................................................81
Recode into Different Variables: Old and New Values........................................................................ 82
Automatic Recode......................................................................................................................................82
Rank Cases.................................................................................................................................................84
Rank Cases: Types............................................................................................................................... 84
Rank Cases: Ties.................................................................................................................................. 85
Date and Time Wizard................................................................................................................................85
Dates and Times in IBM SPSS Statistics .............................................................................................86
Create a Date/Time Variable from a String..........................................................................................86
Create a Date/Time Variable from a Set of Variables..........................................................................87
Add or Subtract Values from Date/Time Variables............................................................................. 87
Extract Part of a Date/Time Variable................................................................................................... 89
Time Series Data Transformations............................................................................................................90
Dene Dates......................................................................................................................................... 90
Create Time Series............................................................................................................................... 90
Replace Missing Values........................................................................................................................92
Chapter 9. File handling and le transformations.................................................95
File handling and le transformations ......................................................................................................95
Sort cases...................................................................................................................................................95
Sort variables............................................................................................................................................. 96
Transpose...................................................................................................................................................96
Merging Data Files..................................................................................................................................... 97
Add Cases............................................................................................................................................. 97
Add Variables........................................................................................................................................98
Aggregate Data........................................................................................................................................ 101
Aggregate Data: Aggregate Function.................................................................................................102
Aggregate Data: Variable Name and Label........................................................................................102
Split le.................................................................................................................................................... 102
v
Select cases............................................................................................................................................. 103
Select cases: If...................................................................................................................................104
Select cases: Random sample...........................................................................................................104
Select cases: Range........................................................................................................................... 104
Weight cases............................................................................................................................................104
Restructuring Data...................................................................................................................................105
To Restructure Data........................................................................................................................... 105
Restructure Data Wizard: Select Type...............................................................................................105
Restructure Data Wizard (Variables to Cases): Number of Variable Groups....................................108
Restructure Data Wizard (Variables to Cases): Select Variables......................................................108
Restructure Data Wizard (Variables to Cases): Create Index Variables...........................................109
Restructure Data Wizard (Variables to Cases): Create One Index Variable..................................... 110
Restructure Data Wizard (Variables to Cases): Create Multiple Index Variables.............................111
Restructure Data Wizard (Variables to Cases): Options................................................................... 111
Restructure Data Wizard (Cases to Variables): Select Variables...................................................... 111
Restructure Data Wizard (Cases to Variables): Sort Data................................................................. 112
Restructure Data Wizard (Cases to Variables): Options....................................................................112
Restructure Data Wizard: Finish........................................................................................................ 113
Chapter 10. Working with output....................................................................... 115
Working with output................................................................................................................................ 115
Viewer...................................................................................................................................................... 115
Showing and hiding results................................................................................................................115
Moving, deleting, and copying output............................................................................................... 115
Changing initial alignment................................................................................................................. 116
Changing alignment of output items................................................................................................. 116
Viewer outline.................................................................................................................................... 116
Adding items to the Viewer................................................................................................................117
Finding and replacing information in the Viewer.............................................................................. 118
Closing output items.......................................................................................................................... 118
Copying output into other applications...................................................................................................119
Interactive output....................................................................................................................................120
Export output........................................................................................................................................... 120
HTML options..................................................................................................................................... 121
Word/RTF options.............................................................................................................................. 122
Excel options...................................................................................................................................... 122
PowerPoint options............................................................................................................................ 123
PDF options........................................................................................................................................ 123
Text options........................................................................................................................................124
Graphics only options........................................................................................................................ 124
Graphics format options.................................................................................................................... 125
Viewer printing.........................................................................................................................................126
To print output and charts................................................................................................................. 126
Print Preview...................................................................................................................................... 126
Page Attributes: Headers and Footers.............................................................................................. 126
Page Attributes: Options....................................................................................................................127
Saving output........................................................................................................................................... 127
To save a Viewer document...............................................................................................................127
Chapter 11. Pivot tables.....................................................................................129
Pivot tables.............................................................................................................................................. 129
Manipulating a pivot table....................................................................................................................... 129
Activating a pivot table.......................................................................................................................129
Pivoting a table...................................................................................................................................129
Changing display order of elements within a dimension.................................................................. 129
Moving rows and columns within a dimension element................................................................... 129
Transposing rows and columns......................................................................................................... 130
vi
Grouping rows or columns ................................................................................................................ 130
Ungrouping rows or columns.............................................................................................................130
Rotating row or column labels...........................................................................................................130
Sorting rows....................................................................................................................................... 130
Inserting rows and columns.............................................................................................................. 131
Controlling display of variable and value labels................................................................................131
Changing the output language...........................................................................................................131
Navigating large tables...................................................................................................................... 132
Undoing changes................................................................................................................................132
Working with layers................................................................................................................................. 132
Creating and displaying layers...........................................................................................................132
Go to layer category........................................................................................................................... 133
Showing and hiding items....................................................................................................................... 133
Hiding rows and columns in a table...................................................................................................133
Showing hidden rows and columns in a table...................................................................................133
Hiding and showing dimension labels............................................................................................... 133
Hiding and showing table titles......................................................................................................... 133
TableLooks...............................................................................................................................................133
To apply a TableLook......................................................................................................................... 134
To edit or create a TableLook............................................................................................................ 134
Table properties...................................................................................................................................... 134
To change pivot table properties.......................................................................................................134
Table properties: general...................................................................................................................134
Table properties: notes......................................................................................................................135
Table properties: cell formats........................................................................................................... 135
Table properties: borders.................................................................................................................. 136
Table properties: printing.................................................................................................................. 136
Cell properties......................................................................................................................................... 137
Font and background......................................................................................................................... 137
Format value.......................................................................................................................................137
Alignment and margins...................................................................................................................... 137
Footnotes and captions...........................................................................................................................137
Adding footnotes and captions..........................................................................................................137
To hide or show a caption.................................................................................................................. 137
To hide or show a footnote in a table................................................................................................ 138
Footnote marker.................................................................................................................................138
Renumbering footnotes..................................................................................................................... 138
Editing footnotes in legacy tables......................................................................................................138
Data cell widths....................................................................................................................................... 139
Changing column width........................................................................................................................... 139
Displaying hidden borders in a pivot table..............................................................................................139
Selecting rows, columns, and cells in a pivot table................................................................................139
Printing pivot tables.................................................................................................................................140
Controlling table breaks for wide and long tables............................................................................ 140
Creating a chart from a pivot table..........................................................................................................141
Legacy tables........................................................................................................................................... 141
Chapter 12. Models............................................................................................143
Interacting with a model......................................................................................................................... 143
Working with the Model Viewer......................................................................................................... 143
Printing a model.......................................................................................................................................144
Exporting a model....................................................................................................................................144
Saving elds used in the model to a new dataset.................................................................................. 144
Saving predictors to a new dataset based on importance..................................................................... 145
Ensemble Viewer..................................................................................................................................... 145
Models for Ensembles........................................................................................................................145
Split Model Viewer...................................................................................................................................147
vii
Chapter 13. Automated Output Modication.......................................................149
Style Output: Select ................................................................................................................................149
Style Output............................................................................................................................................. 150
Style Output: Labels and Text............................................................................................................152
Style Output: Indexing....................................................................................................................... 152
Style Output: TableLooks...................................................................................................................152
Style Output: Size...............................................................................................................................152
Table Style............................................................................................................................................... 152
Table Style: Condition........................................................................................................................ 153
Table Style: Format............................................................................................................................154
Chapter 14. Working with Command Syntax.......................................................155
Syntax Rules............................................................................................................................................ 155
Pasting Syntax from Dialog Boxes...........................................................................................................156
To Paste Syntax from Dialog Boxes...................................................................................................156
Copying Syntax from the Output Log...................................................................................................... 156
To Copy Syntax from the Output Log.................................................................................................157
Using the Syntax Editor........................................................................................................................... 157
Syntax Editor Window........................................................................................................................ 157
Terminology........................................................................................................................................158
Auto-Completion................................................................................................................................159
Color Coding....................................................................................................................................... 159
Breakpoints........................................................................................................................................ 160
Bookmarks......................................................................................................................................... 161
Commenting or Uncommenting Text................................................................................................ 162
Formatting Syntax..............................................................................................................................162
Running Command Syntax.................................................................................................................163
Character Set Encoding in Syntax Files............................................................................................. 163
Multiple Execute Commands.............................................................................................................164
Character Set Encoding in Syntax Files...................................................................................................164
Multiple Execute Commands.................................................................................................................. 165
Encrypting syntax les.............................................................................................................................165
Chapter 15. Overview of the chart facility...........................................................167
Building and editing a chart.....................................................................................................................167
Building Charts................................................................................................................................... 167
Editing Charts..................................................................................................................................... 168
Chart denition options........................................................................................................................... 169
Adding and Editing Titles and Footnotes...........................................................................................169
Setting General Options.....................................................................................................................169
Chapter 16. Scoring data with predictive models................................................ 171
Scoring Wizard......................................................................................................................................... 171
Matching model elds to dataset elds............................................................................................ 172
Selecting scoring functions................................................................................................................173
Scoring the active dataset..................................................................................................................174
Merging model and transformation XML les.........................................................................................174
Chapter 17. Utilities..........................................................................................175
Utilities..................................................................................................................................................... 175
Variable information................................................................................................................................ 175
Data le comments..................................................................................................................................175
Variable sets............................................................................................................................................ 176
Dening variable sets.............................................................................................................................. 176
Using variable sets to show and hide variables......................................................................................176
Reordering target variable lists............................................................................................................... 177
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Chapter 18. Options...........................................................................................179
Options.....................................................................................................................................................179
General options....................................................................................................................................... 179
Language options.....................................................................................................................................181
Viewer options......................................................................................................................................... 182
Data Options............................................................................................................................................ 182
Changing the default variable view....................................................................................................184
Currency options......................................................................................................................................184
To create custom currency formats.................................................................................................. 184
Output options.........................................................................................................................................184
Chart options........................................................................................................................................... 185
Data Element Colors.......................................................................................................................... 185
Data Element Lines............................................................................................................................ 186
Data Element Markers........................................................................................................................186
Data Element Fills.............................................................................................................................. 187
Pivot Tables options................................................................................................................................ 187
File Locations options..............................................................................................................................188
Script options...........................................................................................................................................189
Multiple imputations options.................................................................................................................. 190
Syntax editor options...............................................................................................................................190
Privacy options.........................................................................................................................................191
Chapter 19. Customizing Menus and Toolbars.....................................................193
Customizing Menus and Toolbars........................................................................................................... 193
Menu Editor..............................................................................................................................................193
Customizing Toolbars.............................................................................................................................. 193
Show Toolbars......................................................................................................................................... 193
To Customize Toolbars............................................................................................................................193
Toolbar Properties............................................................................................................................. 194
Edit Toolbar........................................................................................................................................ 194
Create New Tool.................................................................................................................................194
Chapter 20. Extensions......................................................................................195
Extension Hub..........................................................................................................................................195
Explore tab ........................................................................................................................................ 196
Installed tab ...................................................................................................................................... 196
Settings...............................................................................................................................................197
Extension Details................................................................................................................................197
Installing local extension bundles.......................................................................................................... 197
Installation locations for extensions................................................................................................. 198
Required R packages......................................................................................................................... 199
Batch installation of extension bundles............................................................................................ 199
Creating and managing custom dialogs..................................................................................................200
Custom Dialog Builder layout............................................................................................................ 201
Building a custom dialog....................................................................................................................201
Dialog Properties................................................................................................................................202
Specifying the Menu Location for a Custom Dialog...........................................................................202
Laying out controls on the canvas..................................................................................................... 203
Building the Syntax Template............................................................................................................204
Previewing a custom dialog............................................................................................................... 205
Control types...................................................................................................................................... 206
Extension Properties..........................................................................................................................225
Managing custom dialogs.................................................................................................................. 228
Custom Dialogs for Extension Commands........................................................................................ 231
Creating Localized Versions of Custom Dialogs................................................................................ 231
Creating and editing extension bundles................................................................................................. 233
ix
Chapter 21. Production jobs...............................................................................235
Syntax les...............................................................................................................................................236
Output...................................................................................................................................................... 236
HTML options .....................................................................................................................................237
PowerPoint options ........................................................................................................................... 237
PDF options ....................................................................................................................................... 237
Text options .......................................................................................................................................237
Production jobs with OUTPUT commands........................................................................................ 238
Runtime values........................................................................................................................................ 238
Run options..............................................................................................................................................239
Server login.............................................................................................................................................. 239
Adding and Editing Server Login Settings..........................................................................................239
User prompts........................................................................................................................................... 239
Background job status.............................................................................................................................240
Running production jobs from a command line......................................................................................240
Converting Production Facility les.........................................................................................................241
Chapter 22. Output Management System........................................................... 243
Output object types................................................................................................................................. 244
Command identiers and table subtypes...............................................................................................245
Labels.......................................................................................................................................................245
OMS options.............................................................................................................................................246
Logging.....................................................................................................................................................248
Excluding output display from the viewer.............................................................................................. 248
Routing output to IBM SPSS Statistics data les....................................................................................249
Data les created from multiple tables.............................................................................................249
Controlling column elements to control variables in the data le....................................................249
Variable names in OMS-generated data les.................................................................................... 249
OXML table structure...............................................................................................................................250
OMS identiers........................................................................................................................................ 252
Copying OMS identiers from the viewer outline..............................................................................252
Chapter 23. Scripting Facility............................................................................. 255
Autoscripts...............................................................................................................................................255
Creating Autoscripts.......................................................................................................................... 256
Associating Existing Scripts with Viewer Objects............................................................................. 256
Scripting with the Python Programming Language................................................................................ 257
Running Python Scripts and Python programs..................................................................................257
Script Editor for the Python Programming Language........................................................................258
Scripting in Basic..................................................................................................................................... 259
Compatibility with Versions Prior to 16.0..........................................................................................259
The scriptContext Object................................................................................................................... 261
Startup Scripts......................................................................................................................................... 261
Chapter 24. TABLES and IGRAPH Command Syntax Converter............................263
Chapter 25. Encrypting data les, output documents, and syntax les................ 265
Notices..............................................................................................................267
Trademarks..............................................................................................................................................268
Index................................................................................................................ 269
x
Chapter 1. Overview
Windows
There are a number of different types of windows in IBM SPSS Statistics:
Data Editor. The Data Editor displays the contents of the data le. You can create new data les or modify
existing data les with the Data Editor. If you have more than one data le open, there is a separate Data
Editor window for each data le.
Viewer. All statistical results, tables, and charts are displayed in the Viewer. You can edit the output and
save it for later use. A Viewer window opens automatically the rst time you run a procedure that
generates output.
Pivot Table Editor. Output that is displayed in pivot tables can be modied in many ways with the Pivot
Table Editor. You can edit text, swap data in rows and columns, add color, create multidimensional
tables, and selectively hide and show results.
Chart Editor. You can modify high-resolution charts and plots in chart windows. You can change the
colors, select different type fonts or sizes, switch the horizontal and vertical axes, rotate 3-D scatterplots,
and even change the chart type.
Text Output Editor. Text output that is not displayed in pivot tables can be modied with the Text Output
Editor. You can edit the output and change font characteristics (type, style, color, size).
Syntax Editor. You can paste your dialog box choices into a syntax window, where your selections appear
in the form of command syntax. You can then edit the command syntax to use special features that are
not available through dialog boxes. You can save these commands in a le for use in subsequent sessions.
Designated window versus active window
If you have more than one open Viewer window, output is routed to the designated Viewer window. If
you have more than one open Syntax Editor window, command syntax is pasted into the designated
Syntax Editor window. The designated windows are indicated by a plus sign in the icon in the title bar. You
can change the designated windows at any time.
The designated window should not be confused with the active window, which is the currently selected
window. If you have overlapping windows, the active window appears in the foreground. If you open a
window, that window automatically becomes the active window and the designated window.
Changing the designated window
1. Make the window that you want to designate the active window (click anywhere in the window).
2. From the menus choose:
Utilities > Designate Window
Note: For Data Editor windows, the active Data Editor window determines the dataset that is used in
subsequent calculations or analyses. There is no "designated" Data Editor window. See the topic “Basic
Handling of Multiple Data Sources” on page 61 for more information.
Variable names and variable labels in dialog box lists
You can display either variable names or variable labels in dialog box lists, and you can control the sort
order of variables in source variable lists. To control the default display attributes of variables in source
lists, choose Options on the Edit menu. See the topic “General options” on page 179 for more
information.
You can also change the variable list display attributes within dialogs. The method for changing the
display attributes depends on the dialog:
• If the dialog provides sorting and display controls above the source variable list, use those controls to
change the display attributes.
• If the dialog does not contain sorting controls above the source variable list, right-click any variable in
the source list and select the display attributes from the pop-up menu.
You can display either variable names or variable labels (names are displayed for any variables without
dened labels), and you can sort the source list by le order, alphabetical order, or measurement level.
(In dialogs with sorting controls above the source variable list, the default selection of None sorts the list
in le order.)
Data type, measurement level, and variable list icons
The icons that are displayed next to variables in dialog box lists provide information about the variable
type and measurement level.
Table 1. Measurement level icons
Numeric String Date Time
Scale (Continuous) n/a
Ordinal
Nominal
• For more information on measurement level, see “Variable measurement level” on page 47.
• For more information on numeric, string, date, and time data types, see “Variable type” on page 47.
Auto-Recovery
The Auto-Recovery dialog displays in instances when there is unsaved data in the active session and IBM
SPSS Statistics exits unexpectedly (the dialog displays after relaunching SPSS Statistics). The dialog
provides options for restoring data from previous sessions that quit unexpectedly and for deleting saved
session data.
Note: Saved session data will remain in a backed-up state until you either restore or delete the data. The
Document Recovery dialog will continue to display each time you launch SPSS Statistics until all saved
sessions are either restored or deleted.
Refer to the Automatic Recovery section in the “General options” on page 179 dialog for information on
the available automatic recovery settings.
Auto-Recovery takes too long
In cases when the Auto-Recovery feature takes to long to complete, a variation of the Auto-Recovery
dialog displays and provides options for disabling Auto-Recovery completely, or for specic les. You can
also select to not show the dialog again for the active session.
If you choose to disable Auto-Recovery, you can reactivate the feature via Edit > Options... > General >
Auto-Recovery. For more information, see “General options” on page 179.
Restore points
Restore points save data from active sessions that either quit unexpectedly (automatic recovery) or that
you explicitly save. Each restore point is an SPSS Statistics session snapshot. Each restore point contains
Data Editor, syntax, and output le information that was active at the time the session either quit
2
IBM SPSS Statistics 27 Core System User's Guide
unexpectedly or that you explicitly saved. Saved restore points remain in a backed-up state until you
either restore or delete them.
Note: Refer to the Automatic Recovery section in the “General options” on page 179 dialog for
information on the available automatic recovery settings.
Opening restore points
Available restore points automatically display in the SPSS Statistics welcome dialog each time you launch
SPSS Statistics.
Restore points can also be accessed through the SPSS Statistics File menu:
1. Click File > Open Restore Point.... The Auto-Recovery dialog displays all available restore points.
2. Select a restore point to open and then click OK.
Saving restore points
An SPSS Statistics session restore point is created automatically when an active session quits
unexpectedly. You can manually save a restore point via File > Save Restore Point...
Deleting restore points
Existing session restore points can be deleted from the SPSS Statistics welcome page or from File > Open
Restore Point... dialog. Select a restore point and click the delete icon
.
Finding out more
For a comprehensive overview of the basics, see the online tutorial. From any IBM SPSS Statistics menu
choose:
Help > Tutorial
Chapter 1. Overview
3
4 IBM SPSS Statistics 27 Core System User's Guide
Chapter 2. Getting help
The Knowledge Center contains a number of different sections.
Help
The section you are currently in. Provides information about the user interface. There is a separate
section for each optional module.
Reference
Reference information for the command language and the GPL graphics language. The reference
material for the command language is also available in PDF form: Help > Command Syntax
Reference.
Tutorial
Step-by-step instructions for using many of the basic features.
Case Studies
Hands-on examples for creating various types of statistical analyses and how to interpret the results.
Statistics Coach
Guides you through the process of nding the procedure that you want to use.
Integration Plug-ins
Separate sections for the Python and R plug-ins.
Context-sensitive help
In many places in the user interface, you can get context-sensitive help.
• Help buttons in dialogs take you directly to the help topic for that dialog.
• Right-click on terms in an activated pivot table in the Viewer and choose What's This? from the pop-up
menu to display denitions of the terms.
• In a command syntax window, position the cursor anywhere within a syntax block for a command and
press F1 on the keyboard. The help for that command is displayed
Other resources
Answers to many common problems can be found at https://www.ibm.com/products/spss-statistics/
support.
If you're a student using a student, academic or grad pack version of any IBM SPSS software product,
please see our special online Solutions for Education pages for students. If you're a student using a
university-supplied copy of the IBM SPSS software, please contact the IBM SPSS product coordinator at
your university.
The IBM SPSS Statistics community has resources for all levels of users and application developers.
Download utilities, graphics examples, new statistical modules, and articles. Visit the IBM SPSS Statistics
community at https://www.ibm.com/community/spss-statistics.
Documentation in PDF format for statistical algorithms and command syntax is available at https://
www.ibm.com/support/pages/ibm-spss-statistics-27-documentation.
6 IBM SPSS Statistics 27 Core System User's Guide
Chapter 3. Data les
Data les come in a wide variety of formats, and this software is designed to handle many of them,
including:
• Excel spreadsheets
• Database tables from many database sources, including Oracle, SQLServer, DB2, and others
• Tab-delimited, CSV, and other types of simple text les
• SAS data les
• Stata data les
Opening data les
In addition to les saved in IBM SPSS Statistics format, you can open Excel, SAS, Stata, tab-delimited,
and other les without converting the les to an intermediate format or entering data denition
information.
• Opening a data le makes it the active dataset. If you already have one or more open data les, they
remain open and available for subsequent use in the session. Clicking anywhere in the Data Editor
window for an open data le will make it the active dataset. See the topic Chapter 6, “Working with
Multiple Data Sources,” on page 61 for more information.
• In distributed analysis mode using a remote server to process commands and run procedures, the
available data les, folders, and drives are dependent on what is available on or from the remote server.
The current server name is indicated at the top of the dialog box. You will not have access to data les
on your local computer unless you specify the drive as a shared device and the folders containing your
data les as shared folders. See the topic Chapter 4, “Distributed Analysis Mode,” on page 41 for more
information.
To open data les
1. From the menus choose:
File > Open > Data...
2. In the Open Data dialog box, select the le that you want to open.
3. Click Open.
Optionally, you can:
• Automatically set the width of each string variable to the longest observed value for that variable using
Minimize string widths based on observed values. This is particularly useful when reading code page
data les in Unicode mode. See the topic “General options” on page 179 for more information.
• Read variable names from the rst row of spreadsheet les.
• Specify a range of cells to read from spreadsheet les.
• Specify a worksheet within an Excel le to read (Excel 95 or later).
For information on reading data from databases, see “Reading Database Files” on page 14. For
information on reading data from text data les, see “Text Wizard” on page 10. For information on
reading IBM Cognos
®
data, see “Reading Cognos BI data” on page 19.
Data le types
SPSS Statistics. Opens data les that are saved in IBM SPSS Statistics format and also the DOS product
SPSS/PC+.
SPSS Statistics Compressed. Opens data les that are saved in IBM SPSS Statistics compressed format.
SPSS/PC+. Opens SPSS/PC+ data les. This option is available only on Windows operating systems.
Portable. Opens data les that are saved in portable format. Saving a le in portable format takes
considerably longer than saving the le in IBM SPSS Statistics format.
Excel. Opens Excel les.
Lotus 1-2-3. Opens data les that are saved in 1-2-3 format for release 3.0, 2.0, or 1A of Lotus.
SYLK. Opens data les that are saved in SYLK (symbolic link) format, a format that is used by some
spreadsheet applications.
dBASE. Opens dBASE-format les for either dBASE IV, dBASE III or III PLUS, or dBASE II. Each case is a
record. Variable and value labels and missing-value specications are lost when you save a le in this
format.
SAS. SAS versions 6–9 and SAS transport les.
Stata. Stata versions 4–13.
Reading Excel les
This topic applies to Excel 95 and later les. To read Excel 4 or earlier versions, see the topic “Reading
Older Excel Files and Other Spreadsheets ” on page 9.
To import an Excel le
1. From the menus choose:
File > Import Data > Excel..., or drag and drop an existing Excel le directly into an open IBM SPSS
Statistics instance.
2. Select the appropriate import settings.
Worksheet
Excel les can contain multiple worksheets. By default, the Data Editor reads the rst worksheet.
To read a different worksheet, select the worksheet from the list.
Range
You can also read a range of cells. Use the same method for specifying cell ranges as you would in
Excel. For example: A1:D10.
Read variable names from rst row of data
You can read variable names from the rst row of the le or the rst row of the dened range.
Values that don't conform to variable naming rules are converted to valid variable names, and the
original names are used as variable labels.
Percentage of values that determine data type
The data type for each variable is determined by the percentage of values that conform to the
same format.
• The value must be greater than 50.
• The denominator used to determine the percentage is the number of non-blank values for each
variable.
• If no consistent format is used by the specied percentage of values, the variable is assigned the
string data type.
• For variables that are assigned a numeric format (including date and time formats) based on the
percentage value, values that do not conform to that format are assigned the system-missing
value.
Ignore hidden rows and columns
Hidden rows and columns in the Excel le are not included. This option is available only for Excel
2007 and later les (XLSX, XLSM).
Remove leading spaces from string values
Any blank spaces at the beginning of string values are removed.
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IBM SPSS Statistics 27 Core System User's Guide
Remove trailing spaces from string values
Blank spaces at the end of the string values are removed. This setting affects the calculation of the
dened width of string variables.
3. Click OK.
Reading Older Excel Files and Other Spreadsheets
This topic applies to reading Excel 4 or earlier les, Lotus 1-2-3 les and SYLK format spreadsheet les.
For information on reading Excel 95 or later les, see the topic “Reading Excel les” on page 8
.
Read variable names. For spreadsheets, you can read variable names from the rst row of the le or the
rst row of the dened range. The values are converted as necessary to create valid variable names,
including converting spaces to underscores.
Range. For spreadsheet data les, you can also read a range of cells. Use the same method for specifying
cell ranges as you would with the spreadsheet application.
How Spreadsheets are Read
• The data type and width for each variable are determined by the column width and data type of the rst
data cell in the column. Values of other types are converted to the system-missing value. If the rst data
cell in the column is blank, the global default data type for the spreadsheet (usually numeric) is used.
• For numeric variables, blank cells are converted to the system-missing value, indicated by a period. For
string variables, a blank is a valid string value, and blank cells are treated as valid string values.
• If you do not read variable names from the spreadsheet, the column letters (A, B, C, ...) are used for
variable names for Excel and Lotus les. For SYLK les and Excel les saved in R1C1 display format, the
software uses the column number preceded by the letter C for variable names (C1, C2, C3, ...).
Reading dBASE les
Database les are logically very similar to IBM SPSS Statistics data les. The following general rules apply
to dBASE les:
• Field names are converted to valid variable names.
• Colons used in dBASE eld names are translated to underscores.
• Records marked for deletion but not actually purged are included. The software creates a new string
variable, D_R, which contains an asterisk for cases marked for deletion.
Reading Stata les
The following general rules apply to Stata data les:
• Variable names. Stata variable names are converted to IBM SPSS Statistics variable names in case-
sensitive form. Stata variable names that are identical except for case are converted to valid variable
names by appending an underscore and a sequential letter (_A, _B, _C, ..., _Z, _AA, _AB, ..., and so
forth).
• Variable labels. Stata variable labels are converted to IBM SPSS Statistics variable labels.
• Value labels. Stata value labels are converted to IBM SPSS Statistics value labels, except for Stata
value labels assigned to "extended" missing values. Value labels longer than 120 bytes are truncated.
• String variables. Stata strl variables are converted to string variables. Values longer than 32K bytes are
truncated. Stata strl values that contain blobs (binary large objects) are converted to blank strings.
• Missing values. Stata "extended" missing values are converted to system-missing values.
• Date conversion. Stata date format values are converted to IBM SPSS Statistics DATE format (d-m-y)
values. Stata "time-series" date format values (weeks, months, quarters, and so on) are converted to
simple numeric (F) format, preserving the original, internal integer value, which is the number of weeks,
months, quarters, and so on, since the start of 1960.
Chapter 3. Data
les 9
Reading CSV Files
To read CSV les, from the menus choose: File > Import Data > CSV
Note: The Import Data function does not support CSV data that includes embedded line breaks in quoted
text. A possible workaround is to save the CSV le (that includes quoted embedded line breaks) as
an .xls/.xlsx le, and then use the import Excel feature.
The Read CSV File dialog reads CSV format text data les that use a comma, a semicolon, or a tab as the
delimiter between values.
If the text le uses a different delimiter, contains text at the beginning of the le that is not variable
names or data values, or has other special considerations, use the Text Wizard to read the les.
First line contains variable names
The rst non-blank line in the le contains label text that is used as variable names. Values that are
invalid as variable names are automatically converted to valid variable names.
Remove leading spaces from string values
Any blank spaces at the beginning of string values are removed.
Remove trailing spaces from string values
Blank spaces at the end of the string values are removed. This setting affects the calculation of the
dened width of string variables.
Delimiter between values
The delimiter can be a comma, a semicolon, or a tab. If the delimiter is any other character or a blank
space, use the Text Wizard to read the le.
Decimal symbol
The symbol that is used to indicate decimals in the text data le. The symbol can be a period or a
comma.
Text Qualier
Character that is used to enclose values that contain the delimiter character. The qualier appears at
the start and the end of the value. The qualier can be double quotation mark, single quotation mark,
or none.
Percentage of values that determine data type
The data type for each variable is determined by the percentage of values that conform to the same
format.
• The value must be greater than 50.
• If no consistent format is used by the specied percentage of values, the variable is assigned the
string data type.
• For variables that are assigned a numeric format (including date and time formats) based on the
percentage value, values that do not conform to that format are assigned the system-missing value.
Cache data locally
A data cache is a complete copy of the data le that is stored in temporary disk space. Caching the
data le can improve performance.
Text Wizard
The Text Wizard can read text data les formatted in a variety of ways:
• Tab-delimited les
• Space-delimited les
• Comma-delimited les
• Fixed-eld format les
For delimited les, you can also specify other characters as delimiters between values, and you can
specify multiple delimiters.
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IBM SPSS Statistics 27 Core System User's Guide
To Read Text Data Files
1. From the menus choose:
File > Import Data > Text Data...
2. Select the text le in the Open Data dialog box.
3. If necessary, select the encoding of the le.
4. Follow the steps in the Text Wizard to dene how to read the data le.
Encoding
The encoding of a le affects the way character data are read. Unicode data les typically contain a byte
order mark that identies the character encoding. Some applications create Unicode les without a byte
order mark, and code page data les do not contain any encoding identier.
• Unicode (UTF-8). Reads the le as Unicode UTF-8.
• Unicode (UTF-16). Reads the le as Unicode UTF-16 in the endianness of the operating system.
• Unicode (UTF-16BE). Reads the le as Unicode UTF-16, big endian.
• Unicode (UTF-16LE). Reads the le as Unicode UTF-16, little endian.
• Local Encoding. Reads the le in current locale code page character encoding.
If a le contains a Unicode byte order mark, it is read in that Unicode encoding, regardless of the encoding
you select. If a le does not contain a Unicode byte order mark, by default the encoding is assumed to be
the current locale code page character encoding, unless you select one of the Unicode encodings.
To change the current locale for data les in a different code page character encoding, select
Edit>Options from the menus, and change the locale on the Language tab.
Text Wizard: Step 1
The text le is displayed in a preview window. You can apply a predened format (previously saved from
the Text Wizard) or follow the steps in the Text Wizard to specify how the data should be read.
Text Wizard: Step 2
This step provides information about variables. A variable is similar to a eld in a database. For example,
each item in a questionnaire is a variable.
How are your variables arranged?
The arrangement of variables denes the method that is used to differentiate one variable from the
next.
Delimited
Spaces, commas, tabs, or other characters are used to separate variables. The variables are
recorded in the same order for each case but not necessarily in the same column locations.
Fixed width
Each variable is recorded in the same column location on the same record (line) for each case in
the data le. No delimiter is required between variables. The column location determines which
variable is being read.
Note: The Text Wizard cannot read xed-width Unicode text les. You can use the DATA LIST
command to read xed-width Unicode les.
Are variable names included at the top of your le?
The values on the specied line number are used to create variable names. Values that don't conform
to variable naming rules are converted to valid variable names.
What is the decimal symbol?
The character that indicates decimal values can be either a period or a comma.
Chapter 3. Data
les 11
Text Wizard: Step 3 (Delimited Files)
This step provides information about cases. A case is similar to a record in a database. For example, each
respondent to a questionnaire is a case.
The rst case of data begins on which line number? Indicates the rst line of the data le that contains
data values. If the top line(s) of the data le contain descriptive labels or other text that does not
represent data values, this will not be line 1.
How are your cases represented? Controls how the Text Wizard determines where each case ends and
the next one begins.
• Each line represents a case. Each line contains only one case. It is fairly common for each case to be
contained on a single line (row), even though this can be a very long line for data les with a large
number of variables. If not all lines contain the same number of data values, the number of variables for
each case is determined by the line with the greatest number of data values. Cases with fewer data
values are assigned missing values for the additional variables.
• A specic number of variables represents a case. The specied number of variables for each case
tells the Text Wizard where to stop reading one case and start reading the next. Multiple cases can be
contained on the same line, and cases can start in the middle of one line and be continued on the next
line. The Text Wizard determines the end of each case based on the number of values read, regardless
of the number of lines. Each case must contain data values (or missing values indicated by delimiters)
for all variables, or the data le will be read incorrectly.
How many cases do you want to import? You can import all cases in the data le, the rst n cases (n is a
number you specify), or a random sample of a specied percentage. Since the random sampling routine
makes an independent pseudo-random decision for each case, the percentage of cases selected can only
approximate the specied percentage. The more cases there are in the data le, the closer the
percentage of cases selected is to the specied percentage.
Text Wizard: Step 3 (Fixed-Width Files)
This step provides information about cases. A case is similar to a record in a database. For example, each
respondent to questionnaire is a case.
The rst case of data begins on which line number? Indicates the rst line of the data le that contains
data values. If the top line(s) of the data le contain descriptive labels or other text that does not
represent data values, this will not be line 1.
How many lines represent a case? Controls how the Text Wizard determines where each case ends and
the next one begins. Each variable is dened by its line number within the case and its column location.
You need to specify the number of lines for each case to read the data correctly.
How many cases do you want to import? You can import all cases in the data le, the rst n cases (n is a
number you specify), or a random sample of a specied percentage. Since the random sampling routine
makes an independent pseudo-random decision for each case, the percentage of cases selected can only
approximate the specied percentage. The more cases there are in the data le, the closer the
percentage of cases selected is to the specied percentage.
Text Wizard: Step 4 (Delimited Files)
This step species delimiters and text qualiers that are used in the text data le. You can also specify
the treatment of leading and trailing spaces in string values.
Which delimiters appear between variables?
The characters or symbols that separate data values. You can select any combination of spaces,
commas, semicolons, tabs, or other characters. Multiple, consecutive delimiters without intervening
data values are treated as missing values.
What is the text qualier?
Characters that are used to enclose values that contain delimiter characters. The text qualier
appears at both the beginning and the end of the value, enclosing the entire value.
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IBM SPSS Statistics 27 Core System User's Guide
Leading and Trailing Spaces
Controls the treatment of leading and trailing blank spaces in string values.
Remove leading spaces from string values
Any blank spaces at the beginning of string values are removed.
Remove trailing spaces from string values
Blank spaces at the end of a value are ignored when the dened width of string variables is
calculated. If Space is selected as a delimiter, multiple consecutive blank spaces are not treated
as multiple delimiters.
Text Wizard: Step 4 (Fixed-Width Files)
This step displays the Text Wizard's best guess on how to read the data le and allows you to modify how
the Text Wizard will read variables from the data le. Vertical lines in the preview window indicate where
the Text Wizard currently thinks each variable begins in the le.
Insert, move, and delete variable break lines as necessary to separate variables. If multiple lines are used
for each case, the data will be displayed as one line for each case, with subsequent lines appended to the
end of the line.
Notes:
For computer-generated data les that produce a continuous stream of data values with no intervening
spaces or other distinguishing characteristics, it may be difcult to determine where each variable begins.
Such data les usually rely on a data denition le or some other written description that species the
line and column location for each variable.
Text Wizard: Step 5
This step controls the variable name and the data format that is used to read each variable. You can also
specify variables to exclude.
Variable name
You can overwrite the default variable names with your own variable names. If you read variable
names from the data le, names that do not conform to variable naming rules are automatically
modied. Select a variable in the preview window and then enter a variable name.
Data format
Select a variable in the preview window and then select a format from the list.
• Automatic determines the data format based on an evaluation of all the data values.
• To exclude a variable, select Do Not Import.
Percentage of values that determine Automatic data format
For automatic format, the data format for each variable is determined by the percentage of values that
conform to the same format.
• The value must be greater than 50.
• The denominator used to determine the percentage is the number of non-blank values for each
variable.
• If no consistent format is used by the specied percentage of values, the variable is assigned the
string data type.
• For variables that are assigned a numeric format (including date and time formats) based on the
percentage value, values that do not conform to that format are assigned the system-missing value.
Formatting options
Formatting options for reading variables include:
Automatic
The format is determined based on an evaluation of all the data values.
Numeric
Valid values include numbers, a leading plus or minus sign, and a decimal indicator.
Chapter 3. Data
les 13
String
Valid values include virtually any keyboard characters and embedded blanks. For delimited les, you
can specify the number of characters in the value, up to a maximum of 32,767. By default, the value is
set to the number of characters to the longest string value encountered for the selected variable(s) in
the rst 250 rows of the le. For xed-width les, the number of characters in string values is dened
by the placement of variable break lines.
Date/Time
Valid values include dates of the general format dd-mm-yyyy, mm/dd/yyyy, dd.mm.yyyy, yyyy/mm/dd,
hh:mm:ss, and a variety of other date and time formats. Months can be represented in digits, Roman
numerals, or three-letter abbreviations, or they can be fully spelled out. Select a date format from the
list.
Dollar
Valid values are numbers with an optional leading dollar sign and optional commas as thousands
separators.
Comma
Valid values include numbers that use a period as a decimal indicator and commas as thousands
separators.
Dot
Valid values include numbers that use a comma as a decimal indicator and periods as thousands
separators.
Do not import
Omit the selected variable(s) from the imported data le.
Note: Values that contain invalid characters for the selected format will be treated as missing. Values that
contain any of the specied delimiters will be treated as multiple values.
Text Wizard: Step 6
This is the nal step of the Text Wizard. You can save your specications in a le for use when importing
similar text data les. You can also paste the syntax generated by the Text Wizard into a syntax window.
You can then customize and/or save the syntax for use in other sessions or in production jobs.
Cache data locally. A data cache is a complete copy of the data le, stored in temporary disk space.
Caching the data le can improve performance.
Reading Database Files
You can read data from any database format for which you have a database driver. In local analysis mode,
the necessary drivers must be installed on your local computer. In distributed analysis mode (available
with IBM SPSS Statistics Server), the drivers must be installed on the remote server. See the topic
Chapter 4, “Distributed Analysis Mode,” on page 41
for more information.
Note: If you are running the Windows 64-bit version of IBM SPSS Statistics, you cannot read Excel,
Access, or dBASE database sources, even though they may appear on the list of available database
sources. The 32-bit ODBC drivers for these products are not compatible.
To Read Database Files
1. From the menus choose:
File > Import Data > Database > New Query...
2. Select the data source.
3. If necessary (depending on the data source), select the database le and/or enter a login name,
password, and other information.
4. Select the table(s) and elds. For OLE DB data sources (available only on Windows operating systems),
you can only select one table.
5. Specify any relationships between your tables.
6. Optionally:
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IBM SPSS Statistics 27 Core System User's Guide
• Specify any selection criteria for your data.
• Add a prompt for user input to create a parameter query.
• Save your constructed query before running it.
Connection Pooling
If you access the same database source multiple times in the same session or job, you can improve
performance with connection pooling.
1. In the last step of the wizard, paste the command syntax into a syntax window.
2. At the end of the quoted CONNECT string, add Pooling=true.
To Edit Saved Database Queries
1. From the menus choose:
File > Import Data > Database > Edit Query...
2. Select the query le (*.spq) that you want to edit.
3. Follow the instructions for creating a new query.
To Read Database Files with Saved Queries
1. From the menus choose:
File > Import Data > Database > Run Query...
2. Select the query le (*.spq) that you want to run.
3. If necessary (depending on the database le), enter a login name and password.
4. If the query has an embedded prompt, enter other information if necessary (for example, the quarter
for which you want to retrieve sales gures).
Selecting a Data Source
Use the rst screen of the Database Wizard to select the type of data source to read.
ODBC Data Sources
If you do not have any ODBC data sources congured, or if you want to add a new data source, click Add
ODBC Data Source.
• On Linux operating systems, this button is not available. ODBC data sources are specied in odbc.ini,
and the ODBCINI environment variables must be set to the location of that le. For more information,
see the documentation for your database drivers.
• In distributed analysis mode (available with IBM SPSS Statistics Server), this button is not available. To
add data sources in distributed analysis mode, see your system administrator.
An ODBC data source consists of two essential pieces of information: the driver that will be used to
access the data and the location of the database you want to access. To specify data sources, you must
have the appropriate drivers installed. Drivers for a variety of database formats are included with the
installation media.
Selecting Data Fields
The Select Data step controls which tables and elds are read. Database elds (columns) are read as
variables.
If a table has any eld(s) selected, all of its elds will be visible in the following Database Wizard
windows, but only elds that are selected in this step will be imported as variables. This enables you to
create table joins and to specify criteria by using elds that you are not importing.
Displaying eld names. To list the elds in a table, click the plus sign (+) to the left of a table name. To
hide the elds, click the minus sign (–) to the left of a table name.
Chapter 3. Data
les 15
To add a eld. Double-click any eld in the Available Tables list, or drag it to the Retrieve Fields In This
Order list. Fields can be reordered by dragging and dropping them within the elds list.
To remove a eld. Double-click any eld in the Retrieve Fields In This Order list, or drag it to the
Available Tables list.
Sort eld names. If this check box is selected, the Database Wizard will display your available elds in
alphabetical order.
By default, the list of available tables displays only standard database tables. You can control the type of
items that are displayed in the list:
• Tables. Standard database tables.
• Views. Views are virtual or dynamic "tables" dened by queries. These can include joins of multiple
tables and/or elds derived from calculations based on the values of other elds.
• Synonyms. A synonym is an alias for a table or view, typically dened in a query.
• System tables. System tables dene database properties. In some cases, standard database tables
may be classied as system tables and will only be displayed if you select this option. Access to real
system tables is often restricted to database administrators.
Note: For OLE DB data sources (available only on Windows operating systems), you can select elds only
from a single table. Multiple table joins are not supported for OLE DB data sources.
Creating a Relationship between Tables
The Specify Relationships step allows you to dene the relationships between the tables for ODBC data
sources. If elds from more than one table are selected, you must dene at least one join.
Establishing relationships. To create a relationship, drag a eld from any table onto the eld to which
you want to join it. The Database Wizard will draw a join line between the two elds, indicating their
relationship. These elds must be of the same data type.
Auto Join Tables. Attempts to automatically join tables based on primary/foreign keys or matching eld
names and data type.
Join Type. If outer joins are supported by your driver, you can specify inner joins, left outer joins, or right
outer joins.
• Inner joins. An inner join includes only rows where the related elds are equal. In this example, all
rows with matching ID values in the two tables will be included.
• Outer joins. In addition to one-to-one matching with inner joins, you can also use outer joins to merge
tables with a one-to-many matching scheme. For example, you could match a table in which there are
only a few records representing data values and associated descriptive labels with values in a table
containing hundreds or thousands of records representing survey respondents. A left outer join includes
all records from the table on the left and, from the table on the right, includes only those records in
which the related elds are equal. In a right outer join, the join imports all records from the table on the
right and, from the table on the left, imports only those records in which the related elds are equal.
Computing New Fields
If you are in distributed mode, connected to a remote server (available with IBM SPSS Statistics Server),
you can compute new elds before you read the data into IBM SPSS Statistics.
You can also compute new elds after you read the data into IBM SPSS Statistics, but computing new
elds in the database can save time for large data sources.
New Field Name. The name must comply with IBM SPSS Statistics variable name rules.
Expression. Enter the expression to compute the new eld. You can drag existing eld names from the
Fields list and functions from the Functions list.
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IBM SPSS Statistics 27 Core System User's Guide
Limiting Retrieved Cases
The Limit Retrieved Cases step allows you to specify the criteria to select subsets of cases (rows).
Limiting cases generally consists of lling the criteria grid with criteria. Criteria consist of two expressions
and some relation between them. The expressions return a value of true, false, or missing for each case.
• If the result is true, the case is selected.
• If the result is false or missing, the case is not selected.
• Most criteria use one or more of the six relational operators (<, >, <=, >=, =, and <>).
• Expressions can include eld names, constants, arithmetic operators, numeric and other functions, and
logical variables. You can use elds that you do not plan to import as variables.
To build your criteria, you need at least two expressions and a relation to connect the expressions.
1. To build an expression, choose one of the following methods:
• In an Expression cell, type eld names, constants, arithmetic operators, numeric and other
functions, or logical variables.
• Double-click the eld in the Fields list.
• Drag the eld from the Fields list to an Expression cell.
• Choose a eld from the drop-down menu in any active Expression cell.
2. To choose the relational operator (such as = or >), put your cursor in the Relation cell and either type
the operator or choose it from the drop-down menu.
If the SQL contains WHERE clauses with expressions for case selection, dates and times in expressions
need to be specied in a special manner (including the curly braces shown in the examples):
• Date literals should be specied using the general form {d 'yyyy-mm-dd'}.
• Time literals should be specied using the general form {t 'hh:mm:ss'}.
• Date/time literals (timestamps) should be specied using the general form {ts 'yyyy-mm-dd
hh:mm:ss'}.
• The entire date and/or time value must be enclosed in single quotes. Years must be expressed in
four-digit form, and dates and times must contain two digits for each portion of the value. For
example January 1, 2005, 1:05 AM would be expressed as:
{ts '2005-01-01 01:05:00'}
Functions. A selection of built-in arithmetic, logical, string, date, and time SQL functions is provided.
You can drag a function from the list into the expression, or you can enter any valid SQL function. See
your database documentation for valid SQL functions.
Use Random Sampling. This option selects a random sample of cases from the data source. For large
data sources, you may want to limit the number of cases to a small, representative sample, which can
signicantly reduce the time that it takes to run procedures. Native random sampling, if available for
the data source, is faster than IBM SPSS Statistics random sampling, because IBM SPSS Statistics
random sampling must still read the entire data source to extract a random sample.
• Approximately. Generates a random sample of approximately the specied percentage of cases.
Since this routine makes an independent pseudorandom decision for each case, the percentage of
cases selected can only approximate the specied percentage. The more cases there are in the data
le, the closer the percentage of cases selected is to the specied percentage.
• Exactly. Selects a random sample of the specied number of cases from the specied total number
of cases. If the total number of cases specied exceeds the total number of cases in the data le, the
sample will contain proportionally fewer cases than the requested number.
Note: If you use random sampling, aggregation (available in distributed mode with IBM SPSS Statistics
Server) is not available.
Prompt For Value. You can embed a prompt in your query to create a parameter query. When users
run the query, they will be asked to enter information (based on what is specied here). You might
Chapter 3. Data
les 17
want to do this if you need to see different views of the same data. For example, you may want to run
the same query to see sales gures for different scal quarters.
3. Place your cursor in any Expression cell, and click Prompt For Value to create a prompt.
Creating a Parameter Query
Use the Prompt for Value step to create a dialog box that solicits information from users each time
someone runs your query. This feature is useful if you want to query the same data source by using
different criteria.
To build a prompt, enter a prompt string and a default value. The prompt string is displayed each time a
user runs your query. The string should specify the kind of information to enter. If the user is not selecting
from a list, the string should give hints about how the input should be formatted. An example is as
follows: Enter a Quarter (Q1, Q2, Q3, ...).
Allow user to select value from list. If this check box is selected, you can limit the user to the values that
you place here. Ensure that your values are separated by returns.
Data type. Choose the data type here (Number, String, or Date).
Date and time values must be entered in special manner:
• Date values must use the general form yyyy-mm-dd.
• Time values must use the general form: hh:mm:ss.
• Date/time values (timestamps) must use the general form yyyy-mm-dd hh:mm:ss.
Aggregating Data
If you are in distributed mode, connected to a remote server (available with IBM SPSS Statistics Server),
you can aggregate the data before reading it into IBM SPSS Statistics.
You can also aggregate data after reading it into IBM SPSS Statistics, but preaggregating may save time
for large data sources.
1. To create aggregated data, select one or more break variables that dene how cases are grouped.
2. Select one or more aggregated variables.
3. Select an aggregate function for each aggregate variable.
4. Optionally, create a variable that contains the number of cases in each break group.
Note: If you use IBM SPSS Statistics random sampling, aggregation is not available.
Dening Variables
Variable names and labels. The complete database eld (column) name is used as the variable label.
Unless you modify the variable name, the Database Wizard assigns variable names to each column from
the database in one of two ways:
• If the name of the database eld forms a valid, unique variable name, the name is used as the variable
name.
• If the name of the database eld does not form a valid, unique variable name, a new, unique name is
automatically generated.
Click any cell to edit the variable name.
Converting strings to numeric values. Select the Recode to Numeric box for a string variable if you want
to automatically convert it to a numeric variable. String values are converted to consecutive integer values
based on alphabetical order of the original values. The original values are retained as value labels for the
new variables.
Width for variable-width string elds. This option controls the width of variable-width string values. By
default, the width is 255 bytes, and only the rst 255 bytes (typically 255 characters in single-byte
languages) will be read. The width can be up to 32,767 bytes. Although you probably don't want to
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IBM SPSS Statistics 27 Core System User's Guide
truncate string values, you also don't want to specify an unnecessarily large value, which will cause
processing to be inefcient.
Minimize string widths based on observed values. Automatically set the width of each string variable to
the longest observed value.
Sorting Cases
If you are in distributed mode, connected to a remote server (available with IBM SPSS Statistics Server),
you can sort the data before reading it into IBM SPSS Statistics.
You can also sort data after reading it into IBM SPSS Statistics, but presorting may save time for large
data sources.
Results
The Results step displays the SQL Select statement for your query.
• You can edit the SQL Select statement before you run the query, but if you click the Back button to
make changes in previous steps, the changes to the Select statement will be lost.
• To save the query for future use, use the Save query to le section.
• To paste complete GET DATA syntax into a syntax window, select Paste it into the syntax editor for
further modication. Copying and pasting the Select statement from the Results window will not paste
the necessary command syntax.
Note: The pasted syntax contains a blank space before the closing quote on each line of SQL that is
generated by the wizard. These blanks are not superfluous. When the command is processed, all lines of
the SQL statement are merged together in a very literal fashion. Without the space, there would be no
space between the last character on one line and rst character on the next line.
Reading Cognos BI data
If you have access to a IBM Cognos Business Intelligence server, you can read IBM Cognos Business
Intelligence data packages and list reports into IBM SPSS Statistics.
To read IBM Cognos Business Intelligence data:
Important: Cognos BI data will not fully import when a Cognos Analytics Administrator license is not
present. You must either already have, or purchase, a Cognos Analytics Administrator license prior to
importing Cognos BI data. Users who import Cognos BI data must have their role set as "System
Administrator". For more information on license roles in Cognos Analytics, see How do you restrict users
based on their License Roles in Cognos Analytics (versions 11.0.0 to 11.0.6).
1. From the menus choose:
File > Import Data > Cognos Business Intelligence
2. Specify the URL for the IBM Cognos Business Intelligence server connection.
3. Specify the location of the data package or report.
4. Select the data elds or report that you want to read.
Optionally, you can:
• Select lters for data packages.
• Import aggregated data instead of raw data.
• Specify parameter values.
Mode. Species the type of information you want to read: Data or Report. The only type of report that can
be read is a list report.
Connection. The URL of the Cognos Business Intelligence server. Click the Edit button to dene the
details of a new Cognos connection from which to import data or reports. See the topic “Cognos
connections” on page 20 for more information.
Chapter 3. Data
les 19
Location. The location of the package or report that you want to read. Click the Edit button to display a
list of available sources from which to import content. See the topic “Cognos location” on page 20 for
more information.
Content. For data, displays the available data packages and lters. For reports, display the available
reports.
Fields to import. For data packages, select the elds you want to include and move them to this list.
Report to import. For reports, select the list report you want to import. The report must be a list report.
Filters to apply. For data packages, select the lters you want to apply and move them to this list.
Parameters. If this button is enabled, the selected object has parameters dened. You can use
parameters to make adjustments (for example, perform a parameterized calculation) before importing
the data. If parameters are dened but no default is provided, the button displays a warning triangle.
Aggregate data before performing import. For data packages, if aggregation is dened in the package,
you can import the aggregated data instead of the raw data.
Cognos connections
The Cognos Connections dialog species the IBM Cognos Business Intelligence server URL and any
required additional credentials.
Cognos server URL. The URL of the IBM Cognos Business Intelligence server. This is the value of the
"external dispatcher URI" environment property of IBM Cognos Conguration on the server. Contact your
system administrator for more information
Mode. Select Set Credentials if you need to log in with a specic namespace, username and password
(for example, as an administrator). Select Use Anonymous connection to log in with no user credentials,
in which case you do not ll in the other elds. Select Stored Credentials to use the login information
from a stored credential. To use a stored credential, you must be connected to the IBM SPSS
Collaboration and Deployment Services Repository that contains the credential. After you are connected
to the repository, click Browse to see the list of available credentials.
Namespace ID. The security authentication provider used to log on to the server. The authentication
provider is used to dene and maintain users, groups, and roles, and to control the authentication
process.
User name. Enter the user name with which to log on to the server.
Password. Enter the password associated with the specied user name.
Save as Default. Saves these settings as your default, to avoid having to re-enter them each time.
Cognos location
The Specify Location dialog box enables you to select a package from which to import data, or a package
or folder from which to import reports. It displays the public folders that are available to you. If you select
Data in the main dialog, the list will display folders containing data packages. If you select Report in the
main dialog, the list will display folders containing list reports. Select the location you want by navigating
through the folder structure.
Specifying parameters for data or reports
If parameters have been dened, either for a data object or a report, you can specify values for these
parameters before importing the data or report. An example of parameters for a report would be start and
end dates for the report contents.
Name. The parameter name as it is specied in the IBM Cognos Business Intelligence database.
Type. A description of the parameter.
Value. The value to assign to the parameter. To enter or edit a value, double-click its cell in the table.
Values are not validated here; any invalid values are detected at run time.
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IBM SPSS Statistics 27 Core System User's Guide
Automatically remove invalid parameters from table. This option is selected by default and will remove
any invalid parameters found within the data object or report.
Changing variable names
For IBM Cognos Business Intelligence data packages, package eld names are automatically converted to
valid variable names. You can use the Fields tab of the Read Cognos Data dialog to override the default
names. Names must be unique and must conform to variable naming rules. See the topic “Variable
names” on page 46 for more information.
Reading Cognos TM1 data
If you have access to an IBM Cognos TM1
®
database, you can import TM1 data from a specied view into
IBM SPSS Statistics. The multidimensional OLAP cube data from TM1 is flattened when read into SPSS
Statistics.
Important: To enable the exchange of data between SPSS Statistics and TM1, you must copy the
following three processes from SPSS Statistics to the TM1 server: ExportToSPSS.pro,
ImportFromSPSS.pro, and SPSSCreateNewMeasures.pro. To add these processes to the TM1
server, you must copy them to the data directory of the TM1 server and restart the TM1 server. These les
are available from the common/scripts/TM1 directory under the SPSS Statistics installation directory.
Restriction:
• The TM1 view from which you import must include one or more elements from a measure dimension.
• The data to be imported from TM1 must be in UTF-8 format.
All of the data in the specied TM1 view are imported. It is therefore best to limit the view to the data that
are required for the analysis. Any necessary ltering of the data is best done in TM1, for example with the
TM1 Subset Editor.
To read TM1 data:
1. From the menus, choose:
File > Import Data > Cognos TM1
2. Connect to the TM1 Performance Management system.
3. Log in to the TM1 server.
4. Select a TM1 cube and select the view that you want to import.
Optionally, you can override the default names of the SPSS Statistics variables that are created from the
names of the TM1 dimensions and measures.
PM System
The URL of the Performance Management system that contains the TM1 server to which you want to
connect. The Performance Management system is dened as a single URL for all TM1 servers. From
this URL, all TM1 servers that are installed and running on your environment can be discovered and
accessed. Enter the URL and click Connect.
TM1 Server
When the connection to the Performance Management system is established, select the server that
contains the data you want to import and click Login. If you did not previously connect to this server,
you are prompted to log in.
Username and password
Select this option to log in with a specic username and password. If the server uses
authentication mode 5 (IBM Cognos security), then select the namespace that identies the
security authentication provider from the available list.
Stored credential
Select this option to use the login information from a stored credential. To use a stored credential,
you must be connected to the IBM SPSS Collaboration and Deployment Services Repository that
contains the credential. After you are connected to the repository, click Browse to see the list of
available credentials.
Chapter 3. Data
les 21
Select a TM1 cube view to import
Lists the names of the cubes within the TM1 server from which you can import data. Double-click a
cube to display a list of the views that you can import. Select a view and click the right arrow to move
it into the View to import eld.
Column dimension(s)
Lists the names of the column dimensions in the selected view.
Row dimension(s)
Lists the names of the row dimensions in the selected view.
Context dimension(s)
Lists the names of the context dimensions in the selected view.
Note:
• When the data are imported, a separate SPSS Statistics variable is created for each regular dimension
and for each element in the measure dimension.
• Empty cells and cells with a value of zero in TM1 are converted to the system-missing value.
• Cells with string values that cannot be converted to a numeric value are converted to the system-
missing value.
Changing variable names
By default, valid IBM SPSS Statistics variable names are automatically generated from the dimension
names and names of elements in the measure dimension from the selected IBM Cognos TM1 cube view.
You can use the Fields tab of the Import from TM1 dialog to override the default names. Names must be
unique and must conform to variable naming rules.
File information
A data le contains much more than raw data. It also contains any variable denition information,
including:
• Variable names
• Variable formats
• Descriptive variable and value labels
This information is stored in the dictionary portion of the data le. The Data Editor provides one way to
view the variable denition information. You can also display complete dictionary information for the
active dataset or any other data le.
To Display Data File Information
1. From the menus in the Data Editor window choose:
File > Display Data File Information
2. For the currently open data le, choose Working File.
3. For other data les, choose External File, and then select the data le.
The data le information is displayed in the Viewer.
Saving data les
In addition to saving data les in IBM SPSS Statistics format, you can save data in a wide variety of
external formats, including:
• Excel and other spreadsheet formats
• Tab-delimited and CSV text les
• SAS
• Stata
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IBM SPSS Statistics 27 Core System User's Guide
• Database tables
To save modied data les
1. Make the Data Editor the active window (click anywhere in the window to make it active).
2. From the menus choose:
File > Save
The modied data le is saved, overwriting the previous version of the le.
To save data les in code page character encoding
Unicode data les cannot be read by IBM SPSS Statistics versions prior to version 16.0. In Unicode mode,
to save a data le in code page character encoding:
1. Make the Data Editor the active window (click anywhere in the window to make it active).
2. From the menus choose:
File > Save As
3. From the Save as type drop-down list in the Save Data dialog, select SPSS Statistics Local Encoding.
4. Enter a name for the new data le.
The modied data le is saved in the current locale code page character encoding. This action has no
effect on the active dataset. The encoding of the active dataset is not changed. Saving a le in code page
character encoding is similar to saving a le in an external format, such as tab-delimited text or Excel.
Saving data les in external formats
1. Make the Data Editor the active window (click anywhere in the window to make it active).
2. From the menus choose:
File > Save As...
3. Select a le type from the drop-down list.
4. Enter a le name for the new data le.
Options
Depending on the le type, additional options are available.
Encoding
Available for SAS les and text data formats: tab-delimited, comma-delimited, and xed ASCII text.
Write variable names to le
Available for Excel, tab-delimited, comma-delimited, 1-2-3, and SYLK. For Excel 97 and later
versions, you can write either variable names or labels. For variables without dened variable labels,
the variable name is used.
Sheet name
For Excel 2007 and later versions, you can specify a sheet name. You can also append a sheet to an
existing le.
Save value labels to a .sas le
SAS 6 and later versions.
For information on exporting data to database tables, see “Exporting to a Database” on page 29
.
Saving data: Data le types
You can save data in the following formats:
SPSS Statistics (*.sav). IBM SPSS Statistics format.
Chapter 3. Data
les 23
• Data les saved in IBM SPSS Statistics format cannot be read by versions of the software prior to
version 7.5. Data les saved in Unicode encoding cannot be read by releases of IBM SPSS Statistics
prior to version 16.0
• When using data les with variable names longer than eight bytes in version 10.x or 11.x, unique, eight-
byte versions of variable names are used—but the original variable names are preserved for use in
release 12.0 or later. In releases prior to 10.0, the original long variable names are lost if you save the
data le.
• When using data les with string variables longer than 255 bytes in versions prior to release 13.0, those
string variables are broken up into multiple 255-byte string variables.
SPSS Statistics Compressed (*.zsav). Compressed IBM SPSS Statistics format.
• ZSAV les have the same features as SAV les, but they take up less disk space.
• ZSAV les may take more or less time to open and save, depending on the le size and system
conguration. Extra time is needed to de-compress and compress ZSAV les. However, because ZSAV
les are smaller on disk, they reduce the time needed to read and write from disk. As the le size gets
larger, this time savings surpasses the extra time needed to de-compress and compress the les.
• Only IBM SPSS Statistics version 21 or higher can open ZSAV les.
• The option to save the data le with your local code page encoding is not available for ZSAV les. These
les are always saved in UTF-8 encoding.
SPSS Statistics Local Encoding (*.sav). In Unicode mode, this option saves the data le in the current
locale code page character encoding. This option is not available in code page mode.
SPSS 7.0 (*.sav). Version 7.0 format. Data les saved in version 7.0 format can be read by version 7.0
and earlier versions but do not include dened multiple response sets or Data Entry for Windows
information.
SPSS/PC+ (*.sys). SPSS/PC+ format. If the data le contains more than 500 variables, only the rst 500
will be saved. For variables with more than one dened user-missing value, additional user-missing
values will be recoded into the rst dened user-missing value. This format is available only on Windows
operating systems.
Portable (*.por). Portable format that can be read by other versions of IBM SPSS Statistics and versions
on other operating systems. Variable names are limited to eight bytes and are automatically converted to
unique eight-byte names if necessary. In most cases, saving data in portable format is no longer
necessary, since IBM SPSS Statistics data les should be platform/operating system independent. You
cannot save data les in portable le in Unicode mode. See the topic “General options” on page 179
for
more information.
Tab-delimited (*.dat). Text les with values separated by tabs. (Note: Tab characters embedded in string
values are preserved as tab characters in the tab-delimited le. No distinction is made between tab
characters embedded in values and tab characters that separate values.) You can save les in Unicode
encoding or local code page encoding.
Comma-delimited (*.csv). Text les with values separated by commas or semicolons. If the current IBM
SPSS Statistics decimal indicator is a period, values are separated by commas. If the current decimal
indicator is a comma, values are separated by semicolons. You can save les in Unicode encoding or local
code page encoding.
Fixed ASCII (*.dat). Text le in xed format, using the default write formats for all variables. There are
no tabs or spaces between variable elds. You can save les in Unicode encoding or local code page
encoding.
Excel 2007 (*.xlsx). Microsoft Excel 2007 XLSX-format workbook. The maximum number of variables is
16,000; any additional variables beyond the rst 16,000 are dropped. If the dataset contains more than
one million cases, multiple sheets are created in the workbook.
Excel 97 through 2003 (*.xls). Microsoft Excel 97 workbook. The maximum number of variables is 256;
any additional variables beyond the rst 256 are dropped. If the dataset contains more than 65,356
cases, multiple sheets are created in the workbook.
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IBM SPSS Statistics 27 Core System User's Guide
Excel 2.1 (*.xls). Microsoft Excel 2.1 spreadsheet le. The maximum number of variables is 256, and the
maximum number of rows is 16,384.
1-2-3 Release 3.0 (*.wk3). Lotus 1-2-3 spreadsheet le, release 3.0. The maximum number of variables
that you can save is 256.
1-2-3 Release 2.0 (*.wk1). Lotus 1-2-3 spreadsheet le, release 2.0. The maximum number of variables
that you can save is 256.
1-2-3 Release 1.0 (*.wks). Lotus 1-2-3 spreadsheet le, release 1A. The maximum number of variables
that you can save is 256.
SYLK (*.slk). Symbolic link format for Microsoft Excel and Multiplan spreadsheet les. The maximum
number of variables that you can save is 256.
dBASE IV (*.dbf). dBASE IV format.
dBASE III (*.dbf). dBASE III format.
dBASE II (*.dbf). dBASE II format.
SAS v9+ Windows (*.sas7bdat). SAS versions 9 for Windows. You can save les in Unicode (UTF-8) or
local code page encoding.
SAS v9+ UNIX (*.sas7bdat). SAS versions 9 for UNIX. You can save les in Unicode (UTF-8) or local code
page encoding.
SAS v7-8 Windows short extension (*.sd7). SAS versions 7–8 for Windows short lename format.
SAS v7-8 Windows long extension (*.sas7bdat). SAS versions 7–8 for Windows long lename format.
SAS v7-8 for UNIX (*.sas7bdat). SAS v8 for UNIX.
SAS v6 for Windows (*.sd2). SAS v6 le format for Windows/OS2.
SAS v6 for UNIX (*.ssd01). SAS v6 le format for UNIX (Sun, HP, IBM).
SAS v6 for Alpha/OSF (*.ssd04). SAS v6 le format for Alpha/OSF (DEC UNIX).
SAS Transport (*.xpt). SAS transport le.
Stata Version 13 Intercooled (*.dta).
Stata Version 13 SE (*.dta).
Stata Version 12 Intercooled (*.dta).
Stata Version 12 SE (*.dta).
Stata Version 11 Intercooled (*.dta).
Stata Version 11 SE (*.dta).
Stata Version 10 Intercooled (*.dta).
Stata Version 10 SE (*.dta).
Stata Version 9 Intercooled (*.dta).
Stata Version 9 SE (*.dta).
Stata Version 8 Intercooled (*.dta).
Stata Version 8 SE (*.dta).
Stata Version 7 Intercooled (*.dta).
Stata Version 7 SE (*.dta).
Stata Version 6 (*.dta).
Stata Versions 4–5 (*.dta).
Chapter 3. Data
les 25
Note: SAS data le names can be up to 32 characters in length. Blank spaces and non-alphanumeric
characters other than the underscore ("_") are not allowed and names have to start with a letter or an
underscore, numbers can follow.
Saving data les in Excel format
You can save your data in one of three Microsoft Excel le formats. Excel 2.1, Excel 97, and Excel 2007.
• Excel 2.1 and Excel 97 are limited to 256 columns; so only the rst 256 variables are included.
• Excel 2007 is limited to 16,000 columns; so only the rst 16,000 variables are included.
• Excel 2.1 is limited to 16,384 rows; so only the rst 16,384 cases are included.
• Excel 97 and Excel 2007 also have limits on the number of rows per sheet, but workbooks can have
multiple sheets, and multiple sheets are created if the single-sheet maximum is exceeded.
Options
• For all versions of Excel, you can include variable names as the rst row of the Excel le.
• For Excel 97 and later versions, you can write either variable names or labels. For variables without
dened variable labels, the variable name is used.
• For Excel 2007 and later versions, you can specify a sheet name. You can also append a sheet to an
existing le.
Variable types
The following table shows the variable type matching between the original data in IBM SPSS Statistics
and the exported data in Excel.
Table 2. How Excel data formats map to IBM SPSS Statistics variable types and formats
IBM SPSS Statistics Variable Type Excel Data Format
Numeric 0.00; #,##0.00; ...
Comma 0.00; #,##0.00; ...
Dollar $#,##0_); ...
Date d-mmm-yyyy
Time hh:mm:ss
String General
Saving data les in SAS format
Special handling is given to various aspects of your data when saved as a SAS le. These cases include:
• Certain characters that are allowed in IBM SPSS Statistics variable names are not valid in SAS, such as
@, #, and $. These illegal characters are replaced with an underscore when the data are exported.
• IBM SPSS Statistics variable names that contain multibyte characters (for example, Japanese or
Chinese characters) are converted to variables names of the general form Vnnn, where nnn is an integer
value.
• IBM SPSS Statistics variable labels containing more than 40 characters are truncated when exported to
a SAS v6 le.
• Where they exist, IBM SPSS Statistics variable labels are mapped to the SAS variable labels. If no
variable label exists in the IBM SPSS Statistics data, the variable name is mapped to the SAS variable
label.
• SAS allows only one value for system-missing, whereas IBM SPSS Statistics allows numerous user-
missing values in addition to system-missing. As a result, all user-missing values in IBM SPSS Statistics
are mapped to a single system-missing value in the SAS le.
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IBM SPSS Statistics 27 Core System User's Guide
• SAS 6-8 data les are saved in the current IBM SPSS Statistics locale encoding, regardless of current
mode (Unicode or code page). In Unicode mode, SAS 9 les are saved in UTF-8 format. In code page
mode, SAS 9 les are saved in the current locale encoding.
• A maximum of 32,767 variables can be saved to SAS 6-8.
• SAS data le names can be up to 32 characters in length. Blank spaces and non-alphanumeric
characters other than the underscore ("_") are not allowed and names have to start with a letter or an
underscore, numbers can follow.
Save value labels
You have the option of saving the values and value labels associated with your data le to a SAS syntax
le. This syntax le contains proc format and proc datasets commands that can be run in SAS to
create a SAS format catalog le.
This feature is not supported for the SAS transport le.
Variable types
The following table shows the variable type matching between the original data in IBM SPSS Statistics
and the exported data in SAS.
Table 3. How SAS variable types and formats map to IBM SPSS Statistics types and formats
IBM SPSS Statistics Variable
Type
SAS Variable Type SAS Data Format
Numeric Numeric 12
Comma Numeric 12
Dot Numeric 12
Scientic Notation Numeric 12
Date Numeric (Date) for example,
MMDDYY10, ...
Date (Time) Numeric Time18
Dollar Numeric 12
Custom Currency Numeric 12
String Character $8
Saving data les in Stata format
• Data can be written in Stata 5–13 format and in both Intercooled and SE format (version 7 or later).
• Data les that are saved in Stata 5 format can be read by Stata 4.
• The rst 80 bytes of variable labels are saved as Stata variable labels.
• For Stata releases 4-8, the rst 80 bytes of value labels for numeric variables are saved as Stata value
labels. For Stata release 9 or later, the complete value labels for numeric variables are saved. Value
labels are dropped for string variables, non-integer numeric values, and numeric values greater than an
absolute value of 2,147,483,647.
• For versions 7 and later, the rst 32 bytes of variable names in case-sensitive form are saved as Stata
variable names. For earlier versions, the rst eight bytes of variable names are saved as Stata variable
names. Any characters other than letters, numbers, and underscores are converted to underscores.
• IBM SPSS Statistics variable names that contain multi-byte characters (for example, Japanese or
Chinese characters) are converted to generic single-byte variable names.
Chapter 3. Data
les 27
• For versions 5–6 and Intercooled versions 7 and later, the rst 80 bytes of string values are saved. For
Stata SE 7–12, the rst 244 bytes of string values are saved. For Stata SE 13 or later, complete string
values are saved, regardless of length.
• For versions 5–6 and Intercooled versions 7 and later, only the rst 2,047 variables are saved. For Stata
SE 7 or later, only the rst 32,767 variables are saved.
Table 4. How Stata variable type and format map to IBM SPSS Statistics type and format
IBM SPSS Statistics Variable
Type
Stata Variable Type Stata Data Format
Numeric Numeric g
Comma Numeric g
Dot Numeric g
Scientic Notation Numeric g
Date*, Datetime Numeric D_m_Y
Time, DTime Numeric g (number of seconds)
Wkday Numeric g (1–7)
Month Numeric g (1–12)
Dollar Numeric g
Custom Currency Numeric g
String String s
*Date, Adate, Edate, SDate, Jdate, Qyr, Moyr, Wkyr
Saving Subsets of Variables
The Save Data As Variables dialog box allows you to select the variables that you want saved in the new
data le. By default, all variables will be saved. Deselect the variables that you don't want to save, or click
Drop All and then select the variables that you want to save.
Visible Only. Selects only variables in variable sets currently in use. See the topic “Using variable sets to
show and hide variables” on page 176 for more information.
To Save a Subset of Variables
1. Make the Data Editor the active window (click anywhere in the window to make it active).
2. From the menus choose:
File > Save As...
3. Click Variables.
4. Select the variables that you want to save.
Encrypting data les
For IBM SPSS Statistics data les, you can protect condential information stored in a data le by
encrypting the le with a password. Once encrypted, the le can only be opened by providing the
password.
1. Make the Data Editor the active window (click anywhere in the window to make it active).
2. From the menus choose:
File > Save As...
3. Select Encrypt le with password in the Save Data As dialog box.
4. Click Save.
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IBM SPSS Statistics 27 Core System User's Guide
5. In the Encrypt File dialog box, provide a password and re-enter it in the Conrm password text box.
Passwords are limited to 10 characters and are case-sensitive.
Warning: Passwords cannot be recovered if they are lost. If the password is lost the le cannot be
opened.
Creating strong passwords
• Use eight or more characters.
• Include numbers, symbols and even punctuation in your password.
• Avoid sequences of numbers or characters, such as "123" and "abc", and avoid repetition, such as
"111aaa".
• Do not create passwords that use personal information such as birthdays or nicknames.
• Periodically change the password.
Note: Storing encrypted les to an IBM SPSS Collaboration and Deployment Services Repository is not
supported.
Modifying encrypted les
• If you open an encrypted le, make modications to it and choose File > Save, the modied le will be
saved with the same password.
• You can change the password on an encrypted le by opening the le, repeating the steps for
encrypting it, and specifying a different password in the Encrypt File dialog box.
• You can save an unencrypted version of an encrypted le by opening the le, choosing File > Save As
and deselecting Encrypt le with password in the Save Data As dialog box.
Note: Encrypted data les and output documents cannot be opened in versions of IBM SPSS Statistics
prior to version 21. Encrypted syntax les cannot be opened in versions prior to version 22.
Exporting to a Database
You can use the Export to Database Wizard to:
• Replace values in existing database table elds (columns) or add new elds to a table.
• Append new records (rows) to a database table.
• Completely replace a database table or create a new table.
To export data to a database:
1. From the menus in the Data Editor window for the dataset that contains the data you want to export,
choose:
File > Export > Database
2. Select the database source.
3. Follow the instructions in the export wizard to export the data.
Creating Database Fields from IBM SPSS Statistics Variables
When creating new elds (adding elds to an existing database table, creating a new table, replacing a
table), you can specify eld names, data type, and width (where applicable).
Field name. The default eld names are the same as the IBM SPSS Statistics variable names. You can
change the eld names to any names allowed by the database format. For example, many databases
allow characters in eld names that aren't allowed in variable names, including spaces. Therefore, a
variable name like CallWaiting could be changed to the eld name Call Waiting.
Type. The export wizard makes initial data type assignments based on the standard ODBC data types or
data types allowed by the selected database format that most closely matches the dened IBM SPSS
Statistics data format--but databases can make type distinctions that have no direct equivalent in IBM
SPSS Statistics, and vice versa. For example, most numeric values in IBM SPSS Statistics are stored as
Chapter 3. Data
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double-precision floating-point values, whereas database numeric data types include float (double),
integer, real, and so on. In addition, many databases don't have equivalents to IBM SPSS Statistics time
formats. You can change the data type to any type available in the drop-down list.
As a general rule, the basic data type (string or numeric) for the variable should match the basic data type
of the database eld. If there is a data type mismatch that cannot be resolved by the database, an error
results and no data are exported to the database. For example, if you export a string variable to a
database eld with a numeric data type, an error will result if any values of the string variable contain
non-numeric characters.
Width. You can change the dened width for string (char, varchar) eld types. Numeric eld widths are
dened by the data type.
By default, IBM SPSS Statistics variable formats are mapped to database eld types based on the
following general scheme. Actual database eld types may vary, depending on the database.
Table 5. Format conversion for databases
IBM SPSS Statistics Variable Format Database Field Type
Numeric Float or Double
Comma Float or Double
Dot Float or Double
Scientic Notation Float or Double
Date Date or Datetime or Timestamp
Datetime Datetime or Timestamp
Time, DTime Float or Double (number of seconds)
Wkday Integer (1–7)
Month Integer (1–12)
Dollar Float or Double
Custom Currency Float or Double
String Char or Varchar
User-Missing Values
There are two options for the treatment of user-missing values when data from variables are exported to
database elds:
• Export as valid values. User-missing values are treated as regular, valid, nonmissing values.
• Export numeric user-missing as nulls and export string user-missing values as blank spaces.
Numeric user-missing values are treated the same as system-missing values. String user-missing
values are converted to blank spaces (strings cannot be system-missing).
Selecting a Data Source
In the rst panel of the Export to Database Wizard, you select the data source to which you want to export
data.
You can export data to any database source for which you have the appropriate ODBC driver. (Note:
Exporting data to OLE DB data sources is not supported.)
If you do not have any ODBC data sources congured, or if you want to add a new data source, click Add
ODBC Data Source.
• On Linux operating systems, this button is not available. ODBC data sources are specied in odbc.ini,
and the ODBCINI environment variables must be set to the location of that le. For more information,
see the documentation for your database drivers.
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IBM SPSS Statistics 27 Core System User's Guide
• In distributed analysis mode (available with IBM SPSS Statistics Server), this button is not available. To
add data sources in distributed analysis mode, see your system administrator.
An ODBC data source consists of two essential pieces of information: the driver that will be used to
access the data and the location of the database you want to access. To specify data sources, you must
have the appropriate drivers installed. Drivers for a variety of database formats are included with the
installation media.
Some data sources may require a login ID and password before you can proceed to the next step.
Choosing How to Export the Data
After you select the data source, you indicate the manner in which you want to export the data.
The following choices are available for exporting data to a database:
• Replace values in existing elds. Replaces values of selected elds in an existing table with values
from the selected variables in the active dataset. See the topic “Replacing Values in Existing Fields” on
page 32 for more information.
• Add new elds to an existing table. Creates new elds in an existing table that contain the values of
selected variables in the active dataset. See the topic “Adding New Fields” on page 32 for more
information. This option is not available for Excel les.
• Append new records to an existing table. Adds new records (rows) to an existing table containing the
values from cases in the active dataset. See the topic “Appending New Records (Cases)” on page 33
for more information.
• Drop an existing table and create a new table of the same name. Deletes the specied table and
creates a new table of the same name that contains selected variables from the active dataset. All
information from the original table, including denitions of eld properties (for example, primary keys,
data types) is lost. See the topic “Creating a New Table or Replacing a Table” on page 33 for more
information.
• Create a new table. Creates a new table in the database containing data from selected variables in the
active dataset. The name can be any value that is allowed as a table name by the data source. The name
cannot duplicate the name of an existing table or view in the database. See the topic “Creating a New
Table or Replacing a Table” on page 33 for more information.
Selecting a Table
When modifying or replacing a table in the database, you need to select the table to modify or replace.
This panel in the Export to Database Wizard displays a list of tables and views in the selected database.
By default, the list displays only standard database tables. You can control the type of items that are
displayed in the list:
• Tables. Standard database tables.
• Views. Views are virtual or dynamic "tables" dened by queries. These can include joins of multiple
tables and/or elds derived from calculations based on the values of other elds. You can append
records or replace values of existing elds in views, but the elds that you can modify may be restricted,
depending on how the view is structured. For example, you cannot modify a derived eld, add elds to a
view, or replace a view.
• Synonyms. A synonym is an alias for a table or view, typically dened in a query.
• System tables. System tables dene database properties. In some cases, standard database tables
may be classied as system tables and will be displayed only if you select this option. Access to real
system tables is often restricted to database administrators.
Selecting Cases to Export
Case selection in the Export to Database Wizard is limited either to all cases or to cases selected using a
previously dened lter condition. If no case ltering is in effect, this panel will not appear, and all cases
in the active dataset will be exported.
For information on dening a lter condition for case selection, see “Select cases” on page 103.
Chapter 3. Data
les 31
Matching Cases to Records
When adding elds (columns) to an existing table or replacing the values of existing elds, you need to
make sure that each case (row) in the active dataset is correctly matched to the corresponding record in
the database.
• In the database, the eld or set of elds that uniquely identies each record is often designated as the
primary key.
• You need to identify which variable(s) correspond to the primary key eld(s) or other elds that uniquely
identify each record.
• The elds don't have to be the primary key in the database, but the eld value or combination of eld
values must be unique for each case.
To match variables with elds in the database that uniquely identify each record:
1. Drag and drop the variable(s) onto the corresponding database elds.
or
2. Select a variable from the list of variables, select the corresponding eld in the database table, and
click Connect.
To delete a connection line:
3. Select the connection line and press the Delete key.
Note: The variable names and database eld names may not be identical (since database eld names may
contain characters not allowed in IBM SPSS Statistics variable names), but if the active dataset was
created from the database table you are modifying, either the variable names or the variable labels will
usually be at least similar to the database eld names.
Replacing Values in Existing Fields
To replace values of existing elds in a database:
1. In the Choose how to export the data panel of the Export to Database Wizard, select Replace values
in existing elds.
2. In the Select a table or view panel, select the database table.
3. In the Match cases to records panel, match the variables that uniquely identify each case to the
corresponding database eld names.
4. For each eld for which you want to replace values, drag and drop the variable that contains the new
values into the Source of values column, next to the corresponding database eld name.
• As a general rule, the basic data type (string or numeric) for the variable should match the basic data
type of the database eld. If there is a data type mismatch that cannot be resolved by the database, an
error results and no data is exported to the database. For example, if you export a string variable to a
database eld with a numeric data type (for example, double, real, integer), an error will result if any
values of the string variable contain non-numeric characters. The letter a in the icon next to a variable
denotes a string variable.
• You cannot modify the eld name, type, or width. The original database eld attributes are preserved;
only the values are replaced.
Adding New Fields
To add new elds to an existing database table:
1. In the Choose how to export the data panel of the Export to Database Wizard, select Add new elds
to an existing table.
2. In the Select a table or view panel, select the database table.
3. In the Match cases to records panel, match the variables that uniquely identify each case to the
corresponding database eld names.
4. Drag and drop the variables that you want to add as new elds to the Source of values column.
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IBM SPSS Statistics 27 Core System User's Guide
For information on eld names and data types, see the section on creating database elds from IBM SPSS
Statistics variables in “Exporting to a Database” on page 29.
Value Labels. If a variable has dened variable labels, export value label text instead of values. For values
that do not have a dened value label, the data value is exported as a text string. This option is not
available for date format variables or variables that do not have any dened value labels.
Show existing elds. Select this option to display a list of existing elds. You cannot use this panel in the
Export to Database Wizard to replace existing elds, but it may be helpful to know what elds are already
present in the table. If you want to replace the values of existing elds, see “Replacing Values in Existing
Fields” on page 32.
Appending New Records (Cases)
To append new records (cases) to a database table:
1. In the Choose how to export the data panel of the Export to Database Wizard, select Append new
records to an existing table.
2. In the Select a table or view panel, select the database table.
3. Match variables in the active dataset to table elds by dragging and dropping variables to the Source
of values column.
The Export to Database Wizard will automatically select all variables that match existing elds, based on
information about the original database table stored in the active dataset (if available) and/or variable
names that are the same as eld names. This initial automatic matching is intended only as a guide and
does not prevent you from changing the way in which variables are matched with database elds.
When adding new records to an existing table, the following basic rules/limitations apply:
• All cases (or all selected cases) in the active dataset are added to the table. If any of these cases
duplicate existing records in the database, an error may result if a duplicate key value is encountered.
For information on exporting only selected cases, see “Selecting Cases to Export” on page 31
.
• You can use the values of new variables created in the session as the values for existing elds, but you
cannot add new elds or change the names of existing elds. To add new elds to a database table, see
“Adding New Fields” on page 32.
• Any excluded database elds or elds not matched to a variable will have no values for the added
records in the database table. (If the Source of values cell is empty, there is no variable matched to the
eld.)
Creating a New Table or Replacing a Table
To create a new database table or replace an existing database table:
1. In the Choose how to export the data panel of the export wizard, select Drop an existing table and
create a new table of the same name or select Create a new table and enter a name for the new
table. If the table name contains any characters other than letters, numbers, or an underscore, the
name must be enclosed in double quotes.
2. If you are replacing an existing table, in the Select a table or view panel, select the database table.
3. Drag and drop variables into the Variables to save column.
4. Optionally, you can designate variables/elds that dene the primary key, change eld names, and
change the data type.
Primary key. To designate variables as the primary key in the database table, select the box in the
column identied with the key icon.
• All values of the primary key must be unique or an error will result.
• If you select a single variable as the primary key, every record (case) must have a unique value for that
variable.
• If you select multiple variables as the primary key, this denes a composite primary key, and the
combination of values for the selected variables must be unique for each case.
Chapter 3. Data
les 33
For information on eld names and data types, see the section on creating database elds from IBM SPSS
Statistics variables in “Exporting to a Database” on page 29.
Value Labels. If a variable has dened variable labels, export value label text instead of values. For values
that do not have a dened value label, the data value is exported as a text string. This option is not
available for date format variables or variables that do not have any dened value labels.
Completing the Database Export Wizard
The last step of the Export to Database Wizard provides a summary of the export specications.
Summary
• Dataset. The IBM SPSS Statistics session name for the dataset that is used to export data. This
information is primarily useful if you have multiple open data sources. A data source opened with
command syntax has a dataset name only if one is explicitly assigned.
• Table. The name of the table to be modied or created.
• Cases to Export. Either all cases are exported or cases that are selected by a previously dened lter
condition are exported.
• Action. Indicates how the database is modied (for example, create a new table, add elds or records
to an existing table).
• User-Missing Values. User-missing values can be exported as valid values or treated the same as
system-missing for numeric variables and converted to blank spaces for string variables. This setting is
controlled in the panel in which you select the variables to export.
Bulk Loading
Bulk load. Submits data to the database in batches instead of one record at a time. This action can make
the operation much faster, particularly for large data les.
• Batch size. Species the number records to submit in each batch.
• Batch commit. Commits records to the database in the specied batch size.
• ODBC binding. Uses the ODBC binding method to commit records in the specied batch size. This
option is only available if the database supports ODBC binding. This option is not available on macOS.
– Row-wise binding. Row-wise binding typically improves speed compared to the use of
parameterized inserts that insert data on a record-by-record basis.
– Column-wise binding. Column-wise binding improves performance by binding each database
column to an array of n values.
What would you like to do?
• Export the data. Exports the data to the database.
• Paste the syntax. Pastes the command syntax for exporting the data to a syntax window. You can
modify and save the pasted command syntax.
Exporting to Data Collection
The Export to Data Collection dialog box creates IBM SPSS Statistics data les and Data Collection
metadata les that you can use to read the data into Data Collection applications. This is particularly
useful when "roundtripping" data between IBM SPSS Statistics and Data Collection applications.
Note: There may be instances where the data cannot be re-loaded to the Data Collection database in the
correct format due to the complexity in the structure.
To export data for use in Data Collection applications:
1. From the menus in the Data Editor window that contains the data you want to export, choose:
File > Export > Data Collection
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IBM SPSS Statistics 27 Core System User's Guide
2. Click Data File to specify the name and location of the IBM SPSS Statistics data le.
3. Click Metadata File to specify the name and location of the Data Collection metadata le.
For new variables and datasets not created from Data Collection data sources, IBM SPSS Statistics
variable attributes are mapped to Data Collection metadata attributes.
If the active dataset was created from a Data Collection data source:
• The new metadata le is created by merging the original metadata attributes with metadata attributes
for any new variables, plus any changes to original variables that might affect their metadata attributes
(for example, addition of, or changes to, value labels).
• For original variables read from the Data Collection data source, any metadata attributes not recognized
by IBM SPSS Statistics are preserved in their original state. For example, IBM SPSS Statistics converts
grid variables to regular IBM SPSS Statistics variables, but the metadata that denes these grid
variables is preserved when you save the new metadata le.
• If any Data Collection variables were automatically renamed to conform to IBM SPSS Statistics variable
naming rules, the metadata le maps the converted names back to the original Data Collection variable
names.
The presence or absence of value labels can affect the metadata attributes of variables and consequently
the way those variables are read by Data Collection applications. If value labels have been dened for any
nonmissing values of a variable, they should be dened for all nonmissing values of that variable;
otherwise, the unlabeled values will be dropped when the data le is read by Data Collection.
This feature is only available with IBM SPSS Statistics installed on Microsoft Windows operating systems,
and is only available in local analysis mode. This feature is not available in distributed analysis mode
using IBM SPSS Statistics Server.
To write Data Collection metadata les, you must have the following items installed:
• .NET framework. To obtain the most recent version of the .NET framework, go to http://
www.microsoft.com/net.
• Data Collection Survey Reporter Developer Kit.
Exporting to Cognos TM1
If you have access to an IBM Cognos TM1 database, you can export data from IBM SPSS Statistics to
TM1. This feature is particularly useful when you import data from TM1, transform or score the data in
SPSS Statistics, and then want to export the results back to TM1.
Important: To enable the exchange of data between SPSS Statistics and TM1, you must copy the
following three processes from SPSS Statistics to the TM1 server: ExportToSPSS.pro,
ImportFromSPSS.pro, and SPSSCreateNewMeasures.pro. To add these processes to the TM1
server, you must copy them to the data directory of the TM1 server and restart the TM1 server. These les
are available from the common/scripts/TM1 directory under the SPSS Statistics installation directory.
To export data to TM1:
1. From the menus, choose:
File > Export > Cognos TM1
2. Connect to the TM1 Performance Management system.
3. Log in to the TM1 server.
4. Select the TM1 cube where you want to export the data.
5. Specify the mappings from the elds in the active dataset to the dimensions and measures in the TM1
cube.
PM System
The URL of the Performance Management system that contains the TM1 server to which you want to
connect. The Performance Management system is dened as a single URL for all TM1 servers. From
Chapter 3. Data
les 35
this URL, all TM1 servers that are installed and running on your environment can be discovered and
accessed. Enter the URL and click Connect.
TM1 Server
When the connection to the Performance Management system is established, select the server that
contains the cube to which you want to export the data and click Login. If you did not previously
connect to this server, you are prompted to enter your user name and password. If the server uses
authentication mode 5 (IBM Cognos security), then select the namespace that identies the security
authentication provider from the available list.
Select a TM1 cube to export
Lists the names of the cubes within the TM1 server into which you can export data. Select a cube and
click the right arrow to move it into the Export to cube eld.
Note:
• System-missing and user-missing values of elds that are mapped to elements in the measure
dimension of the TM1 cube are ignored on export. The associated cells in the TM1 cube are unchanged.
• Fields with a value of zero, that are mapped to elements in the measure dimension, are exported as a
valid value.
Mapping elds to TM1 dimensions
Use the Mapping tab in the Export to TM1 dialog box to map SPSS Statistics elds to the associated IBM
Cognos TM1 dimensions and measures. You can map to existing elements in the measure dimension or
you can create new elements in the measure dimension of the TM1 cube.
• For each regular dimension in the specied TM1 cube, you must either map a eld in the active dataset
to the dimension or specify a slice for the dimension. A slice species a single leaf element of a
dimension so that all exported cases are associated with the specied leaf element.
• For a eld that is mapped to a regular dimension, cases with eld values that do not match a leaf
element in the specied dimension are not exported. In that regard, you can export only to leaf
elements.
• Only string elds in the active dataset can be mapped to regular dimensions. Only numeric elds in the
active dataset can be mapped to elements in the measure dimension of the cube.
• Values that are exported to an existing element in the measure dimension overwrite the associated
cells in the TM1 cube.
To map an SPSS Statistics eld to a regular TM1 dimension or to an existing element in the measure
dimension:
1. Select the SPSS Statistics eld from the Fields list.
2. Select the associated TM1 dimension or measure from the TM1 Dimensions list.
3. Click Map.
To map an SPSS Statistics eld to a new element in the measure dimension:
1. Select the SPSS Statistics eld from the Fields list.
2. Select the item for the measure dimension from the TM1 Dimensions list.
3. Click Create New, enter the name of the measure element in the TM1 Measure Name dialog and click
OK.
To specify a slice for a regular dimension:
1. Select the dimension from the TM1 Dimensions list.
2. Click Slice on.
3. In the Select Leaf Member dialog, select the element that species the slice and then click OK. You
can search for a specic element by entering a search string in the Find text box and clicking Find
Next. A match is found if any part of an element matches the search string.
• Spaces included in the search string are included in the search.
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IBM SPSS Statistics 27 Core System User's Guide
• Searches are not case-sensitive.
• The asterisk (*) is treated as any other character and does not indicate a wildcard search.
You can remove a mapping denition by selecting the mapped item from the TM1 Dimensions list and
clicking Unmap. You can delete the specication of a new measure by selecting the measure from the
TM1 Dimensions list and clicking Delete.
Comparing datasets
Compare Datasets compares the active dataset to another dataset in the current session or an external
le in IBM SPSS Statistics format.
To compare datasets
1. Open a data le and make sure it is the active dataset. (You can make a dataset the active dataset by
clicking on the Data Editor window for that dataset.)
2. From the menus choose:
Data > Compare Datasets
3. Select the open dataset or IBM SPSS Statistics data le that you want to compare to the active
dataset.
4. Select one or more elds (variables) that you want to compare.
Optionally, you can:
• Match cases (records) based on one or more case ID values.
• Compare data dictionary properties (eld and value labels, user-missing values, measurement level,
etc).
• Create a flag eld in the active dataset that identies mismatched cases.
• Create new datasets that contain only matched cases or only mismatched cases.
Compare Datasets: Compare tab
The Matched elds list displays a list of elds that have the same name and same basic type (string or
numeric) in both datasets.
1. Select one or more elds (variables) to compare. The comparison of the two datasets is based on the
selected elds only.
2. To see a list of elds that either do no have matching names or are not the same basic type in both
datasets, click Unmatched elds. Unmatched elds are excluded from the comparison of the two
datasets.
3. Optionally, select one or more case (record) ID elds that identify each case.
• If you specify multiple case ID elds, each unique combination of values identies a case.
• Both les must be sorted in ascending order of the case ID elds. If the datasets are not already sorted,
select (check) Sort Cases to sort both datasets in case ID order.
• If you do not include any case ID elds, cases are compared in le order. That is, the rst case (record)
in the active dataset is compared to the rst case in the other dataset, and so on.
Compare Datasets: Unmatched Fields
The Unmatched Fields dialog displays a list of elds (variables) that are considered unmatched in the two
datasets. An unmatched eld is a eld that either is missing from one of the datasets or is not the same
basic type (string or numeric) in both les. Unmatched elds are excluded from the comparison of the two
datasets.
Chapter 3. Data
les 37
Compare Datasets: Attributes tab
By default, only data values are compared, and eld attributes (data dictionary properties) such as value
labels, user-missing values, and measurement level, are not compared. To compare eld attributes:
1. In the Compare Datasets dialog, click the Attributes tab.
2. Click Compare the Data Dictionaries.
3. Select the attributes you want to compare.
• Width. For numeric elds, the maximum number of characters displayed (digits plus formatting
characters, such as currency symbols, grouping symbols, and decimal indicator). For string elds, the
maximum number of bytes allowed.
• Label. Descriptive eld label.
• Value Label. Descriptive value labels.
• Missing. Dened user-missing values.
• Columns. Column width in Data view of the Data Editor.
• Align. Alignment in Data view of the Data Editor.
• Measure. Measurement level.
• Role. Field role.
• Attributes. User-dened custom eld attributes.
Comparing datasets: Output tab
By default, Compare Datasets creates a new eld in the active dataset that identies mismatches and
produces a table that provides details for the rst 100 mismatches. You can use the Output tab to change
the output options.
Flag mismatches in a new eld. A new eld that identies mismatches is created in the active dataset.
• The value of the new eld is 1 if there are differences and 0 if all the values are the same. If there are
cases (records) in the active dataset that are not present in the other dataset, the value is -1.
• The default name of the new eld is CasesCompare. You can specify a different eld name. The name
must conform to eld (variable) naming rules. See the topic “Variable names” on page 46
for more
information.
Copy matched cases to a new dataset. Creates a new dataset that contains only cases (records) from
the active dataset that have matching values in the other dataset. The dataset name must conform to eld
(variable) naming rules. If the dataset already exists, it will be overwritten.
Copy mismatched cases to a new dataset. Creates a new dataset that contains only cases from the
active dataset that have different values in the other dataset. The dataset name must conform to eld
(variable) naming rules. If the dataset already exists, it will be overwritten.
Limit the case-by-case table. For cases (records) in the active dataset that also exist in the other dataset
and also have the same basic type (numeric or string) in both datasets, the case-by-case table provides
details on the mismatched values for each case. By default, the table is limited to the rst 100
mismatches. You can specify a different value or deselect (clear) this item to include all mismatches.
Protecting original data
To prevent the accidental modication or deletion of your original data, you can mark the le as read-only.
1. From the Data Editor menus choose:
File > Mark File Read Only
If you make subsequent modications to the data and then try to save the data le, you can save the data
only with a different lename, so the original data are not affected.
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IBM SPSS Statistics 27 Core System User's Guide
You can change the le permissions back to read-write by choosing Mark File Read Write from the File
menu.
Virtual Active File
The virtual active le enables you to work with large data les without requiring equally large (or larger)
amounts of temporary disk space. For most analysis and charting procedures, the original data source is
reread each time you run a different procedure. Procedures that modify the data require a certain amount
of temporary disk space to keep track of the changes, and some actions always require enough disk space
for at least one entire copy of the data le.
Actions that don't require any temporary disk space include:
• Reading IBM SPSS Statistics data les
• Merging two or more IBM SPSS Statistics data les
• Reading database tables with the Database Wizard
• Merging IBM SPSS Statistics data les with database tables
• Running procedures that read data (for example, Frequencies, Crosstabs, Explore)
Actions that create one or more columns of data in temporary disk space include:
• Computing new variables
• Recoding existing variables
• Running procedures that create or modify variables (for example, saving predicted values in Linear
Regression)
Actions that create an entire copy of the data le in temporary disk space include:
• Reading Excel les
• Running procedures that sort data (for example, Sort Cases, Split File)
• Reading data with GET TRANSLATE or DATA LIST commands
• Using the Cache Data facility or the CACHE command
• Launching other applications from IBM SPSS Statistics that read the data le (for example, AnswerTree,
DecisionTime)
Note: The GET DATA command provides functionality comparable to DATA LIST without creating an
entire copy of the data le in temporary disk space. The SPLIT FILE command in command syntax does
not sort the data le and therefore does not create a copy of the data le. This command, however,
requires sorted data for proper operation, and the dialog box interface for this procedure will
automatically sort the data le, resulting in a complete copy of the data le. (Command syntax is not
available with the Student Version.)
Actions that create an entire copy of the data le by default:
• Reading databases with the Database Wizard
• Reading text les with the Text Wizard
The Text Wizard provides an optional setting to automatically cache the data. By default, this option is
selected. You can turn it off by deselecting Cache data locally. For the Database Wizard, you can paste
the generated command syntax and delete the CACHE command.
Creating a Data Cache
Although the virtual active le can vastly reduce the amount of temporary disk space required, the
absence of a temporary copy of the "active" le means that the original data source has to be reread for
each procedure. For large data les read from an external source, creating a temporary copy of the data
may improve performance. For example, for data tables read from a database source, the SQL query that
reads the information from the database must be reexecuted for any command or procedure that needs
to read the data. Since virtually all statistical analysis procedures and charting procedures need to read
Chapter 3. Data
les 39
the data, the SQL query is reexecuted for each procedure you run, which can result in a signicant
increase in processing time if you run a large number of procedures.
If you have sufcient disk space on the computer performing the analysis (either your local computer or a
remote server), you can eliminate multiple SQL queries and improve processing time by creating a data
cache of the active le. The data cache is a temporary copy of the complete data.
Note: By default, the Database Wizard automatically creates a data cache, but if you use the GET DATA
command in command syntax to read a database, a data cache is not automatically created. (Command
syntax is not available with the Student Version.)
To Create a Data Cache
1. From the menus choose:
File > Cache Data...
2. Click OK or Cache Now.
OK creates a data cache the next time the program reads the data (for example, the next time you run a
statistical procedure), which is usually what you want because it doesn't require an extra data pass.
Cache Now creates a data cache immediately, which shouldn't be necessary under most circumstances.
Cache Now is useful primarily for two reasons:
• A data source is "locked" and can't be updated by anyone until you end your session, open a different
data source, or cache the data.
• For large data sources, scrolling through the contents of the Data View tab in the Data Editor will be
much faster if you cache the data.
To Cache Data Automatically
You can use the SET command to automatically create a data cache after a specied number of changes
in the active data le. By default, the active data le is automatically cached after 20 changes in the active
data le.
1. From the menus choose:
File > New > Syntax
2. In the syntax window, type SET CACHE n (where n represents the number of changes in the active
data le before the data le is cached).
3. From the menus in the syntax window choose:
Run > All
Note: The cache setting is not persistent across sessions. Each time you start a new session, the value is
reset to the default of 20.
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IBM SPSS Statistics 27 Core System User's Guide
Chapter 4. Distributed Analysis Mode
Distributed analysis mode allows you to use a computer other than your local (or desktop) computer for
memory-intensive work. Because remote servers that are used for distributed analysis are typically more
powerful and faster than your local computer, distributed analysis mode can signicantly reduce
computer processing time. Distributed analysis with a remote server can be useful if your work involves:
• Large data les, particularly data read from database sources.
• Memory-intensive tasks. Any task that takes a long time in local analysis mode may be a good candidate
for distributed analysis.
Distributed analysis affects only data-related tasks, such as reading data, transforming data, computing
new variables, and calculating statistics. Distributed analysis has no effect on tasks related to editing
output, such as manipulating pivot tables or modifying charts.
Note: Distributed analysis is available only if you have both a local version and access to a licensed server
version of the software that is installed on a remote server.
Server Login
The Server Login dialog box allows you to select the computer that processes commands and runs
procedures. You can select your local computer or a remote server.
You can add, modify, or delete remote servers in the list. Remote servers usually require a user ID and
password, and a domain name may also be necessary. If you are licensed to use the Statistics Adapter
and your site is running IBM SPSS Collaboration and Deployment Services you may be able to connect to
a remote server using single sign-on. Single sign-on allows users to connect to a remote server without
explicitly providing a user ID and password. The necessary authentication is performed with the user's
existing credentials on the current machine--obtained, for example, from Windows Active Directory.
Contact your system administrator for information about available servers, a user ID and password,
domain names, and other connection information, including whether single sign-on is supported at your
site.
You can select a default server and save the user ID, domain name, and password that are associated
with any server. You are automatically connected to the default server when you start a new session.
Important: You can connect to a server that is not at the same release level as the client. The server can
be one or two releases newer or older compared to the client. However, it is not recommended to
maintain this conguration for an extended time. If the server is newer than the client, the server may
create output that cannot be read by the client. If the client is newer than the server, syntax submitted by
the client may not be recognized by the server. Therefore, you should talk to your administrator about
connecting to a server that is at the same release level as the client.
If you are licensed to use the Statistics Adapter and your site is running IBM SPSS Collaboration and
Deployment Services 3.5 or later, you can click Search... to view a list of servers that are available on your
network. If you are not logged on to a IBM SPSS Collaboration and Deployment Services Repository, you
will be prompted to enter connection information before you can view the list of servers.
Adding and Editing Server Login Settings
Use the Server Login Settings dialog box to add or edit connection information for remote servers for use
in distributed analysis mode.
Contact your system administrator for a list of available servers, port numbers for the servers, and
additional connection information. Do not use the Secure Socket Layer unless instructed to do so by your
administrator.
Server Name. A server "name" can be an alphanumeric name that is assigned to a computer (for
example, NetworkServer) or a unique IP address that is assigned to a computer (for example,
202.123.456.78).
Port Number. The port number is the port that the server software uses for communications.
Description. You can enter an optional description to display in the servers list.
Connect with Secure Socket Layer. Secure Socket Layer (SSL) encrypts requests for distributed analysis
when they are sent to the remote server. Before you use SSL, check with your administrator. For this
option to be enabled, SSL must be congured on your desktop computer and the server.
To Select, Switch, or Add Servers
1. From the menus choose:
File > Switch Server...
To select a default server:
2. In the server list, select the box next to the server that you want to use.
3. If the server is congured for single sign-on then simply ensure that Set Credentials is unchecked.
Otherwise, select Set Credentials and enter the user ID, domain name, and password that were
provided by your administrator.
Note: You are automatically connected to the default server when you start a new session.
To switch to another server:
4. Select the server from the list.
5. If the server is congured for single sign-on then simply ensure that Set Credentials is unchecked.
Otherwise, select Set Credentials and enter the user ID, domain name, and password (if necessary).
Note: When you switch servers during a session, all open windows are closed. You will be prompted
to save changes before the windows are closed.
To add a server:
6. Get the server connection information from your administrator.
7. Click Add to open the Server Login Settings dialog box.
8. Enter the connection information and optional settings, and then click OK.
To edit a server:
9. Get the revised connection information from your administrator.
10. Click Edit to open the Server Login Settings dialog box.
11. Enter the changes and click OK.
To search for available servers:
Note: The ability to search for available servers is available only if you are licensed to use the
Statistics Adapter and your site is running IBM SPSS Collaboration and Deployment Services 3.5 or
later.
12. Click Search... to open the Search for Servers dialog box. If you are not logged on to a IBM SPSS
Collaboration and Deployment Services Repository, you will be prompted for connection information.
13. Select one or more available servers and click OK. The servers will now appear in the Server Login
dialog box.
14. To connect to one of the servers, follow the instructions "To switch to another server."
Searching for Available Servers
Use the Search for Servers dialog box to select one or more servers that are available on your network.
This dialog box appears when you click Search... on the Server Login dialog box.
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IBM SPSS Statistics 27 Core System User's Guide
Select one or more servers and click OK to add them to the Server Login dialog box. Although you can
manually add servers in the Server Login dialog box, searching for available servers lets you connect to
servers without requiring that you know the correct server name and port number. This information is
automatically provided. However, you still need the correct logon information, such as user name,
domain, and password.
Opening Data Files from a Remote Server
In distributed analysis mode, the Open Remote File dialog box replaces the standard Open File dialog
box.
• The contents of the list of available les, folders, and drives depends on what is available on or from the
remote server. The current server name is indicated at the top of the dialog box.
• In distributed analysis mode, you will not have access to les on your local computer unless you specify
the drive as a shared device or specify the folders containing your data les as shared folders. Consult
the documentation for your operating system for information on how to "share" folders on your local
computer with the server network.
• If the server is running a different operating system (for example, you are running Windows and the
server is running UNIX), you probably won't have access to local data les in distributed analysis mode
even if they are in shared folders.
File Access in Local and Distributed Analysis Mode
The view of data folders (directories) and drives for both your local computer and the network is based on
the computer that you are currently using to process commands and run procedures—which is not
necessarily the computer in front of you.
Local analysis mode. When you use your local computer as your "server," the view of data les, folders,
and drives in the le access dialog box (for opening data les) is similar to what you see in other
applications or in Windows Explorer. You can see all of the data les and folders on your computer and
any les and folders on mounted network drives.
Distributed analysis mode. When you use another computer as a "remote server" to run commands and
procedures, the view of data les, folders, and drives represents the view from the remote server
computer. Although you may see familiar folder names (such as Program Files) and drives (such as C),
these items are not the folders and drives on your computer; they are the folders and drives on the
remote server.
In distributed analysis mode, you will not have access to data les on your local computer unless you
specify the drive as a shared device or specify the folders containing your data les as shared folders. If
the server is running a different operating system (for example, you are running Windows and the server is
running UNIX), you probably won't have access to local data les in distributed analysis mode even if they
are in shared folders.
Distributed analysis mode is not the same as accessing data les that reside on another computer on your
network. You can access data les on other network devices in local analysis mode or in distributed
analysis mode. In local mode, you access other devices from your local computer. In distributed mode,
you access other network devices from the remote server.
If you're not sure if you're using local analysis mode or distributed analysis mode, look at the title bar in
the dialog box for accessing data les. If the title of the dialog box contains the word Remote (as in Open
Remote File), or if the text Remote Server: [server name] appears at the top of the dialog box, you're
using distributed analysis mode.
Note: This situation affects only dialog boxes for accessing data les (for example, Open Data, Save Data,
Open Database, and Apply Data Dictionary). For all other le types (for example, Viewer les, syntax les,
and script les), the local view is always used.
Chapter 4. Distributed Analysis Mode
43
Availability of Procedures in Distributed Analysis Mode
In distributed analysis mode, procedures are available for use only if they are installed on both your local
version and the version on the remote server.
If you have optional components installed locally that are not available on the remote server and you
switch from your local computer to a remote server, the affected procedures will be removed from the
menus and the corresponding command syntax will result in errors. Switching back to local mode will
restore all affected procedures.
Absolute versus Relative Path Specications
In distributed analysis mode, relative path specications for data les and command syntax les are
relative to the current server, not relative to your local computer. A relative path specication such as /
mydocs/mydata.sav does not point to a directory and le on your local drive; it points to a directory and
le on the remote server's hard drive.
Windows UNC Path Specications
If you are using a Windows server version, you can use universal naming convention (UNC) specications
when accessing data and syntax les with command syntax. The general form of a UNC specication is:
\\servername\sharename\path\filename
• Servername is the name of the computer that contains the data le.
• Sharename is the folder (directory) on that computer that is designated as a shared folder.
• Path is any additional folder (subdirectory) path below the shared folder.
• Filename is the name of the data le.
An example is as follows:
GET FILE='\\hqdev001\public\july\sales.sav'.
If the computer does not have a name assigned to it, you can use its IP address, as in:
GET FILE='\\204.125.125.53\public\july\sales.sav'.
Even with UNC path specications, you can access data and syntax les only from devices and folders
that are designated as shared. When you use distributed analysis mode, this situation includes data and
syntax les on your local computer.
UNIX Absolute Path Specications
For UNIX server versions, there is no equivalent to the UNC path, and all directory paths must be absolute
paths that start at the root of the server; relative paths are not allowed. For example, if the data le is
located in /bin/data and the current directory is also /bin/data, GET FILE='sales.sav' is not valid;
you must specify the entire path, as in:
GET FILE='/bin/sales.sav'.
INSERT FILE='/bin/salesjob.sps'.
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IBM SPSS Statistics 27 Core System User's Guide
Chapter 5. Data Editor
The Data Editor provides a convenient, spreadsheet-like method for creating and editing data les. The
Data Editor window opens automatically when you start a session.
The Data Editor provides two views of your data:
• Data View. This view displays the actual data values or dened value labels.
• Variable View. This view displays variable denition information, including dened variable and value
labels, data type (for example, string, date, or numeric), measurement level (nominal, ordinal, or scale),
and user-dened missing values.
In both views, you can add, change, and delete information that is contained in the data le.
Data View
Many of the features of Data View are similar to the features that are found in spreadsheet applications.
There are, however, several important distinctions:
• Rows are cases. Each row represents a case or an observation. For example, each individual respondent
to a questionnaire is a case.
• Columns are variables. Each column represents a variable or characteristic that is being measured. For
example, each item on a questionnaire is a variable.
• Cells contain values. Each cell contains a single value of a variable for a case. The cell is where the case
and the variable intersect. Cells contain only data values. Unlike spreadsheet programs, cells in the
Data Editor cannot contain formulas.
• The data le is rectangular. The dimensions of the data le are determined by the number of cases and
variables. You can enter data in any cell. If you enter data in a cell outside the boundaries of the dened
data le, the data rectangle is extended to include any rows and/or columns between that cell and the
le boundaries. There are no "empty" cells within the boundaries of the data le. For numeric variables,
blank cells are converted to the system-missing value. For string variables, a blank is considered a valid
value.
Variable View
Variable View contains descriptions of the attributes of each variable in the data le. In Variable View:
• Rows are variables.
• Columns are variable attributes.
You can add or delete variables and modify attributes of variables, including the following attributes:
• Variable name
• Data type
• Number of digits or characters
• Number of decimal places
• Descriptive variable and value labels
• User-dened missing values
• Column width
• Measurement level
All of these attributes are saved when you save the data le.
In addition to dening variable properties in Variable View, there are two other methods for dening
variable properties:
• The Copy Data Properties Wizard provides the ability to use an external IBM SPSS Statistics data le or
another dataset that is available in the current session as a template for dening le and variable
properties in the active dataset. You can also use variables in the active dataset as templates for other
variables in the active dataset. Copy Data Properties is available on the Data menu in the Data Editor
window.
• Dene Variable Properties (also available on the Data menu in the Data Editor window) scans your data
and lists all unique data values for any selected variables, identies unlabeled values, and provides an
auto-label feature. This method is particularly useful for categorical variables that use numeric codes to
represent categories--for example, 0 = Male, 1 = Female.
To display or dene variable attributes
1. Make the Data Editor the active window.
2. Double-click a variable name at the top of the column in Data View, or click the Variable View tab.
3. To dene new variables, enter a variable name in any blank row.
4. Select the attribute(s) that you want to dene or modify.
Variable names
The following rules apply to variable names:
• Each variable name must be unique; duplication is not allowed.
• Variable names can be up to 64 bytes long, and the rst character must be a letter or one of the
characters @, #, or $. Subsequent characters can be any combination of letters, numbers,
nonpunctuation characters, and a period (.). In code page mode, sixty-four bytes typically means 64
characters in single-byte languages (for example, English, French, German, Spanish, Italian, Hebrew,
Russian, Greek, Arabic, and Thai) and 32 characters in double-byte languages (for example, Japanese,
Chinese, and Korean). Many string characters that only take one byte in code page mode take two or
more bytes in Unicode mode. For example, é is one byte in code page format but is two bytes in Unicode
format; so résumé is six bytes in a code page le and eight bytes in Unicode mode.
Note: Letters include any nonpunctuation characters used in writing ordinary words in the languages
supported in the platform's character set.
• Variable names cannot contain spaces.
• A # character in the rst position of a variable name denes a scratch variable. You can only create
scratch variables with command syntax. You cannot specify a # as the rst character of a variable in
dialogs that create new variables.
• A $ sign in the rst position indicates that the variable is a system variable. The $ sign is not allowed as
the initial character of a user-dened variable.
• The period, the underscore, and the characters $, #, and @ can be used within variable names. For
example, A._$@#1 is a valid variable name.
• Variable names cannot begin or end with a period. Names that begin with a period are invalid; names
the end with a period may be interpreted as a command terminator. You cannot create variables that
begin or end with a period in dialogs that create new variables.
• Variable names ending in underscores should be avoided, since such names may conflict with names of
variables automatically created by commands and procedures.
• Reserved keywords cannot be used as variable names. Reserved keywords are ALL, AND, BY, EQ, GE,
GT, LE, LT, NE, NOT, OR, TO, and WITH.
• Variable names can be dened with any mixture of uppercase and lowercase characters, and case is
preserved for display purposes.
• When long variable names need to wrap onto multiple lines in output, lines are broken at underscores,
periods, and points where content changes from lower case to upper case.
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IBM SPSS Statistics 27 Core System User's Guide
Variable measurement level
You can specify the level of measurement as scale (numeric data on an interval or ratio scale), ordinal, or
nominal. Nominal and ordinal data can be either string (alphanumeric) or numeric.
• Nominal. A variable can be treated as nominal when its values represent categories with no intrinsic
ranking (for example, the department of the company in which an employee works). Examples of
nominal variables include region, postal code, and religious afliation.
• Ordinal. A variable can be treated as ordinal when its values represent categories with some intrinsic
ranking (for example, levels of service satisfaction from highly dissatised to highly satised). Examples
of ordinal variables include attitude scores representing degree of satisfaction or condence and
preference rating scores.
• Scale. A variable can be treated as scale (continuous) when its values represent ordered categories with
a meaningful metric, so that distance comparisons between values are appropriate. Examples of scale
variables include age in years and income in thousands of dollars.
Note: For ordinal string variables, the alphabetic order of string values is assumed to reflect the true order
of the categories. For example, for a string variable with the values of low, medium, high, the order of the
categories is interpreted as high, low, medium, which is not the correct order. In general, it is more
reliable to use numeric codes to represent ordinal data.
For new numeric variables created with transformations, data from external sources, and IBM SPSS
Statistics data les created prior to version 8, default measurement level is determined by the conditions
in the following table. Conditions are evaluated in the order listed in the table . The measurement level for
the rst condition that matches the data is applied.
Table 6. Rules for determining measurement level
Condition Measurement Level
All values of a variable are missing Nominal
Format is dollar or custom-currency Continuous
Format is date or time (excluding Month and Wkday) Continuous
Variable contains at least one non-integer value Continuous
Variable contains at least one negative value Continuous
Variable contains no valid values less than 10,000 Continuous
Variable has N or more valid, unique values* Continuous
Variable has no valid values less than 10 Continuous
Variable has less than N valid, unique values* Nominal
* N is a user-specied cut-off value. The default is 24.
• You can change the cutoff value in the Options dialog box. See the topic “Data Options” on page 182 for
more information.
• The Dene Variable Properties dialog box, available from the Data menu, can help you assign the
correct measurement level. See the topic “Assigning the Measurement Level” on page 65 for more
information.
Variable type
Variable Type species the data type for each variable. By default, all new variables are assumed to be
numeric. You can use Variable Type to change the data type. The contents of the Variable Type dialog box
depend on the selected data type. For some data types, there are text boxes for width and number of
decimals; for other data types, you can simply select a format from a scrollable list of examples.
The available data types are as follows:
Chapter 5. Data Editor
47
Numeric. A variable whose values are numbers. Values are displayed in standard numeric format. The
Data Editor accepts numeric values in standard format or in scientic notation.
Comma. A numeric variable whose values are displayed with commas delimiting every three places and
displayed with the period as a decimal delimiter. The Data Editor accepts numeric values for comma
variables with or without commas or in scientic notation. Values cannot contain commas to the right of
the decimal indicator.
Dot. A numeric variable whose values are displayed with periods delimiting every three places and with
the comma as a decimal delimiter. The Data Editor accepts numeric values for dot variables with or
without periods or in scientic notation. Values cannot contain periods to the right of the decimal
indicator.
Scientic notation. A numeric variable whose values are displayed with an embedded E and a signed
power-of-10 exponent. The Data Editor accepts numeric values for such variables with or without an
exponent. The exponent can be preceded by E or D with an optional sign or by the sign alone--for
example, 123, 1.23E2, 1.23D2, 1.23E+2, and 1.23+2.
Date. A numeric variable whose values are displayed in one of several calendar-date or clock-time
formats. Select a format from the list. You can enter dates with slashes, hyphens, periods, commas, or
blank spaces as delimiters. The century range for two-digit year values is determined by your Options
settings (from the Edit menu, choose Options, and then click the Data tab).
Dollar. A numeric variable displayed with a leading dollar sign ($), commas delimiting every three places,
and a period as the decimal delimiter. You can enter data values with or without the leading dollar sign.
Custom currency. A numeric variable whose values are displayed in one of the custom currency formats
that you have dened on the Currency tab of the Options dialog box. Dened custom currency characters
cannot be used in data entry but are displayed in the Data Editor.
String. A variable whose values are not numeric and therefore are not used in calculations. The values
can contain any characters up to the dened length. Uppercase and lowercase letters are considered
distinct. This type is also known as an alphanumeric variable.
Restricted numeric. A variable whose values are restricted to non-negative integers. Values are
displayed with leading zeros padded to the maximum width of the variable. Values can be entered in
scientic notation.
To dene variable type
1. Click the button in the Type cell for the variable that you want to dene.
2. Select the data type in the Variable Type dialog box.
3. Click OK.
Input versus display formats
Depending on the format, the display of values in Data View may differ from the actual value as entered
and stored internally. Following are some general guidelines:
• For numeric, comma, and dot formats, you can enter values with any number of decimal positions (up to
16), and the entire value is stored internally. The Data View displays only the dened number of decimal
places and rounds values with more decimals. However, the complete value is used in all computations.
• For string variables, all values are right-padded to the maximum width. For a string variable with a
maximum width of three, a value of No is stored internally as 'No ' and is not equivalent to ' No'.
• For date formats, you can use slashes, dashes, spaces, commas, or periods as delimiters between day,
month, and year values, and you can enter numbers, three-letter abbreviations, or complete names for
month values. Dates of the general format dd-mmm-yy are displayed with dashes as delimiters and
three-letter abbreviations for the month. Dates of the general format dd/mm/yy and mm/dd/yy are
displayed with slashes for delimiters and numbers for the month. Internally, dates are stored as the
number of seconds from October 14, 1582. The century range for dates with two-digit years is
determined by your Options settings (from the Edit menu, choose Options, and then click the Data tab).
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IBM SPSS Statistics 27 Core System User's Guide
• For time formats, you can use colons, periods, or spaces as delimiters between hours, minutes, and
seconds. Times are displayed with colons as delimiters. Internally, times are stored as a number of
seconds that represents a time interval. For example, 10:00:00 is stored internally as 36000, which is
60 (seconds per minute) x 60 (minutes per hour) x 10 (hours).
Variable labels
You can assign descriptive variable labels up to 256 characters (128 characters in double-byte
languages). Variable labels can contain spaces and reserved characters that are not allowed in variable
names.
To specify variable labels
1. Make the Data Editor the active window.
2. Double-click a variable name at the top of the column in Data View, or click the Variable View tab.
3. In the Label cell for the variable, enter the descriptive variable label.
Value labels
You can assign descriptive value labels for each value of a variable. This process is particularly useful if
your data le uses numeric codes to represent non-numeric categories (for example, codes of 1 and 2 for
male and female).
To specify value labels
1. Click the button in the Values cell for the variable that you want to dene.
2. For each value, enter the value and a label.
3. Click Add to enter the value label.
4. Click OK.
Inserting line breaks in labels
Variable labels and value labels automatically wrap to multiple lines in pivot tables and charts if the cell or
area isn't wide enough to display the entire label on one line, and you can edit results to insert manual
line breaks if you want the label to wrap at a different point. You can also create variable labels and value
labels that will always wrap at specied points and be displayed on multiple lines.
1. For variable labels, select the Label cell for the variable in Variable View in the Data Editor.
2. For value labels, select the Values cell for the variable in Variable View in the Data Editor, click the
button in the cell, and select the label that you want to modify in the Value Labels dialog box.
3. At the place in the label where you want the label to wrap, type \n.
The \n is not displayed in pivot tables or charts; it is interpreted as a line break character.
Missing values
Missing Values denes specied data values as user-missing. For example, you might want to distinguish
between data that are missing because a respondent refused to answer and data that are missing
because the question didn't apply to that respondent. Data values that are specied as user-missing are
flagged for special treatment and are excluded from most calculations.
To dene missing values
1. Click the button in the Missing cell for the variable that you want to dene.
2. Enter the values or range of values that represent missing data.
Chapter 5. Data Editor
49
Roles
Some dialogs support predened roles that can be used to pre-select variables for analysis. When you
open one of these dialogs, variables that meet the role requirements will be automatically displayed in
the destination list(s). Available roles are:
Input. The variable will be used as an input (e.g., predictor, independent variable).
Target. The variable will be used as an output or target (e.g., dependent variable).
Both. The variable will be used as both input and output.
None. The variable has no role assignment.
Partition. The variable will be used to partition the data into separate samples for training, testing, and
validation.
Split. Included for round-trip compatibility with IBM SPSS Modeler. Variables with this role are not used
as split-le variables in IBM SPSS Statistics.
• By default, all variables are assigned the Input role. This includes data from external le formats and
data les from versions of IBM SPSS Statistics prior to version 18.
• Role assignment only affects dialogs that support role assignment. It has no effect on command syntax.
To assign roles
1. Select the role from the list in the Role cell for the variable.
Column width
You can specify a number of characters for the column width. Column widths can also be changed in Data
View by clicking and dragging the column borders.
• Column width for proportional fonts is based on average character width. Depending on the characters
used in the value, more or fewer characters may be displayed in the specied width.
• Column width affect only the display of values in the Data Editor. Changing the column width does not
change the dened width of a variable.
Variable alignment
Alignment controls the display of data values and/or value labels in Data View. The default alignment is
right for numeric variables and left for string variables. This setting affects only the display in Data View.
Applying variable denition attributes to multiple variables
After you have dened variable denition attributes for a variable, you can copy one or more attributes
and apply them to one or more variables.
Basic copy and paste operations are used to apply variable denition attributes. You can:
• Copy a single attribute (for example, value labels) and paste it to the same attribute cell(s) for one or
more variables.
• Copy all attributes from one variable and paste them to one or more other variables.
• Create multiple new variables with all the attributes of a copied variable.
Applying variable denition attributes to other variables
To Apply Individual Attributes from a Dened Variable
1. In Variable View, select the attribute cell that you want to apply to other variables.
2. From the menus choose:
Edit > Copy
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IBM SPSS Statistics 27 Core System User's Guide
3. Select the attribute cell(s) to which you want to apply the attribute. (You can select multiple target
variables.)
4. From the menus choose:
Edit > Paste
If you paste the attribute to blank rows, new variables are created with default attributes for all attributes
except the selected attribute.
To apply all attributes from a dened variable
1. In Variable View, select the row number for the variable with the attributes that you want to use. (The
entire row is highlighted.)
2. From the menus choose:
Edit > Copy
3. Select the row number(s) for the variable(s) to which you want to apply the attributes. (You can select
multiple target variables.)
4. From the menus choose:
Edit > Paste
Generating multiple new variables with the same attributes
1. In Variable View, click the row number for the variable that has the attributes that you want to use for
the new variable. (The entire row is highlighted.)
2. From the menus choose:
Edit > Copy
3. Click the empty row number beneath the last dened variable in the data le.
4. From the menus choose:
Edit > Paste Variables...
5. In the Paste Variables dialog box, enter the number of variables that you want to create.
6. Enter a prex and starting number for the new variables.
7. Click OK.
The new variable names will consist of the specied prex plus a sequential number starting with the
specied number.
Custom Variable Attributes
In addition to the standard variable attributes (for example, value labels, missing values, measurement
level), you can create your own custom variable attributes. Like standard variable attributes, these
custom attributes are saved with IBM SPSS Statistics data les. Therefore, you could create a variable
attribute that identies the type of response for survey questions (for example, single selection, multiple
selection, ll-in-the-blank) or the formulas used for computed variables.
Creating Custom Variable Attributes
To create new custom attributes:
1. In Variable View, from the menus choose:
Data > New Custom Attribute...
2. Drag and drop the variables to which you want to assign the new attribute to the Selected Variables
list.
3. Enter a name for the attribute. Attribute names must follow the same rules as variable names. See the
topic “Variable names” on page 46
for more information.
Chapter 5. Data Editor
51
4. Enter an optional value for the attribute. If you select multiple variables, the value is assigned to all
selected variables. You can leave this blank and then enter values for each variable in Variable View.
Display attribute in the Data Editor. Displays the attribute in Variable View of the Data Editor. For
information on controlling the display of custom attributes, see “Displaying and Editing Custom Variable
Attributes” on page 52 below.
Display Dened List of Attributes. Displays a list of custom attributes already dened for the dataset.
Attribute names that begin with a dollar sign ($) are reserved attributes that cannot be modied.
Displaying and Editing Custom Variable Attributes
Custom variable attributes can be displayed and edited in the Data Editor in Variable View.
• Custom variable attribute names are enclosed in square brackets.
• Attribute names that begin with a dollar sign are reserved and cannot be modied.
• A blank cell indicates that the attribute does not exist for that variable; the text Empty displayed in a cell
indicates that the attribute exists for that variable but no value has been assigned to the attribute for
that variable. Once you enter text in the cell, the attribute exists for that variable with the value you
enter.
• The text Array... displayed in a cell indicates that this is an attribute array--an attribute that contains
multiple values. Click the button in the cell to display the list of values.
To Display and Edit Custom Variable Attributes
1. In Variable View, from the menus choose:
View > Customize Variable View...
2. Select (check) the custom variable attributes you want to display. (The custom variable attributes are
the ones enclosed in square brackets.)
Once the attributes are displayed in Variable View, you can edit them directly in the Data Editor.
Variable Attribute Arrays
The text Array... (displayed in a cell for a custom variable attribute in Variable View or in the Custom
Variable Properties dialog box in Dene Variable Properties) indicates that this is an attribute array, an
attribute that contains multiple values. For example, you could have an attribute array that identies all of
the source variables used to compute a derived variable. Click the button in the cell to display and edit the
list of values.
Customizing Variable View
You can use Customize Variable View to control which attributes are displayed in Variable View (for
example, name, type, label) and the order in which they are displayed.
• Any custom variable attributes associated with the dataset are enclosed in square brackets. See the
topic “Creating Custom Variable Attributes” on page 51
for more information.
• Customized display settings are saved with IBM SPSS Statistics data les.
• You can also control the default display and order of attributes in Variable View. See the topic
“Changing the default variable view” on page 184 for more information.
To customize Variable View
1. In Variable View, from the menus choose:
View > Customize Variable View...
2. Select (check) the variable attributes you want to display.
3. Use the up and down arrow buttons to change the display order of the attributes.
Restore Defaults. Apply the default display and order settings.
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Spell checking
variable and value labels
To check the spelling of variable labels and value labels:
1. Select the Variable View tab in the Data Editor window.
2. Right-click the Labels or Values column and from the pop-up menu choose:
Spelling
or
3. In Variable View, from the menus choose:
Utilities > Spelling
or
4. In the Value Labels dialog box, click Spelling. (This limits the spell checking to the value labels for a
particular variable.)
Spell checking is limited to variable labels and value labels in Variable View of the Data Editor.
String data values
To check the spelling of string data values:
1. Select the Data View tab of the Data Editor.
2. Optionally, select one or more variables (columns) to check. To select a variable, click the variable
name at the top of the column.
3. From the menus choose:
Utilities > Spelling
• If there are no selected variables in Data View, all string variables will be checked.
• If there are no string variables in the dataset or the none of the selected variables is a string variable,
the Spelling option on the Utilities menu is disabled.
Customizing Variable View
You can use Customize Variable View to control which attributes are displayed in Variable View (for
example, name, type, label) and the order in which they are displayed.
• Any custom variable attributes associated with the dataset are enclosed in square brackets. See the
topic “Creating Custom Variable Attributes” on page 51
for more information.
• Customized display settings are saved with IBM SPSS Statistics data les.
• You can also control the default display and order of attributes in Variable View. See the topic
“Changing the default variable view” on page 184 for more information.
To customize Variable View
1. In Variable View, from the menus choose:
View > Customize Variable View...
2. Select (check) the variable attributes you want to display.
3. Use the up and down arrow buttons to change the display order of the attributes.
Restore Defaults. Apply the default display and order settings.
Spell checking
variable and value labels
To check the spelling of variable labels and value labels:
1. Select the Variable View tab in the Data Editor window.
Chapter 5. Data Editor
53
2. Right-click the Labels or Values column and from the pop-up menu choose:
Spelling
or
3. In Variable View, from the menus choose:
Utilities > Spelling
or
4. In the Value Labels dialog box, click Spelling. (This limits the spell checking to the value labels for a
particular variable.)
Spell checking is limited to variable labels and value labels in Variable View of the Data Editor.
String data values
To check the spelling of string data values:
1. Select the Data View tab of the Data Editor.
2. Optionally, select one or more variables (columns) to check. To select a variable, click the variable
name at the top of the column.
3. From the menus choose:
Utilities > Spelling
• If there are no selected variables in Data View, all string variables will be checked.
• If there are no string variables in the dataset or the none of the selected variables is a string variable,
the Spelling option on the Utilities menu is disabled.
Entering data
In Data View, you can enter data directly in the Data Editor. You can enter data in any order. You can enter
data by case or by variable, for selected areas or for individual cells.
• The active cell is highlighted.
• The variable name and row number of the active cell are displayed in the top left corner of the Data
Editor.
• When you select a cell and enter a data value, the value is displayed in the cell editor at the top of the
Data Editor.
• Data values are not recorded until you press Enter or select another cell.
• To enter anything other than simple numeric data, you must dene the variable type rst.
If you enter a value in an empty column, the Data Editor automatically creates a new variable and assigns
a variable name.
To enter numeric data
1. Select a cell in Data View.
2. Enter the data value. (The value is displayed in the cell editor at the top of the Data Editor.)
3. To record the value, press Enter or select another cell.
To enter non-numeric data
1. Double-click a variable name at the top of the column in Data View or click the Variable View tab.
2. Click the button in the Type cell for the variable.
3. Select the data type in the Variable Type dialog box.
4. Click OK.
5. Double-click the row number or click the Data View tab.
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IBM SPSS Statistics 27 Core System User's Guide
6. Enter the data in the column for the newly dened variable.
To use value labels for data entry
1. If value labels aren't currently displayed in Data View, from the menus choose:
View > Value Labels
2. Click the cell in which you want to enter the value.
3. Choose a value label from the drop-down list.
The value is entered, and the value label is displayed in the cell.
Note: This process works only if you have dened value labels for the variable.
Data value restrictions in the data editor
The dened variable type and width determine the type of value that can be entered in the cell in Data
View.
• If you type a character that is not allowed by the dened variable type, the character is not entered.
• For string variables, characters beyond the dened width are not allowed.
• For numeric variables, integer values that exceed the dened width can be entered, but the Data Editor
displays either scientic notation or a portion of the value followed by an ellipsis (...) to indicate that the
value is wider than the dened width. To display the value in the cell, change the dened width of the
variable.
Note: Changing the column width does not affect the variable width.
Editing data
With the Data Editor, you can modify data values in Data View in many ways. You can:
• Change data values
• Cut, copy, and paste data values
• Add and delete cases
• Add and delete variables
• Change the order of variables
Replacing or modifying data values
To Delete the Old Value and Enter a New Value
1. In Data View, double-click the cell. (The cell value is displayed in the cell editor.)
2. Edit the value directly in the cell or in the cell editor.
3. Press Enter or select another cell to record the new value.
Cutting, copying, and pasting data values
You can cut, copy, and paste individual cell values or groups of values in the Data Editor. You can:
• Move or copy a single cell value to another cell
• Move or copy a single cell value to a group of cells
• Move or copy the values for a single case (row) to multiple cases
• Move or copy the values for a single variable (column) to multiple variables
• Move or copy a group of cell values to another group of cells
Chapter 5. Data Editor
55
Data conversion for pasted values in the data editor
If the dened variable types of the source and target cells are not the same, the Data Editor attempts to
convert the value. If no conversion is possible, the system-missing value is inserted in the target cell.
Converting numeric or date into string. Numeric (for example, numeric, dollar, dot, or comma) and date
formats are converted to strings if they are pasted into a string variable cell. The string value is the
numeric value as displayed in the cell. For example, for a dollar format variable, the displayed dollar sign
becomes part of the string value. Values that exceed the dened string variable width are truncated.
Converting string into numeric or date. String values that contain acceptable characters for the numeric
or date format of the target cell are converted to the equivalent numeric or date value. For example, a
string value of 25/12/91 is converted to a valid date if the format type of the target cell is one of the day-
month-year formats, but the value is converted to system-missing if the format type of the target cell is
one of the month-day-year formats.
Converting date into numeric. Date and time values are converted to a number of seconds if the target
cell is one of the numeric formats (for example, numeric, dollar, dot, or comma). Because dates are
stored internally as the number of seconds since October 14, 1582, converting dates to numeric values
can yield some extremely large numbers. For example, the date 10/29/91 is converted to a numeric value
of 12,908,073,600.
Converting numeric into date or time. Numeric values are converted to dates or times if the value
represents a number of seconds that can produce a valid date or time. For dates, numeric values that are
less than 86,400 are converted to the system-missing value.
Inserting new cases
Entering data in a cell in a blank row automatically creates a new case. The Data Editor inserts the
system-missing value for all other variables for that case. If there are any blank rows between the new
case and the existing cases, the blank rows become new cases with the system-missing value for all
variables. You can also insert new cases between existing cases.
To insert new cases between existing cases
1. In Data View, select any cell in the case (row) below the position where you want to insert the new
case.
2. From the menus choose:
Edit > Insert Cases
A new row is inserted for the case, and all variables receive the system-missing value.
Inserting new variables
Entering data in an empty column in Data View or in an empty row in Variable View automatically creates
a new variable with a default variable name (the prex var and a sequential number) and a default data
format type (numeric). The Data Editor inserts the system-missing value for all cases for the new variable.
If there are any empty columns in Data View or empty rows in Variable View between the new variable
and the existing variables, these rows or columns also become new variables with the system-missing
value for all cases. You can also insert new variables between existing variables.
To insert new variables between existing variables
1. Select any cell in the variable to the right of (Data View) or below (Variable View) the position where
you want to insert the new variable.
2. From the menus choose:
Edit > Insert Variable
A new variable is inserted with the system-missing value for all cases.
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To move variables
1. To select the variable, click the variable name in Data View or the row number for the variable in
Variable View.
2. Drag and drop the variable to the new location.
3. If you want to place the variable between two existing variables: In Data View, drop the variable on the
variable column to the right of where you want to place the variable, or in Variable View, drop the
variable on the variable row below where you want to place the variable.
To change data type
You can change the data type for a variable at any time by using the Variable Type dialog box in Variable
View. The Data Editor will attempt to convert existing values to the new type. If no conversion is possible,
the system-missing value is assigned. The conversion rules are the same as the rules for pasting data
values to a variable with a different format type. If the change in data format may result in the loss of
missing-value specications or value labels, the Data Editor displays an alert box and asks whether you
want to proceed with the change or cancel it.
Finding cases, variables, or imputations
The Go To dialog box nds the specied case (row) number or variable name in the Data Editor.
Cases
1. For cases, from the menus choose:
Edit > Go to Case...
2. Enter an integer value that represents the current row number in Data View.
Note: The current row number for a particular case can change due to sorting and other actions.
Variables
1. For variables, from the menus choose:
Edit > Go to Variable...
2. Enter the variable name or select the variable from the drop-down list.
Imputations
1. From the menus choose:
Edit > Go to Imputation...
2. Select the imputation (or Original data) from the drop-down list.
Alternatively, you can select the imputation from the drop-down list in the edit bar in Data View of the
Data Editor.
Relative case position is preserved when selecting imputations. For example, if there are 1000 cases in
the original dataset, case 1034, the 34th case in the rst imputation, displays at the top of the grid. If you
select imputation 2 in the dropdown, case 2034, the 34th case in imputation 2, would display at the top
of the grid. If you select Original data in the dropdown, case 34 would display at the top of the grid.
Column position is also preserved when navigating between imputations, so that it is easy to compare
values between imputations.
Finding and replacing data and attribute values
To nd and/or replace data values in Data View or attribute values in Variable View:
1. Click a cell in the column you want to search. (Finding and replacing values is restricted to a single
column.)
2. From the menus choose:
Chapter 5. Data Editor
57
Edit > Find
or
Edit > Replace
Data View
• You cannot search up in Data View. The search direction is always down.
• For dates and times, the formatted values as displayed in Data View are searched. For example, a date
displayed as 10/28/2007 will not be found by a search for a date of 10-28-2007.
• For other numeric variables, Contains, Begins with, and Ends with search formatted values. For
example, with the Begins with option, a search value of $123 for a Dollar format variable will nd both
$123.00 and $123.40 but not $1,234. With the Entire cell option, the search value can be formatted or
unformatted (simple F numeric format), but only exact numeric values (to the precision displayed in the
Data Editor) are matched.
• The numeric system-missing value is represented by a single period (.) To nd system-missing values,
enter a single period as the search value and select Entire cell.
• If value labels are displayed for the selected variable column, the label text is searched, not the
underlying data value, and you cannot replace the label text.
Variable View
• Find is only available for the Name, Label, Values, Missing, and custom variable attribute columns.
• Replace is only available for the Label, Values, and custom attribute columns.
• In the Values (value labels) column, the search string can match either the data value or a value label.
Note: Replacing the data value will delete any previous value label associated with that value.
Obtaining Descriptive Statistics for Selected Variables
To obtain descriptive statistics for selected variables:
1. Right-click the selected variables in either Data View or Variable View.
2. From the pop-up menu select Descriptive Statistics.
By default, frequency tables (tables of counts) are displayed for all variables with 24 or fewer unique
values. Summary statistics are determined by variable measurement level and data type (numeric or
string):
• String. No summary statistics are calculated for string variables.
• Numeric, nominal or unknown measurement level. Range, minimum, maximum, mode.
• Numeric, ordinal measurement level. Range, minimum, maximum, mode, mean, median.
• Numeric, continuous (scale) measurement level. Range, minimum, maximum, mode, mean, median,
standard deviation.
You can also obtain bar charts for nominal and ordinal variables, histograms for continuous (scale)
variables, and change the cut-off value that determines when to display frequency tables. See the topic
“Output options” on page 184 for more information.
Case selection status in the Data Editor
If you have selected a subset of cases but have not discarded unselected cases, unselected cases are
marked in the Data Editor with a diagonal line (slash) through the row number.
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Figure 1. Filtered cases in the Data Editor
Data Editor display options
The View menu provides several display options for the Data Editor:
Fonts. This option controls the font characteristics of the data display.
Grid Lines. This option toggles the display of grid lines.
Value Labels. This option toggles between the display of actual data values and user-dened descriptive
value labels. This option is available only in Data View.
Using Multiple Views
In Data View, you can create multiple views (panes) by using the splitters that are located below the
horizontal scroll bar and to the right of the vertical scroll bar.
You can also use the Window menu to insert and remove pane splitters. To insert splitters:
1. In Data View, from the menus choose:
Window > Split
Splitters are inserted above and to the left of the selected cell.
• If the top left cell is selected, splitters are inserted to divide the current view approximately in half, both
horizontally and vertically.
• If any cell other than the top cell in the rst column is selected, a horizontal pane splitter is inserted
above the selected cell.
• If any cell other than the rst cell in the top row is selected, a vertical pane splitter is inserted to the left
of the selected cell.
Data Editor printing
A data le is printed as it appears on the screen.
• The information in the currently displayed view is printed. In Data View, the data are printed. In Variable
View, data denition information is printed.
• Grid lines are printed if they are currently displayed in the selected view.
• Value labels are printed in Data View if they are currently displayed. Otherwise, the actual data values
are printed.
Use the View menu in the Data Editor window to display or hide grid lines and toggle between the display
of data values and value labels.
To print Data Editor contents
1. Make the Data Editor the active window.
Chapter 5. Data Editor
59
2. Click the tab for the view that you want to print.
3. From the menus choose:
File > Print...
60 IBM SPSS Statistics 27 Core System User's Guide
Chapter 6. Working with Multiple Data Sources
Starting with version 14.0, multiple data sources can be open at the same time, making it easier to:
• Switch back and forth between data sources.
• Compare the contents of different data sources.
• Copy and paste data between data sources.
• Create multiple subsets of cases and/or variables for analysis.
• Merge multiple data sources from various data formats (for example, spreadsheet, database, text data)
without saving each data source rst.
Basic Handling of Multiple Data Sources
By default, each data source that you open is displayed in a new Data Editor window. (See “General
options” on page 179 for information on changing the default behavior to only display one dataset at a
time, in a single Data Editor window.)
• Any previously open data sources remain open and available for further use.
• When you rst open a data source, it automatically becomes the active dataset.
• You can change the active dataset simply by clicking anywhere in the Data Editor window of the data
source that you want to use or by selecting the Data Editor window for that data source from the
Window menu.
• Only the variables in the active dataset are available for analysis.
• You cannot change the active dataset when any dialog box that accesses the data is open (including all
dialog boxes that display variable lists).
• At least one Data Editor window must be open during a session. When you close the last open Data
Editor window, IBM SPSS Statistics automatically shuts down, prompting you to save changes rst.
Working with Multiple Datasets in Command Syntax
If you use command syntax to open data sources (for example, GET FILE, GET DATA), you need to use
the DATASET NAME command to name each dataset explicitly in order to have more than one data source
open at the same time.
When working with command syntax, the active dataset name is displayed on the toolbar of the syntax
window. All of the following actions can change the active dataset:
• Use the DATASET ACTIVATE command.
• Click anywhere in the Data Editor window of a dataset.
• Select a dataset name from the Active drop-down list on the toolbar in the syntax window.
Copying and Pasting Information between Datasets
You can copy both data and variable denition attributes from one dataset to another dataset in basically
the same way that you copy and paste information within a single data le.
• Copying and pasting selected data cells in Data View pastes only the data values, with no variable
denition attributes.
• Copying and pasting an entire variable in Data View by selecting the variable name at the top of the
column pastes all of the data and all of the variable denition attributes for that variable.
• Copying and pasting variable denition attributes or entire variables in Variable View pastes the
selected attributes (or the entire variable denition) but does not paste any data values.
Renaming Datasets
When you open a data source through the menus and dialog boxes, each data source is automatically
assigned a dataset name of DataSetn, where n is a sequential integer value, and when you open a data
source using command syntax, no dataset name is assigned unless you explicitly specify one with
DATASET NAME . To provide more descriptive dataset names:
1. From the menus in the Data Editor window for the dataset whose name you want to change choose:
File > Rename Dataset...
2. Enter a new dataset name that conforms to variable naming rules. See the topic “Variable names” on
page 46 for more information.
Suppressing Multiple Datasets
If you prefer to have only one dataset available at a time and want to suppress the multiple dataset
feature:
1. From the menus choose:
Edit > Options...
2. Click the General tab.
Select (check) Open only one dataset at a time.
See the topic “General options” on page 179 for more information.
62 IBM SPSS Statistics 27 Core System User's Guide
Chapter 7. Data preparation
Once you've opened a data le or entered data in the Data Editor, you can start creating reports, charts,
and analyses without any additional preliminary work. However, there are some additional data
preparation features that you may nd useful, including the ability to:
• Assign variable properties that describe the data and determine how certain values should be treated.
• Identify cases that may contain duplicate information and exclude those cases from analyses or delete
them from the data le.
• Create new variables with a few distinct categories that represent ranges of values from variables with a
large number of possible values.
Variable properties
Data entered in the Data Editor in Data View or read from an external le format (such as an Excel
spreadsheet or a text data le) lack certain variable properties that you may nd very useful, including:
• Denition of descriptive value labels for numeric codes (for example, 0 = Male and 1 = Female).
• Identication of missing values codes (for example, 99 = Not applicable).
• Assignment of measurement level (nominal, ordinal, or scale).
All of these variable properties (and others) can be assigned in Variable View in the Data Editor. There are
also several utilities that can assist you in this process:
• Dene Variable Properties can help you dene descriptive value labels and missing values. This is
particularly useful for categorical data with numeric codes used for category values. See the topic
“Dening Variable Properties” on page 63
for more information.
• Set Measurement Level for Unknown identies variables (elds) that do not have a dened
measurement level and provides the ability to set the measurement level for those variables. This is
important for procedures in which measurement level can affect the results or determines which
features are available. See the topic “Setting measurement level for variables with unknown
measurement level” on page 66 for more information.
• Copy Data Properties provides the ability to use an existing IBM SPSS Statistics data le as a template
for le and variable properties in the current data le. This is particularly useful if you frequently use
external-format data les that contain similar content (such as monthly reports in Excel format). See
the topic “Copying Data Properties” on page 68 for more information.
Dening Variable Properties
Dene Variable Properties is designed to assist you in the process of assigning attributes to variables,
including creating descriptive value labels for categorical (nominal, ordinal) variables. Dene Variable
Properties:
• Scans the actual data values and lists all unique data values for each selected variable.
• Identies unlabeled values and provides an "auto-label" feature.
• Provides the ability to copy dened value labels and other attributes from another variable to the
selected variable or from the selected variable to multiple additional variables.
Note: To use Dene Variable Properties without rst scanning cases, enter 0 for the number of cases to
scan.
To Dene Variable Properties
1. From the menus choose:
Data > Dene Variable Properties...
2. Select the numeric or string variables for which you want to create value labels or dene or change
other variable properties, such as missing values or descriptive variable labels.
3. Specify the number of cases to scan to generate the list of unique values. This is particularly useful
for data les with a large number of cases for which a scan of the complete data le might take a
signicant amount of time.
4. Specify an upper limit for the number of unique values to display. This is primarily useful to prevent
listing hundreds, thousands, or even millions of values for scale (continuous interval, ratio) variables.
5. Click Continue to open the main Dene Variable Properties dialog box.
6. Select a variable for which you want to create value labels or dene or change other variable
properties.
7. Enter the label text for any unlabeled values that are displayed in the Value Label grid.
8. If there are values for which you want to create value labels but those values are not displayed, you
can enter values in the Value column below the last scanned value.
9. Repeat this process for each listed variable for which you want to create value labels.
10. Click OK to apply the value labels and other variable properties.
Dening Value Labels and Other Variable Properties
The Dene Variable Properties main dialog box provides the following information for the scanned
variables:
Scanned Variable List. For each scanned variable, a check mark in the Unlabeled (U.) column indicates
that the variable contains values without assigned value labels.
To sort the variable list to display all variables with unlabeled values at the top of the list:
1. Click the Unlabeled column heading under Scanned Variable List.
You can also sort by variable name or measurement level by clicking the corresponding column heading
under Scanned Variable List.
Value Label Grid
• Label. Displays any value labels that have already been dened. You can add or change labels in this
column.
• Value. Unique values for each selected variable. This list of unique values is based on the number of
scanned cases. For example, if you scanned only the rst 100 cases in the data le, then the list reflects
only the unique values present in those cases. If the data le has already been sorted by the variable for
which you want to assign value labels, the list may display far fewer unique values than are actually
present in the data.
• Count. The number of times each value occurs in the scanned cases.
• Missing. Values dened as representing missing data. You can change the missing values designation of
the category by clicking the check box. A check indicates that the category is dened as a user-missing
category. If a variable already has a range of values dened as user-missing (for example, 90-99), you
cannot add or delete missing values categories for that variable with Dene Variable Properties. You can
use Variable View in the Data Editor to modify the missing values categories for variables with missing
values ranges. See the topic “Missing values” on page 49
for more information.
• Changed. Indicates that you have added or changed a value label.
Note: If you specied 0 for the number of cases to scan in the initial dialog box, the Value Label grid will
initially be blank, except for any preexisting value labels and/or dened missing values categories for the
selected variable. In addition, the Suggest button for the measurement level will be disabled.
Measurement Level. Value labels are primarily useful for categorical (nominal and ordinal) variables, and
some procedures treat categorical and scale variables differently; so it is sometimes important to assign
the correct measurement level. However, by default, all new numeric variables are assigned the scale
measurement level. Thus, many variables that are in fact categorical may initially be displayed as scale.
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If you are unsure of what measurement level to assign to a variable, click Suggest.
Role. Some dialogs support the ability to pre-select variables for analysis based on dened roles. See the
topic “Roles” on page 50 for more information.
Copy Properties. You can copy value labels and other variable properties from another variable to the
currently selected variable or from the currently selected variable to one or more other variables.
Unlabeled Values. To create labels for unlabeled values automatically, click Automatic Labels.
Variable Label and Display Format
You can change the descriptive variable label and the display format.
• You cannot change the variable's fundamental type (string or numeric).
• For string variables, you can change only the variable label, not the display format.
• For numeric variables, you can change the numeric type (such as numeric, date, dollar, or custom
currency), width (maximum number of digits, including any decimal and/or grouping indicators), and
number of decimal positions.
• For numeric date format, you can select a specic date format (such as dd-mm-yyyy, mm/dd/yy, and
yyyyddd)
• For numeric custom format, you can select one of ve custom currency formats (CCA through CCE). See
the topic “Currency options” on page 184 for more information.
• An asterisk is displayed in the Value column if the specied width is less than the width of the scanned
values or the displayed values for preexisting dened value labels or missing values categories.
• A period (.) is displayed if the scanned values or the displayed values for preexisting dened value
labels or missing values categories are invalid for the selected display format type. For example, an
internal numeric value of less than 86,400 is invalid for a date format variable.
Assigning the Measurement Level
When you click Suggest for the measurement level in the Dene Variable Properties main dialog box, the
current variable is evaluated based on the scanned cases and dened value labels, and a measurement
level is suggested in the Suggest Measurement Level dialog box that opens. The Explanation area
provides a brief description of the criteria used to provide the suggested measurement level.
Note: Values dened as representing missing values are not included in the evaluation for measurement
level. For example, the explanation for the suggested measurement level may indicate that the
suggestion is in part based on the fact that the variable contains no negative values, whereas it may in
fact contain negative values--but those values are already dened as missing values.
1. Click Continue to accept the suggested level of measurement or Cancel to leave the measurement
level unchanged.
Custom Variable Attributes
The Attributes button in Dene Variable Properties opens the Custom Variable Attributes dialog box. In
addition to the standard variable attributes, such as value labels, missing values, and measurement level,
you can create your own custom variable attributes. Like standard variable attributes, these custom
attributes are saved with IBM SPSS Statistics data les.
Name. Attribute names must follow the same rules as variable names. See the topic “Variable names” on
page 46 for more information.
Value. The value assigned to the attribute for the selected variable.
• Attribute names that begin with a dollar sign are reserved and cannot be modied. You can view the
contents of a reserved attribute by clicking the button in the desired cell.
• The text Array..., displayed in a Value cell, indicates that this is an attribute array, an attribute that
contains multiple values. Click the button in the cell to display the list of values.
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Copying Variable Properties
The Apply Labels and Level dialog box is displayed when you click From Another Variable or To Other
Variables in the Dene Variable Properties main dialog box. It displays all of the scanned variables that
match the current variable's type (numeric or string). For string variables, the dened width must also
match.
1. Select a single variable from which to copy value labels and other variable properties (except variable
label).
or
2. Select one or more variables to which to copy value labels and other variable properties.
3. Click Copy to copy the value labels and the measurement level.
• Existing value labels and missing value categories for target variable(s) are not replaced.
• Value labels and missing value categories for values not already dened for the target variable(s) are
added to the set of value labels and missing value categories for the target variable(s).
• The measurement level for the target variable is always replaced.
• The role for the target variable is always replaced.
• If either the source or target variable has a dened range of missing values, missing values denitions
are not copied.
Setting measurement level for variables with unknown measurement level
For some procedures, measurement level can affect the results or determine which features are
available, and you cannot access the dialogs for these procedures until all variables have a dened
measurement level. The Set Measurement Level for Unknown dialog allows you to dene measurement
level for any variables with an unknown measurement level without performing a data pass (which may be
time-consuming for large data les).
Under certain conditions, the measurement level for some or all numeric variables (elds) in a le may be
unknown. These conditions include:
• Numeric variables from Excel 95 or later les, text data les, or data base sources prior to the rst data
pass.
• New numeric variables created with transformation commands prior to the rst data pass after creation
of those variables.
These conditions apply primarily to reading data or creating new variables via command syntax. Dialogs
for reading data and creating new transformed variables automatically perform a data pass that sets the
measurement level, based on the default measurement level rules.
To set the measurement level for variables with an unknown measurement level
1. In the alert dialog that appears for the procedure, click Assign Manually.
or
2. From the menus, choose:
Data > Set Measurement Level for Unknown
3. Move variables (elds) from the source list to the appropriate measurement level destination list.
• Nominal. A variable can be treated as nominal when its values represent categories with no intrinsic
ranking (for example, the department of the company in which an employee works). Examples of
nominal variables include region, postal code, and religious afliation.
• Ordinal. A variable can be treated as ordinal when its values represent categories with some intrinsic
ranking (for example, levels of service satisfaction from highly dissatised to highly satised). Examples
of ordinal variables include attitude scores representing degree of satisfaction or condence and
preference rating scores.
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• Continuous. A variable can be treated as scale (continuous) when its values represent ordered
categories with a meaningful metric, so that distance comparisons between values are appropriate.
Examples of scale variables include age in years and income in thousands of dollars.
Multiple Response Sets
Custom Tables and the Chart Builder support a special kind of "variable" called a multiple response set.
Multiple response sets aren't really "variables" in the normal sense. You can't see them in the Data Editor,
and other procedures don't recognize them. Multiple response sets use multiple variables to record
responses to questions where the respondent can give more than one answer. Multiple response sets are
treated like categorical variables, and most of the things you can do with categorical variables, you can
also do with multiple response sets.
Multiple response sets are constructed from multiple variables in the data le. A multiple response set is
a special construct within a data le. You can dene and save multiple response sets in IBM SPSS
Statistics data les, but you cannot import or export multiple response sets from/to other le formats.
You can copy multiple response sets from other IBM SPSS Statistics data les using Copy Data
Properties, which is accessed from the Data menu in the Data Editor window.
Dening Multiple Response Sets
To dene multiple response sets:
1. From the menus, choose:
Data > Dene Multiple Response Sets...
2. Select two or more variables. If your variables are coded as dichotomies, indicate which value you
want to have counted.
3. Enter a unique name for each multiple response set. The name can be up to 63 bytes long. A dollar
sign is automatically added to the beginning of the set name.
4. Enter a descriptive label for the set. (This is optional.)
5. Click Add to add the multiple response set to the list of dened sets.
Dichotomies
A multiple dichotomy set typically consists of multiple dichotomous variables: variables with only two
possible values of a yes/no, present/absent, checked/not checked nature. Although the variables may not
be strictly dichotomous, all of the variables in the set are coded the same way, and the Counted Value
represents the positive/present/checked condition.
For example, a survey asks the question, "Which of the following sources do you rely on for news?" and
provides ve possible responses. The respondent can indicate multiple choices by checking a box next to
each choice. The ve responses become ve variables in the data le, coded 0 for No (not checked) and 1
for Yes (checked). In the multiple dichotomy set, the Counted Value is 1.
The sample data le survey_sample.sav already has three dened multiple response sets. $mltnews is a
multiple dichotomy set.
1. Select (click) $mltnews in the Mult. Response Sets list.
This displays the variables and settings used to dene this multiple response set.
• The Variables in Set list displays the ve variables used to construct the multiple response set.
• The Variable Coding group indicates that the variables are dichotomous.
• The Counted Value is 1.
2. Select (click) one of the variables in the Variables in Set list.
3. Right-click the variable and select Variable Information from the pop-up pop-up menu.
4. In the Variable Information window, click the arrow on the Value Labels drop-down list to display the
entire list of dened value labels.
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The value labels indicate that the variable is a dichotomy with values of 0 and 1, representing No and Yes,
respectively. All ve variables in the list are coded the same way, and the value of 1 (the code for Yes) is
the counted value for the multiple dichotomy set.
Categories
A multiple category set consists of multiple variables, all coded the same way, often with many possible
response categories. For example, a survey item states, "Name up to three nationalities that best
describe your ethnic heritage." There may be hundreds of possible responses, but for coding purposes
the list is limited to the 40 most common nationalities, with everything else relegated to an "other"
category. In the data le, the three choices become three variables, each with 41 categories (40 coded
nationalities and one "other" category).
In the sample data le, $ethmult and $mltcars are multiple category sets.
Category Label Source
For multiple dichotomies, you can control how sets are labeled.
• Variable labels. Uses the dened variable labels (or variable names for variables without dened
variable labels) as the set category labels. For example, if all of the variables in the set have the same
value label (or no dened value labels) for the counted value (for example, Yes), then you should use the
variable labels as the set category labels.
• Labels of counted values. Uses the dened value labels of the counted values as set category labels.
Select this option only if all variables have a dened value label for the counted value and the value
label for the counted value is different for each variable.
• Use variable label as set label. If you select Label of counted values, you can also use the variable
label for the rst variable in the set with a dened variable label as the set label. If none of the variables
in the set have dened variable labels, the name of the rst variable in the set is used as the set label.
Copy Data Properties
Copying Data Properties
The Copy Data Properties Wizard provides the ability to use an external IBM SPSS Statistics data le as a
template for dening le and variable properties in the active dataset. You can also use variables in the
active dataset as templates for other variables in the active dataset. You can:
• Copy selected le properties from an external data le or open dataset to the active dataset. File
properties include documents, le labels, multiple response sets, variable sets, and weighting.
• Copy selected variable properties from an external data le or open dataset to matching variables in the
active dataset. Variable properties include value labels, missing values, level of measurement, variable
labels, print and write formats, alignment, and column width (in the Data Editor).
• Copy selected variable properties from one variable in either an external data le, open dataset, or the
active dataset to many variables in the active dataset.
• Create new variables in the active dataset based on selected variables in an external data le or open
dataset.
When copying data properties, the following general rules apply:
• If you use an external data le as the source data le, it must be a data le in IBM SPSS Statistics
format.
• If you use the active dataset as the source data le, it must contain at least one variable. You cannot
use a completely blank active dataset as the source data le.
• Undened (empty) properties in the source dataset do not overwrite dened properties in the active
dataset.
• Variable properties are copied from the source variable only to target variables of a matching type--
string (alphanumeric) or numeric (including numeric, date, and currency).
Note: Copy Data Properties replaces Apply Data Dictionary, formerly available on the File menu.
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To Copy Data Properties
1. From the menus in the Data Editor window choose:
Data > Copy Data Properties...
2. Select the data le with the le and/or variable properties that you want to copy. This can be a
currently open dataset, an external IBM SPSS Statistics data le, or the active dataset.
3. Follow the step-by-step instructions in the Copy Data Properties Wizard.
Selecting Source and Target Variables
In this step, you can specify the source variables containing the variable properties that you want to copy
and the target variables that will receive those variable properties.
Apply properties from selected source dataset variables to matching active dataset variables.
Variable properties are copied from one or more selected source variables to matching variables in the
active dataset. Variables "match" if both the variable name and type (string or numeric) are the same. For
string variables, the dened length must also be the same. By default, only matching variables are
displayed in the two variable lists.
• Create matching variables in the active dataset if they do not already exist. This updates the source
list to display all variables in the source data le. If you select source variables that do not exist in the
active dataset (based on variable name), new variables will be created in the active dataset with the
variable names and properties from the source data le.
If the active dataset contains no variables (a blank, new dataset), all variables in the source data le are
displayed and new variables based on the selected source variables are automatically created in the
active dataset.
Apply properties from a single source variable to selected active dataset variables of the same type.
Variable properties from a single selected variable in the source list can be applied to one or more
selected variables in the active dataset list. Only variables of the same type (numeric or string) as the
selected variable in the source list are displayed in the active dataset list. For string variables, only strings
of the same dened length as the source variable are displayed. This option is not available if the active
dataset contains no variables.
Note: You cannot create new variables in the active dataset with this option.
Apply dataset properties only--no variable selection. Only le properties (for example, documents, le
label, weight) will be applied to the active dataset. No variable properties will be applied. This option is
not available if the active dataset is also the source data le.
Choosing Variable Properties to Copy
You can copy selected variable properties from the source variables to the target variables. Undened
(empty) properties in the source variables do not overwrite dened properties in the target variables.
Value Labels. Value labels are descriptive labels associated with data values. Value labels are often used
when numeric data values are used to represent non-numeric categories (for example, codes of 1 and 2
for Male and Female). You can replace or merge value labels in the target variables.
• Replace deletes any dened value labels for the target variable and replaces them with the dened
value labels from the source variable.
• Merge merges the dened value labels from the source variable with any existing dened value label for
the target variable. If the same value has a dened value label in both the source and target variables,
the value label in the target variable is unchanged.
Custom Attributes. User-dened custom variable attributes. See the topic “Custom Variable Attributes”
on page 51 for more information.
• Replace deletes any custom attributes for the target variable and replaces them with the dened
attributes from the source variable.
• Merge merges the dened attributes from the source variable with any existing dened attributes for
the target variable.
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Missing Values. Missing values are values identied as representing missing data (for example, 98 for Do
not know and 99 for Not applicable). Typically, these values also have dened value labels that describe
what the missing value codes stand for. Any existing dened missing values for the target variable are
deleted and replaced with the dened missing values from the source variable.
Variable Label. Descriptive variable labels can contain spaces and reserved characters not allowed in
variable names. If you're copying variable properties from a single source variable to multiple target
variables, you might want to think twice before selecting this option.
Measurement Level. The measurement level can be nominal, ordinal, or scale.
Role. Some dialogs support the ability to pre-select variables for analysis based on dened roles. See the
topic “Roles” on page 50 for more information.
Formats. For numeric variables, this controls numeric type (such as numeric, date, or currency), width
(total number of displayed characters, including leading and trailing characters and decimal indicator),
and number of decimal places displayed. This option is ignored for string variables.
Alignment. This affects only alignment (left, right, center) in Data View in the Data Editor.
Data Editor Column Width. This affects only column width in Data View in the Data Editor.
Copying Dataset (File) Properties
You can apply selected, global dataset properties from the source data le to the active dataset. (This is
not available if the active dataset is the source data le.)
Multiple Response Sets. Applies multiple response set denitions from the source data le to the active
dataset.
• Multiple response sets that contain no variables in the active dataset are ignored unless those variables
will be created based on specications in step 2 (Selecting Source and Target Variables) in the Copy
Data Properties Wizard.
• Replace deletes all multiple response sets in the active dataset and replaces them with the multiple
response sets from the source data le.
• Merge adds multiple response sets from the source data le to the collection of multiple response sets
in the active dataset. If a set with the same name exists in both les, the existing set in the active
dataset is unchanged.
Variable Sets. Variable sets are used to control the list of variables that are displayed in dialog boxes.
Variable sets are dened by selecting Dene Variable Sets from the Utilities menu.
• Sets in the source data le that contain variables that do not exist in the active dataset are ignored
unless those variables will be created based on specications in step 2 (Selecting Source and Target
Variables) in the Copy Data Properties Wizard.
• Replace deletes any existing variable sets in the active dataset, replacing them with variable sets from
the source data le.
• Merge adds variable sets from the source data le to the collection of variable sets in the active dataset.
If a set with the same name exists in both les, the existing set in the active dataset is unchanged.
Documents. Notes appended to the data le via the DOCUMENT command.
• Replace deletes any existing documents in the active dataset, replacing them with the documents from
the source data le.
• Merge combines documents from the source and active dataset. Unique documents in the source le
that do not exist in the active dataset are added to the active dataset. All documents are then sorted by
date.
Custom Attributes. Custom data le attributes, typically created with the DATAFILE ATTRIBUTE
command in command syntax.
• Replace deletes any existing custom data le attributes in the active dataset, replacing them with the
data le attributes from the source data le.
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• Merge combines data le attributes from the source and active dataset. Unique attribute names in the
source le that do not exist in the active dataset are added to the active dataset. If the same attribute
name exists in both data les, the named attribute in the active dataset is unchanged.
Weight Specication. Weights cases by the current weight variable in the source data le if there is a
matching variable in the active dataset. This overrides any weighting currently in effect in the active
dataset.
File Label. Descriptive label applied to a data le with the FILE LABEL command.
Results
The last step in the Copy Data Properties Wizard provides information on the number of variables for
which variable properties will be copied from the source data le, the number of new variables that will
be created, and the number of dataset (le) properties that will be copied.
You can also choose to paste the generated command syntax into a syntax window and save the syntax
for later use.
Identifying Duplicate Cases
"Duplicate" cases may occur in your data for many reasons, including:
• Data entry errors in which the same case is accidentally entered more than once.
• Multiple cases share a common primary ID value but have different secondary ID values, such as family
members who all live in the same house.
• Multiple cases represent the same case but with different values for variables other than those that
identify the case, such as multiple purchases made by the same person or company for different
products or at different times.
Identify Duplicate Cases allows you to dene duplicate almost any way that you want and provides some
control over the automatic determination of primary versus duplicate cases.
To Identify and Flag Duplicate Cases
1. From the menus choose:
Data > Identify Duplicate Cases...
2. Select one or more variables that identify matching cases.
3. Select one or more of the options in the Variables to Create group.
Optionally, you can:
4. Select one or more variables to sort cases within groups dened by the selected matching cases
variables. The sort order dened by these variables determines the "rst" and "last" case in each
group. Otherwise, the original le order is used.
5. Automatically lter duplicate cases so that they won't be included in reports, charts, or calculations of
statistics.
Dene matching cases by. Cases are considered duplicates if their values match for all selected
variables. If you want to identify only cases that are a 100% match in all respects, select all of the
variables.
Sort within matching groups by. Cases are automatically sorted by the variables that dene matching
cases. You can select additional sorting variables that will determine the sequential order of cases in each
matching group.
• For each sort variable, you can sort in ascending or descending order.
• If you select multiple sort variables, cases are sorted by each variable within categories of the
preceding variable in the list. For example, if you select date as the rst sorting variable and amount as
the second sorting variable, cases will be sorted by amount within each date.
• Use the up and down arrow buttons to the right of the list to change the sort order of the variables.
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• The sort order determines the "rst" and "last" case within each matching group, which determines the
value of the optional primary indicator variable. For example, if you want to lter out all but the most
recent case in each matching group, you could sort cases within the group in ascending order of a date
variable, which would make the most recent date the last date in the group.
Indicator of primary cases. Creates a variable with a value of 1 for all unique cases and the case
identied as the primary case in each group of matching cases and a value of 0 for the nonprimary
duplicates in each group.
• The primary case can be either the last or rst case in each matching group, as determined by the sort
order within the matching group. If you don't specify any sort variables, the original le order
determines the order of cases within each group.
• You can use the indicator variable as a lter variable to exclude non-primary duplicates from reports
and analyses without deleting those cases from the data le.
Sequential count of matching cases in each group. Creates a variable with a sequential value from 1 to
n for cases in each matching group. The sequence is based on the current order of cases in each group,
which is either the original le order or the order determined by any specied sort variables.
Move matching cases to the top. Sorts the data le so that all groups of matching cases are at the top of
the data le, making it easy to visually inspect the matching cases in the Data Editor.
Display frequencies for created variables. Frequency tables containing counts for each value of the
created variables. For example, for the primary indicator variable, the table would show the number of
cases with a value 0 for that variable, which indicates the number of duplicates, and the number of cases
with a value of 1 for that variable, which indicates the number of unique and primary cases.
Missing values
For numeric variables, the system-missing value is treated like any other value—cases with the system-
missing value for an identier variable are treated as having matching values for that variable. For string
variables, cases with no value for an identier variable are treated as having matching values for that
variable.
Filtered cases
Filter conditions are ignored. Filtered cases are included in the evaluation of duplicate cases. If you want
to exclude cases, dene selection rules with Data > Select Cases and select Delete unselected cases.
Visual Binning
Visual Binning is designed to assist you in the process of creating new variables based on grouping
contiguous values of existing variables into a limited number of distinct categories. You can use Visual
Binning to:
• Create categorical variables from continuous scale variables. For example, you could use a scale
income variable to create a new categorical variable that contains income ranges.
• Collapse a large number of ordinal categories into a smaller set of categories. For example, you could
collapse a rating scale of nine down to three categories representing low, medium, and high.
In the rst step, you:
1. Select the numeric scale and/or ordinal variables for which you want to create new categorical
(binned) variables.
Optionally, you can limit the number of cases to scan. For data les with a large number of cases, limiting
the number of cases scanned can save time, but you should avoid this if possible because it will affect the
distribution of values used in subsequent calculations in Visual Binning.
Note: String variables and nominal numeric variables are not displayed in the source variable list. Visual
Binning requires numeric variables, measured on either a scale or ordinal level, since it assumes that the
data values represent some logical order that can be used to group values in a meaningful fashion. You
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can change the dened measurement level of a variable in Variable View in the Data Editor. See the topic
“Variable measurement level” on page 47 for more information.
To Bin Variables
1. From the menus in the Data Editor window choose:
Transform > Visual Binning...
2. Select the numeric scale and/or ordinal variables for which you want to create new categorical
(binned) variables.
3. Select a variable in the Scanned Variable List.
4. Enter a name for the new binned variable. Variable names must be unique and must follow variable
naming rules. See the topic “Variable names” on page 46 for more information.
5. Dene the binning criteria for the new variable. See the topic “Binning Variables” on page 73 for more
information.
6. Click OK.
Binning Variables
The Visual Binning main dialog box provides the following information for the scanned variables:
Scanned Variable List. Displays the variables you selected in the initial dialog box. You can sort the list
by measurement level (scale or ordinal) or by variable label or name by clicking on the column headings.
Cases Scanned. Indicates the number of cases scanned. All scanned cases without user-missing or
system-missing values for the selected variable are used to generate the distribution of values used in
calculations in Visual Binning, including the histogram displayed in the main dialog box and cutpoints
based on percentiles or standard deviation units.
Missing Values. Indicates the number of scanned cases with user-missing or system-missing values.
Missing values are not included in any of the binned categories. See the topic “User-Missing Values in
Visual Binning” on page 76 for more information.
Current Variable. The name and variable label (if any) for the currently selected variable that will be used
as the basis for the new, binned variable.
Binned Variable. Name and optional variable label for the new, binned variable.
• Name. You must enter a name for the new variable. Variable names must be unique and must follow
variable naming rules. See the topic “Variable names” on page 46 for more information.
• Label. You can enter a descriptive variable label up to 255 characters long. The default variable label is
the variable label (if any) or variable name of the source variable with (Binned) appended to the end of
the label.
Minimum and Maximum. Minimum and maximum values for the currently selected variable, based on the
scanned cases and not including values dened as user-missing.
Nonmissing Values. The histogram displays the distribution of nonmissing values for the currently
selected variable, based on the scanned cases.
• After you dene bins for the new variable, vertical lines on the histogram are displayed to indicate the
cutpoints that dene bins.
• You can click and drag the cutpoint lines to different locations on the histogram, changing the bin
ranges.
• You can remove bins by dragging cutpoint lines off the histogram.
Note: The histogram (displaying nonmissing values), the minimum, and the maximum are based on the
scanned values. If you do not include all cases in the scan, the true distribution may not be accurately
reflected, particularly if the data le has been sorted by the selected variable. If you scan zero cases, no
information about the distribution of values is available.
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Grid. Displays the values that dene the upper endpoints of each bin and optional value labels for each
bin.
• Value. The values that dene the upper endpoints of each bin. You can enter values or use Make
Cutpoints to automatically create bins based on selected criteria. By default, a cutpoint with a value of
HIGH is automatically included. This bin will contain any nonmissing values above the other cutpoints.
The bin dened by the lowest cutpoint will include all nonmissing values lower than or equal to that
value (or simply lower than that value, depending on how you dene upper endpoints).
• Label. Optional, descriptive labels for the values of the new, binned variable. Since the values of the
new variable will simply be sequential integers from 1 to n, labels that describe what the values
represent can be very useful. You can enter labels or use Make Labels to automatically create value
labels.
To Delete a Bin from the Grid
1. Right-click either the Value or Label cell for the bin.
2. From the pop-up menu, select Delete Row.
Note: If you delete the HIGH bin, any cases with values higher than the last specied cutpoint value will
be assigned the system-missing value for the new variable.
To Delete All Labels or Delete All Dened Bins
1. Right-click anywhere in the grid.
2. From the pop-up menu select either Delete All Labels or Delete All Cutpoints.
Upper Endpoints. Controls treatment of upper endpoint values entered in the Value column of the grid.
• Included (<=). Cases with the value specied in the Value cell are included in the binned category. For
example, if you specify values of 25, 50, and 75, cases with a value of exactly 25 will go in the rst bin,
since this will include all cases with values less than or equal to 25.
• Excluded (<). Cases with the value specied in the Value cell are not included in the binned category.
Instead, they are included in the next bin. For example, if you specify values of 25, 50, and 75, cases
with a value of exactly 25 will go in the second bin rather than the rst, since the rst bin will contain
only cases with values less than 25.
Make Cutpoints. Generates binned categories automatically for equal width intervals, intervals with the
same number of cases, or intervals based on standard deviations. This is not available if you scanned zero
cases. See the topic “Automatically Generating Binned Categories” on page 74
for more information.
Make Labels. Generates descriptive labels for the sequential integer values of the new, binned variable,
based on the values in the grid and the specied treatment of upper endpoints (included or excluded).
Reverse scale. By default, values of the new, binned variable are ascending sequential integers from 1 to
n. Reversing the scale makes the values descending sequential integers from n to 1.
Copy Bins. You can copy the binning specications from another variable to the currently selected
variable or from the selected variable to multiple other variables. See the topic “Copying Binned
Categories” on page 75 for more information.
Automatically Generating Binned Categories
The Make Cutpoints dialog box allows you to auto-generate binned categories based on selected criteria.
To Use the Make Cutpoints Dialog Box
1. Select (click) a variable in the Scanned Variable List.
2. Click Make Cutpoints.
3. Select the criteria for generating cutpoints that will dene the binned categories.
4. Click Apply.
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Note: The Make Cutpoints dialog box is not available if you scanned zero cases.
Equal Width Intervals. Generates binned categories of equal width (for example, 1–10, 11–20, and 21–
30) based on any two of the following three criteria:
• First Cutpoint Location. The value that denes the upper end of the lowest binned category (for
example, a value of 10 indicates a range that includes all values up to 10).
• Number of Cutpoints. The number of binned categories is the number of cutpoints plus one. For
example, 9 cutpoints generate 10 binned categories.
• Width. The width of each interval. For example, a value of 10 would bin age in years into 10-year
intervals.
Equal Percentiles Based on Scanned Cases. Generates binned categories with an equal number of
cases in each bin (using the aempirical algorithm for percentiles), based on either of the following
criteria:
• Number of Cutpoints. The number of binned categories is the number of cutpoints plus one. For
example, three cutpoints generate four percentile bins (quartiles), each containing 25% of the cases.
• Width (%). Width of each interval, expressed as a percentage of the total number of cases. For
example, a value of 33.3 would produce three binned categories (two cutpoints), each containing
33.3% of the cases.
If the source variable contains a relatively small number of distinct values or a large number of cases with
the same value, you may get fewer bins than requested. If there are multiple identical values at a
cutpoint, they will all go into the same interval; so the actual percentages may not always be exactly
equal.
Cutpoints at Mean and Selected Standard Deviations Based on Scanned Cases. Generates binned
categories based on the values of the mean and standard deviation of the distribution of the variable.
• If you don't select any of the standard deviation intervals, two binned categories will be created, with
the mean as the cutpoint dividing the bins.
• You can select any combination of standard deviation intervals based on one, two, and/or three
standard deviations. For example, selecting all three would result in eight binned categories--six bins in
one standard deviation intervals and two bins for cases more than three standard deviations above and
below the mean.
In a normal distribution, 68% of the cases fall within one standard deviation of the mean; 95%, within two
standard deviations; and 99%, within three standard deviations. Creating binned categories based on
standard deviations may result in some dened bins outside of the actual data range and even outside of
the range of possible data values (for example, a negative salary range).
Note: Calculations of percentiles and standard deviations are based on the scanned cases. If you limit the
number of cases scanned, the resulting bins may not contain the proportion of cases that you wanted in
those bins, particularly if the data le is sorted by the source variable. For example, if you limit the scan to
the rst 100 cases of a data le with 1000 cases and the data le is sorted in ascending order of age of
respondent, instead of four percentile age bins each containing 25% of the cases, you may nd that the
rst three bins each contain only about 3.3% of the cases, and the last bin contains 90% of the cases.
Copying Binned Categories
When creating binned categories for one or more variables, you can copy the binning specications from
another variable to the currently selected variable or from the selected variable to multiple other
variables.
To Copy Binning Specications
1. Dene binned categories for at least one variable--but do not click OK or Paste.
2. Select (click) a variable in the Scanned Variable List for which you have dened binned categories.
3. Click To Other Variables.
4. Select the variables for which you want to create new variables with the same binned categories.
Chapter 7. Data preparation
75
5. Click Copy.
or
6. Select (click) a variable in the Scanned Variable List to which you want to copy dened binned
categories.
7. Click From Another Variable.
8. Select the variable with the dened binned categories that you want to copy.
9. Click Copy.
If you have specied value labels for the variable from which you are copying the binning specications,
those are also copied.
Note: Once you click OK in the Visual Binning main dialog box to create new binned variables (or close the
dialog box in any other way), you cannot use Visual Binning to copy those binned categories to other
variables.
User-Missing Values in Visual Binning
Values dened as user-missing (values identied as codes for missing data) for the source variable are
not included in the binned categories for the new variable. User-missing values for the source variables
are copied as user-missing values for the new variable, and any dened value labels for missing value
codes are also copied.
If a missing value code conflicts with one of the binned category values for the new variable, the missing
value code for the new variable is recoded to a nonconflicting value by adding 100 to the highest binned
category value. For example, if a value of 1 is dened as user-missing for the source variable and the new
variable will have six binned categories, any cases with a value of 1 for the source variable will have a
value of 106 for the new variable, and 106 will be dened as user-missing. If the user-missing value for
the source variable had a dened value label, that label will be retained as the value label for the recoded
value of the new variable.
Note: If the source variable has a dened range of user-missing values of the form LO-n, where n is a
positive number, the corresponding user-missing values for the new variable will be negative numbers.
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Chapter 8. Data Transformations
Data Transformations
In an ideal situation, your raw data are perfectly suitable for the type of analysis you want to perform, and
any relationships between variables are either conveniently linear or neatly orthogonal. Unfortunately,
this is rarely the case. Preliminary analysis may reveal inconvenient coding schemes or coding errors, or
data transformations may be required in order to expose the true relationship between variables.
You can perform data transformations ranging from simple tasks, such as collapsing categories for
analysis, to more advanced tasks, such as creating new variables based on complex equations and
conditional statements.
Computing Variables
Use the Compute dialog box to compute values for a variable based on numeric transformations of other
variables.
• You can compute values for numeric or string (alphanumeric) variables.
• You can create new variables or replace the values of existing variables. For new variables, you can also
specify the variable type and label.
• You can compute values selectively for subsets of data based on logical conditions.
• You can use a large variety of built-in functions, including arithmetic functions, statistical functions,
distribution functions, and string functions.
To Compute Variables
1. From the menus choose:
Transform > Compute Variable...
2. Type the name of a single target variable. It can be an existing variable or a new variable to be added
to the active dataset.
3. To build an expression, either paste components into the Expression eld or type directly in the
Expression eld.
• You can paste functions or commonly used system variables by selecting a group from the Function
group list and double-clicking the function or variable in the Functions and Special Variables list (or
select the function or variable and click the arrow adjacent to the Function group list). Fill in any
parameters indicated by question marks (only applies to functions). The function group labeled All
provides a listing of all available functions and system variables. A brief description of the currently
selected function or variable is displayed in a reserved area in the dialog box.
• String constants must be enclosed in quotation marks or apostrophes.
• If values contain decimals, a period (.) must be used as the decimal indicator.
• For new string variables, you must also select Type & Label to specify the data type.
Compute Variable: If Cases
The If Cases dialog box allows you to apply data transformations to selected subsets of cases, using
conditional expressions. A conditional expression returns a value of true, false, or missing for each case.
• If the result of a conditional expression is true, the case is included in the selected subset.
• If the result of a conditional expression is false or missing, the case is not included in the selected
subset.
• Most conditional expressions use one or more of the six relational operators (<, >, <=, >=, =, and ~=) on
the calculator pad.
• Conditional expressions can include variable names, constants, arithmetic operators, numeric (and
other) functions, logical variables, and relational operators.
Compute Variable: Type and Label
By default, new computed variables are numeric. To compute a new string variable, you must specify the
data type and width.
Label. Optional, descriptive variable label up to 255 bytes long. You can enter a label or use the rst 110
characters of the compute expression as the label.
Type. Computed variables can be numeric or string (alphanumeric). String variables cannot be used in
calculations.
Functions
Many types of functions are supported, including:
• Arithmetic functions
• Statistical functions
• String functions
• Date and time functions
• Distribution functions
• Random variable functions
• Missing value functions
• Scoring functions
For more information and a detailed description of each function, type functions on the Index tab of the
Help system.
Missing Values in Functions
Functions and simple arithmetic expressions treat missing values in different ways. In the expression:
(var1+var2+var3)/3
the result is missing if a case has a missing value for any of the three variables.
In the expression:
MEAN(var1, var2, var3)
the result is missing only if the case has missing values for all three variables.
For statistical functions, you can specify the minimum number of arguments that must have nonmissing
values. To do so, type a period and the minimum number after the function name, as in:
MEAN.2(var1, var2, var3)
Random Number Generators
The Random Number Generators dialog box allows you to select the random number generator and set
the starting sequence value so you can reproduce a sequence of random numbers.
Active Generator. Two different random number generators are available:
• Version 12 Compatible. The random number generator used in version 12 and previous releases. If you
need to reproduce randomized results generated in previous releases based on a specied seed value,
use this random number generator.
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• Mersenne Twister. A newer random number generator that is more reliable for simulation purposes. If
reproducing randomized results from version 12 or earlier is not an issue, use this random number
generator.
Active Generator Initialization. The random number seed changes each time a random number is
generated for use in transformations (such as random distribution functions), random sampling, or case
weighting. To replicate a sequence of random numbers, set the initialization starting point value prior to
each analysis that uses the random numbers. The value must be a positive integer.
Some procedures, such as Linear Models, have internal random number generators.
To select the random number generator and/or set the initialization value:
1. From the menus choose:
Transform > Random Number Generators
Count Occurrences of Values within Cases
This dialog box creates a variable that counts the occurrences of the same value(s) in a list of variables for
each case. For example, a survey might contain a list of magazines with yes/no check boxes to indicate
which magazines each respondent reads. You could count the number of yes responses for each
respondent to create a new variable that contains the total number of magazines read.
To Count Occurrences of Values within Cases
1. From the menus choose:
Transform > Count Values within Cases...
2. Enter a target variable name.
3. Select two or more variables of the same type (numeric or string).
4. Click Dene Values and specify which value or values should be counted.
Optionally, you can dene a subset of cases for which to count occurrences of values.
Count Values within Cases: Values to Count
The value of the target variable (on the main dialog box) is incremented by 1 each time one of the
selected variables matches a specication in the Values to Count list here. If a case matches several
specications for any variable, the target variable is incremented several times for that variable.
Value specications can include individual values, missing or system-missing values, and ranges. Ranges
include their endpoints and any user-missing values that fall within the range.
Count Occurrences: If Cases
The If Cases dialog box allows you to count occurrences of values for a selected subset of cases, using
conditional expressions. A conditional expression returns a value of true, false, or missing for each case.
Shift Values
Shift Values creates new variables that contain the values of existing variables from preceding or
subsequent cases.
Name. Name for the new variable. This must be a name that does not already exist in the active dataset.
Get value from earlier case (lag). Get the value from a previous case in the active dataset. For example,
with the default number of cases value of 1, each case for the new variable has the value of the original
variable from the case that immediately precedes it.
Get value from following case (lead). Get the value from a subsequent case in the active dataset. For
example, with the default number of cases value of 1, each case for the new variable has the value of the
original variable from the next case.
Chapter 8. Data Transformations
79
Number of cases to shift. Get the value from the nth preceding or subsequent case, where n is the value
specied. The value must be a non-negative integer.
• If split le processing is on, the scope of the shift is limited to each split group. A shift value cannot be
obtained from a case in a preceding or subsequent split group.
• Filter status is ignored.
• The value of the result variable is set to system-missing for the rst or last n cases in the dataset or split
group, where n is the value specied for Number of cases to shift. For example, using the Lag method
with a value of 1 would set the result variable to system-missing for the rst case in the dataset (or rst
case in each split group).
• User-missing values are preserved.
• Dictionary information from the original variable, including dened value labels and user-missing value
assignments, is applied to the new variable. (Note: Custom variable attributes are not included.)
• A variable label is automatically generated for the new variable that describes the shift operation that
created the variable.
To Create a New Variable with Shifted Values
1. From the menus, choose:
Transform > Shift Values
2. Select the variable to use as the source of values for the new variable.
3. Enter a name for the new variable.
4. Select the shift method (lag or lead) and the number of cases to shift.
5. Click Change.
6. Repeat for each new variable you want to create.
Recoding Values
You can modify data values by recoding them. This is particularly useful for collapsing or combining
categories. You can recode the values within existing variables, or you can create new variables based on
the recoded values of existing variables.
Recode into Same Variables
The Recode into Same Variables dialog box allows you to reassign the values of existing variables or
collapse ranges of existing values into new values. For example, you could collapse salaries into salary
range categories.
You can recode numeric and string variables. If you select multiple variables, they must all be the same
type. You cannot recode numeric and string variables together.
To Recode Values of a Variable
1. From the menus choose:
Transform > Recode into Same Variables...
2. Select the variables you want to recode. If you select multiple variables, they must be the same type
(numeric or string).
3. Click Old and New Values and specify how to recode values.
Optionally, you can dene a subset of cases to recode. The If Cases dialog box for doing this is the same
as the one described for Count Occurrences.
Recode into Same Variables: Old and New Values
You can dene values to recode in this dialog box. All value specications must be the same data type
(numeric or string) as the variables selected in the main dialog box.
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Old Value. The value(s) to be recoded. You can recode single values, ranges of values, and missing
values. System-missing values and ranges cannot be selected for string variables because neither
concept applies to string variables. Ranges include their endpoints and any user-missing values that fall
within the range.
• Value. Individual old value to be recoded into a new value. The value must be the same data type
(numeric or string) as the variable(s) being recoded.
• System-missing. Values assigned by the program when values in your data are undened according to
the format type you have specied, when a numeric eld is blank, or when a value resulting from a
transformation command is undened. Numeric system-missing values are displayed as periods. String
variables cannot have system-missing values, since any character is legal in a string variable.
• System- or user-missing. Observations with values that either have been dened as user-missing values
or are unknown and have been assigned the system-missing value, which is indicated with a period (.).
• Range. Inclusive range of values. Not available for string variables. Any user-missing values within the
range are included.
• All other values. Any remaining values not included in one of the specications on the Old-New list. This
appears as ELSE on the Old-New list.
New Value. The single value into which each old value or range of values is recoded. You can enter a
value or assign the system-missing value.
• Value. Value into which one or more old values will be recoded. The value must be the same data type
(numeric or string) as the old value.
• System-missing. Recodes specied old values into the system-missing value. The system-missing value
is not used in calculations, and cases with the system-missing value are excluded from many
procedures. Not available for string variables.
Old–>New. The list of specications that will be used to recode the variable(s). You can add, change, and
remove specications from the list. The list is automatically sorted, based on the old value specication,
using the following order: single values, missing values, ranges, and all other values. If you change a
recode specication on the list, the procedure automatically re-sorts the list, if necessary, to maintain this
order.
Recode into Different Variables
The Recode into Different Variables dialog box allows you to reassign the values of existing variables or
collapse ranges of existing values into new values for a new variable. For example, you could collapse
salaries into a new variable containing salary-range categories.
• You can recode numeric and string variables.
• You can recode numeric variables into string variables and vice versa.
• If you select multiple variables, they must all be the same type. You cannot recode numeric and string
variables together.
To Recode Values of a Variable into a New Variable
1. From the menus choose:
Transform > Recode into Different Variables...
2. Select the variables you want to recode. If you select multiple variables, they must be the same type
(numeric or string).
3. Enter an output (new) variable name for each new variable and click Change.
4. Click Old and New Values and specify how to recode values.
Optionally, you can dene a subset of cases to recode. The If Cases dialog box for doing this is the same
as the one described for Count Occurrences.
Chapter 8. Data Transformations
81
Recode into Different Variables: Old and New Values
You can dene values to recode in this dialog box.
Old Value. The value(s) to be recoded. You can recode single values, ranges of values, and missing
values. System-missing values and ranges cannot be selected for string variables because neither
concept applies to string variables. Old values must be the same data type (numeric or string) as the
original variable. Ranges include their endpoints and any user-missing values that fall within the range.
• Value. Individual old value to be recoded into a new value. The value must be the same data type
(numeric or string) as the variable(s) being recoded.
• System-missing. Values assigned by the program when values in your data are undened according to
the format type you have specied, when a numeric eld is blank, or when a value resulting from a
transformation command is undened. Numeric system-missing values are displayed as periods. String
variables cannot have system-missing values, since any character is legal in a string variable.
• System- or user-missing. Observations with values that either have been dened as user-missing values
or are unknown and have been assigned the system-missing value, which is indicated with a period (.).
• Range. Inclusive range of values. Not available for string variables. Any user-missing values within the
range are included.
• All other values. Any remaining values not included in one of the specications on the Old-New list. This
appears as ELSE on the Old-New list.
New Value. The single value into which each old value or range of values is recoded. New values can be
numeric or string.
• Value. Value into which one or more old values will be recoded. The value must be the same data type
(numeric or string) as the old value.
• System-missing. Recodes specied old values into the system-missing value. The system-missing value
is not used in calculations, and cases with the system-missing value are excluded from many
procedures. Not available for string variables.
• Copy old values. Retains the old value. If some values don't require recoding, use this to include the old
values. Any old values that are not specied are not included in the new variable, and cases with those
values will be assigned the system-missing value for the new variable.
Output variables are strings. Denes the new, recoded variable as a string (alphanumeric) variable. The
old variable can be numeric or string.
Convert numeric strings to numbers. Converts string values containing numbers to numeric values. Strings
containing anything other than numbers and an optional sign (+ or -) are assigned the system-missing
value.
Old–>New. The list of specications that will be used to recode the variable(s). You can add, change, and
remove specications from the list. The list is automatically sorted, based on the old value specication,
using the following order: single values, missing values, ranges, and all other values. If you change a
recode specication on the list, the procedure automatically re-sorts the list, if necessary, to maintain this
order.
Automatic Recode
The Automatic Recode dialog box allows you to convert string and numeric values into consecutive
integers. When category codes are not sequential, the resulting empty cells reduce performance and
increase memory requirements for many procedures. Additionally, some procedures cannot use string
variables, and some require consecutive integer values for factor levels.
• The new variable(s) created by Automatic Recode retain any dened variable and value labels from the
old variable. For any values without a dened value label, the original value is used as the label for the
recoded value. A table displays the old and new values and value labels.
• String values are recoded in alphabetical order, with uppercase letters preceding their lowercase
counterparts.
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• Missing values are recoded into missing values higher than any nonmissing values, with their order
preserved. For example, if the original variable has 10 nonmissing values, the lowest missing value
would be recoded to 11, and the value 11 would be a missing value for the new variable.
Use the same recoding scheme for all variables. This option allows you to apply a single autorecoding
scheme to all the selected variables, yielding a consistent coding scheme for all the new variables.
If you select this option, the following rules and limitations apply:
• All variables must be of the same type (numeric or string).
• All observed values for all selected variables are used to create a sorted order of values to recode into
sequential integers.
• User-missing values for the new variables are based on the rst variable in the list with dened user-
missing values. All other values from other original variables, except for system-missing, are treated as
valid.
Treat blank string values as user-missing. For string variables, blank or null values are not treated as
system-missing. This option will autorecode blank strings into a user-missing value higher than the highest
nonmissing value.
Templates
You can save the autorecoding scheme in a template le and then apply it to other variables and other
data les.
For example, you may have a large number of alphanumeric product codes that you autorecode into
integers every month, but some months new product codes are added that change the original
autorecoding scheme. If you save the original scheme in a template and then apply it to the new data that
contain the new set of codes, any new codes encountered in the data are autorecoded into values higher
than the last value in the template, preserving the original autorecode scheme of the original product
codes.
Save template as. Saves the autorecode scheme for the selected variables in an external template le.
• The template contains information that maps the original nonmissing values to the recoded values.
• Only information for nonmissing values is saved in the template. User-missing value information is not
retained.
• If you have selected multiple variables for recoding but you have not selected to use the same
autorecoding scheme for all variables or you are not applying an existing template as part of the
autorecoding, the template will be based on the rst variable in the list.
• If you have selected multiple variables for recoding and you have also selected Use the same recoding
scheme for all variables and/or you have selected Apply template, then the template will contain the
combined autorecoding scheme for all variables.
Apply template from. Applies a previously saved autorecode template to variables selected for recoding,
appending any additional values found in the variables to the end of the scheme and preserving the
relationship between the original and autorecoded values stored in the saved scheme.
• All variables selected for recoding must be the same type (numeric or string), and that type must match
the type dened in the template.
• Templates do not contain any information on user-missing values. User-missing values for the target
variables are based on the rst variable in the original variable list with dened user-missing values. All
other values from other original variables, except for system-missing, are treated as valid.
• Value mappings from the template are applied rst. All remaining values are recoded into values higher
than the last value in the template, with user-missing values (based on the rst variable in the list with
dened user-missing values) recoded into values higher than the last valid value.
• If you have selected multiple variables for autorecoding, the template is applied rst, followed by a
common, combined autorecoding for all additional values found in the selected variables, resulting in a
single, common autorecoding scheme for all selected variables.
To Recode String or Numeric Values into Consecutive Integers
Chapter 8. Data Transformations
83
1. From the menus choose:
Transform > Automatic Recode...
2. Select one or more variables to recode.
3. For each selected variable, enter a name for the new variable and click New Name.
Rank Cases
The Rank Cases dialog box allows you to create new variables containing ranks, normal and Savage
scores, and percentile values for numeric variables.
New variable names and descriptive variable labels are automatically generated, based on the original
variable name and the selected measure(s). A summary table lists the original variables, the new
variables, and the variable labels. (Note: The automatically generated new variable names are limited to a
maximum length of 8 bytes.)
Optionally, you can:
• Rank cases in ascending or descending order.
• Organize rankings into subgroups by selecting one or more grouping variables for the By list. Ranks are
computed within each group. Groups are dened by the combination of values of the grouping variables.
For example, if you select gender and minority as grouping variables, ranks are computed for each
combination of gender and minority.
To Rank Cases
1. From the menus choose:
Transform > Rank Cases...
2. Select one or more variables to rank. You can rank only numeric variables.
Optionally, you can rank cases in ascending or descending order and organize ranks into subgroups.
Rank Cases: Types
You can select multiple ranking methods. A separate ranking variable is created for each method. Ranking
methods include simple ranks, Savage scores, fractional ranks, and percentiles. You can also create
rankings based on proportion estimates and normal scores.
Rank. Simple rank. The value of the new variable equals its rank.
Savage score. The new variable contains Savage scores based on an exponential distribution.
Fractional rank. The value of the new variable equals rank divided by the sum of the weights of the
nonmissing cases.
Fractional rank as percent. Each rank is divided by the number of cases with valid values and multiplied by
100.
Sum of case weights. The value of the new variable equals the sum of case weights. The new variable is a
constant for all cases in the same group.
Ntiles. Ranks are based on percentile groups, with each group containing approximately the same number
of cases. For example, 4 Ntiles would assign a rank of 1 to cases below the 25th percentile, 2 to cases
between the 25th and 50th percentile, 3 to cases between the 50th and 75th percentile, and 4 to cases
above the 75th percentile.
Proportion estimates. Estimates of the cumulative proportion of the distribution corresponding to a
particular rank.
Normal scores. The z scores corresponding to the estimated cumulative proportion.
Proportion Estimation Formula. For proportion estimates and normal scores, you can select the
proportion estimation formula: Blom, Tukey, Rankit, or Van der Waerden.
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• Blom. Creates new ranking variable based on proportion estimates that uses the formula (r-3/8) / (w
+1/4), where w is the sum of the case weights and r is the rank.
• Tukey. Uses the formula (r-1/3) / (w+1/3), where r is the rank and w is the sum of the case weights.
• Rankit. Uses the formula (r-1/2) / w, where w is the number of observations and r is the rank, ranging
from 1 to w.
• Van der Waerden. Van der Waerden's transformation, dened by the formula r/(w+1), where w is the
sum of the case weights and r is the rank, ranging from 1 to w.
Rank Cases: Ties
This dialog box controls the method for assigning rankings to cases with the same value on the original
variable.
The following table shows how the different methods assign ranks to tied values:
Table 7. Ranking methods and results
Value Mean Low High Sequential
10 1 1 1 1
15 3 2 4 2
15 3 2 4 2
15 3 2 4 2
16 5 5 5 3
20 6 6 6 4
Date and Time Wizard
The Date and Time Wizard simplies a number of common tasks associated with date and time variables.
To Use the Date and Time Wizard
1. From the menus choose:
Transform > Date and Time Wizard...
2. Select the task you want to accomplish and follow the steps to dene the task.
• Learn how dates and times are represented. This choice leads to a screen that provides a brief
overview of date/time variables in IBM SPSS Statistics. By clicking on the Help button, it also provides a
link to more detailed information.
• Create a date/time variable from a string containing a date or time. Use this option to create a date/
time variable from a string variable. For example, you have a string variable representing dates in the
form mm/dd/yyyy and want to create a date/time variable from this.
• Create a date/time variable from variables holding parts of dates or times. This choice allows you to
construct a date/time variable from a set of existing variables. For example, you have a variable that
represents the month (as an integer), a second that represents the day of the month, and a third that
represents the year. You can combine these three variables into a single date/time variable.
• Calculate with dates and times. Use this option to add or subtract values from date/time variables. For
example, you can calculate the duration of a process by subtracting a variable representing the start
time of the process from another variable representing the end time of the process.
• Extract a part of a date or time variable. This option allows you to extract part of a date/time variable,
such as the day of the month from a date/time variable, which has the form mm/dd/yyyy.
• Assign periodicity to a dataset. This choice takes you to the Dene Dates dialog box, used to create
date/time variables that consist of a set of sequential dates. This feature is typically used to associate
dates with time series data.
Chapter 8. Data Transformations
85
Note: Tasks are disabled when the dataset lacks the types of variables required to accomplish the task.
For instance, if the dataset contains no string variables, then the task to create a date/time variable from a
string does not apply and is disabled.
Dates and Times in IBM SPSS Statistics
Variables that represent dates and times in IBM SPSS Statistics have a variable type of numeric, with
display formats that correspond to the specic date/time formats. These variables are generally referred
to as date/time variables. Date/time variables that actually represent dates are distinguished from those
that represent a time duration that is independent of any date, such as 20 hours, 10 minutes, and 15
seconds. The latter are referred to as duration variables and the former as date or date/time variables. For
a complete list of display formats, see "Date and Time" in the "Universals" section of the Command
Syntax Reference.
Date and date/time variables. Date variables have a format representing a date, such as mm/dd/yyyy.
Date/time variables have a format representing a date and time, such as dd-mmm-yyyy hh:mm:ss.
Internally, date and date/time variables are stored as the number of seconds from October 14, 1582.
Date and date/time variables are sometimes referred to as date-format variables.
• Both two- and four-digit year specications are recognized. By default, two-digit years represent a
range beginning 69 years prior to the current date and ending 30 years after the current date. This range
is determined by your Options settings and is congurable (from the Edit menu, choose Options and
click the Data tab).
• Dashes, periods, commas, slashes, or blanks can be used as delimiters in day-month-year formats.
• Months can be represented in digits, Roman numerals, or three-character abbreviations, and they can
be fully spelled out. Three-letter abbreviations and fully spelled-out month names must be in English;
month names in other languages are not recognized.
Duration variables. Duration variables have a format representing a time duration, such as hh:mm. They
are stored internally as seconds without reference to a particular date.
• In time specications (applies to date/time and duration variables), colons can be used as delimiters
between hours, minutes, and seconds. Hours and minutes are required, but seconds are optional. A
period is required to separate seconds from fractional seconds. Hours can be of unlimited magnitude,
but the maximum value for minutes is 59 and for seconds is 59.999....
Current date and time. The system variable $TIME holds the current date and time. It represents the
number of seconds from October 14, 1582, to the date and time when the transformation command that
uses it is executed.
Create a Date/Time Variable from a String
To create a date/time variable from a string variable:
1. Select Create a date/time variable from a string containing a date or time on the introduction
screen of the Date and Time Wizard.
Select String Variable to Convert to Date/Time Variable
1. Select the string variable to convert in the Variables list. Note that the list displays only string
variables.
2. Select the pattern from the Patterns list that matches how dates are represented by the string
variable. The Sample Values list displays actual values of the selected variable in the data le. Values
of the string variable that do not t the selected pattern result in a value of system-missing for the new
variable.
Specify Result of Converting String Variable to Date/Time Variable
1. Enter a name for the Result Variable. This cannot be the name of an existing variable.
Optionally, you can:
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• Select a date/time format for the new variable from the Output Format list.
• Assign a descriptive variable label to the new variable.
Create a Date/Time Variable from a Set of Variables
To merge a set of existing variables into a single date/time variable:
1. Select Create a date/time variable from variables holding parts of dates or times on the
introduction screen of the Date and Time Wizard.
Select Variables to Merge into Single Date/Time Variable
1. Select the variables that represent the different parts of the date/time.
• Some combinations of selections are not allowed. For instance, creating a date/time variable from Year
and Day of Month is invalid because once Year is chosen, a full date is required.
• You cannot use an existing date/time variable as one of the parts of the nal date/time variable you’re
creating. Variables that make up the parts of the new date/time variable must be integers. The
exception is the allowed use of an existing date/time variable as the Seconds part of the new variable.
Since fractional seconds are allowed, the variable used for Seconds is not required to be an integer.
• Values, for any part of the new variable, that are not within the allowed range result in a value of
system-missing for the new variable. For instance, if you inadvertently use a variable representing day
of month for Month, any cases with day of month values in the range 14–31 will be assigned the
system-missing value for the new variable since the valid range for months in IBM SPSS Statistics is 1–
13.
Specify Date/Time Variable Created by Merging Variables
1. Enter a name for the Result Variable. This cannot be the name of an existing variable.
2. Select a date/time format from the Output Format list.
Optionally, you can:
• Assign a descriptive variable label to the new variable.
Add or Subtract Values from Date/Time Variables
To add or subtract values from date/time variables:
1. Select Calculate with dates and times on the introduction screen of the Date and Time Wizard.
Select Type of Calculation to Perform with Date/Time Variables
• Add or subtract a duration from a date. Use this option to add to or subtract from a date-format
variable. You can add or subtract durations that are xed values, such as 10 days, or the values from a
numeric variable, such as a variable that represents years.
• Calculate the number of time units between two dates. Use this option to obtain the difference
between two dates as measured in a chosen unit. For example, you can obtain the number of years or
the number of days separating two dates.
• Subtract two durations. Use this option to obtain the difference between two variables that have
formats of durations, such as hh:mm or hh:mm:ss.
Note: Tasks are disabled when the dataset lacks the types of variables required to accomplish the task.
For instance, if the dataset lacks two variables with formats of durations, then the task to subtract two
durations does not apply and is disabled.
Add or Subtract a Duration from a Date
To add or subtract a duration from a date-format variable:
1. Select Add or subtract a duration from a date on the screen of the Date and Time Wizard labeled Do
Calculations on Dates.
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87
Select Date/Time Variable and Duration to Add or Subtract
1. Select a date (or time) variable.
2. Select a duration variable or enter a value for Duration Constant. Variables used for durations cannot
be date or date/time variables. They can be duration variables or simple numeric variables.
3. Select the unit that the duration represents from the drop-down list. Select Duration if using a variable
and the variable is in the form of a duration, such as hh:mm or hh:mm:ss.
Specify Result of Adding or Subtracting a Duration from a Date/Time Variable
1. Enter a name for Result Variable. This cannot be the name of an existing variable.
Optionally, you can:
• Assign a descriptive variable label to the new variable.
Subtract Date-Format Variables
To subtract two date-format variables:
1. Select Calculate the number of time units between two dates on the screen of the Date and Time
Wizard labeled Do Calculations on Dates.
Select Date-Format Variables to Subtract
1. Select the variables to subtract.
2. Select the unit for the result from the drop-down list.
3. Select how the result should be calculated (Result Treatment).
Result Treatment
The following options are available for how the result is calculated:
• Truncate to integer. Any fractional portion of the result is ignored. For example, subtracting
10/28/2006 from 10/21/2007 returns a result of 0 for years and 11 for months.
• Round to integer. The result is rounded to the closest integer. For example, subtracting 10/28/2006
from 10/21/2007 returns a result of 1 for years and 12 for months.
• Retain fractional part. The complete value is retained; no rounding or truncation is applied. For
example, subtracting 10/28/2006 from 10/21/2007 returns a result of 0.98 for years and 11.76 for
months.
For rounding and fractional retention, the result for years is based on average number of days in a year
(365.25), and the result for months is based on the average number of days in a month (30.4375). For
example, subtracting 2/1/2007 from 3/1/2007 (m/d/y format) returns a fractional result of 0.92 months,
whereas subtracting 3/1/2007 from 2/1/2007 returns a fractional difference of 1.02 months. This also
affects values calculated on time spans that include leap years. For example, subtracting 2/1/2008 from
3/1/2008 returns a fractional difference of 0.95 months, compared to 0.92 for the same time span in a
non-leap year.
Table 8. Date difference for years
Date 1 Date 2 Truncate Round Fraction
10/21/2006 10/28/2007 1 1 1.02
10/28/2006 10/21/2007 0 1 .98
2/1/2007 3/1/2007 0 0 .08
2/1/2008 3/1/2008 0 0 .08
3/1/2007 4/1/2007 0 0 .08
4/1/2007 5/1/2007 0 0 .08
88 IBM SPSS Statistics 27 Core System User's Guide
Table 9. Date difference for months
Date 1 Date 2 Truncate Round Fraction
10/21/2006 10/28/2007 12 12 12.22
10/28/2006 10/21/2007 11 12 11.76
2/1/2007 3/1/2007 1 1 .92
2/1/2008 3/1/2008 1 1 .95
3/1/2007 4/1/2007 1 1 1.02
4/1/2007 5/1/2007 1 1 .99
Specify Result of Subtracting Two Date-Format Variables
1. Enter a name for Result Variable. This cannot be the name of an existing variable.
Optionally, you can:
• Assign a descriptive variable label to the new variable.
Subtract Duration Variables
To subtract two duration variables:
1. Select Subtract two durations on the screen of the Date and Time Wizard labeled Do Calculations on
Dates.
Select Duration Variables to Subtract
1. Select the variables to subtract.
Specify Result of Subtracting Two Duration Variables
1. Enter a name for Result Variable. This cannot be the name of an existing variable.
2. Select a duration format from the Output Format list.
Optionally, you can:
• Assign a descriptive variable label to the new variable.
Extract Part of a Date/Time Variable
To extract a component--such as the year--from a date/time variable:
1. Select Extract a part of a date or time variable on the introduction screen of the Date and Time
Wizard.
Select Component to Extract from Date/Time Variable
1. Select the variable containing the date or time part to extract.
2. Select the part of the variable to extract, from the drop-down list. You can extract information from
dates that is not explicitly part of the display date, such as day of the week.
Specify Result of Extracting Component from Date/Time Variable
1. Enter a name for Result Variable. This cannot be the name of an existing variable.
2. If you're extracting the date or time part of a date/time variable, then you must select a format from
the Output Format list. In cases where the output format is not required, the Output Format list will be
disabled.
Optionally, you can:
• Assign a descriptive variable label to the new variable.
Chapter 8. Data Transformations
89
Time Series Data Transformations
Several data transformations that are useful in time series analysis are provided:
• Generate date variables to establish periodicity and to distinguish between historical, validation, and
forecasting periods.
• Create new time series variables as functions of existing time series variables.
• Replace system- and user-missing values with estimates based on one of several methods.
A time series is obtained by measuring a variable (or set of variables) regularly over a period of time. Time
series data transformations assume a data le structure in which each case (row) represents a set of
observations at a different time, and the length of time between cases is uniform.
Dene Dates
The Dene Dates dialog box allows you to generate date variables that can be used to establish the
periodicity of a time series and to label output from time series analysis.
Cases Are. Denes the time interval used to generate dates.
• Not dated removes any previously dened date variables. Any variables with the following names are
deleted: year_, quarter_, month_, week_, day_, hour_, minute_, second_, and date_.
• Custom indicates the presence of custom date variables created with command syntax (for example, a
four-day workweek). This item merely reflects the current state of the active dataset. Selecting it from
the list has no effect.
First Case Is. Denes the starting date value, which is assigned to the rst case. Sequential values, based
on the time interval, are assigned to subsequent cases.
Periodicity at higher level. Indicates the repetitive cyclical variation, such as the number of months in a
year or the number of days in a week. The value displayed indicates the maximum value you can enter.
For hours, minutes, and seconds the maximum is the displayed value minus one.
A new numeric variable is created for each component that is used to dene the date. The new variable
names end with an underscore. A descriptive string variable, date_, is also created from the components.
For example, if you selected Weeks, days, hours, four new variables are created: week_, day_, hour_,
and date_.
If date variables have already been dened, they are replaced when you dene new date variables that
will have the same names as the existing date variables.
To Dene Dates for Time Series Data
1. From the menus choose:
Data > Dene Dates...
2. Select a time interval from the Cases Are list.
3. Enter the value(s) that dene the starting date for First Case Is, which determines the date assigned to
the rst case.
Date Variables versus Date Format Variables
Date variables created with Dene Dates should not be confused with date format variables dened in the
Variable View of the Data Editor. Date variables are used to establish periodicity for time series data. Date
format variables represent dates and/or times displayed in various date/time formats. Date variables are
simple integers representing the number of days, weeks, hours, and so on, from a user-specied starting
point. Internally, most date format variables are stored as the number of seconds from October 14, 1582.
Create Time Series
The Create Time Series dialog box allows you to create new variables based on functions of existing
numeric time series variables. These transformed values are useful in many time series analysis
procedures.
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Default new variable names are the rst six characters of the existing variable used to create it, followed
by an underscore and a sequential number. For example, for the variable price, the new variable name
would be price_1. The new variables retain any dened value labels from the original variables.
Available functions for creating time series variables include differences, moving averages, running
medians, lag, and lead functions.
To Create New Time Series Variables
1. From the menus choose:
Transform > Create Time Series...
2. Select the time series function that you want to use to transform the original variable(s).
3. Select the variable(s) from which you want to create new time series variables. Only numeric variables
can be used.
Optionally, you can:
• Enter variable names to override the default new variable names.
• Change the function for a selected variable.
Time Series Transformation Functions
Difference. Nonseasonal difference between successive values in the series. The order is the number of
previous values used to calculate the difference. Because one observation is lost for each order of
difference, system-missing values appear at the beginning of the series. For example, if the difference
order is 2, the rst two cases will have the system-missing value for the new variable.
Seasonal difference. Difference between series values a constant span apart. The span is based on the
currently dened periodicity. To compute seasonal differences, you must have dened date variables
(Data menu, Dene Dates) that include a periodic component (such as months of the year). The order is
the number of seasonal periods used to compute the difference. The number of cases with the system-
missing value at the beginning of the series is equal to the periodicity multiplied by the order. For
example, if the current periodicity is 12 and the order is 2, the rst 24 cases will have the system-missing
value for the new variable.
Centered moving average. Average of a span of series values surrounding and including the current
value. The span is the number of series values used to compute the average. If the span is even, the
moving average is computed by averaging each pair of uncentered means. The number of cases with the
system-missing value at the beginning and at the end of the series for a span of n is equal to n/2 for even
span values and (n–1)/2 for odd span values. For example, if the span is 5, the number of cases with the
system-missing value at the beginning and at the end of the series is 2.
Prior moving average. Average of the span of series values preceding the current value. The span is the
number of preceding series values used to compute the average. The number of cases with the system-
missing value at the beginning of the series is equal to the span value.
Running medians. Median of a span of series values surrounding and including the current value. The
span is the number of series values used to compute the median. If the span is even, the median is
computed by averaging each pair of uncentered medians. The number of cases with the system-missing
value at the beginning and at the end of the series for a span of n is equal to n/2 for even span values and
(n–1)/2 for odd span values. For example, if the span is 5, the number of cases with the system-missing
value at the beginning and at the end of the series is 2.
Cumulative sum. Cumulative sum of series values up to and including the current value.
Lag. Value of a previous case, based on the specied lag order. The order is the number of cases prior to
the current case from which the value is obtained. The number of cases with the system-missing value at
the beginning of the series is equal to the order value.
Lead. Value of a subsequent case, based on the specied lead order. The order is the number of cases
after the current case from which the value is obtained. The number of cases with the system-missing
value at the end of the series is equal to the order value.
Chapter 8. Data Transformations
91
Smoothing. New series values based on a compound data smoother. The smoother starts with a running
median of 4, which is centered by a running median of 2. It then resmoothes these values by applying a
running median of 5, a running median of 3, and hanning (running weighted averages). Residuals are
computed by subtracting the smoothed series from the original series. This whole process is then
repeated on the computed residuals. Finally, the smoothed residuals are computed by subtracting the
smoothed values obtained the rst time through the process. This is sometimes referred to as T4253H
smoothing.
Replace Missing Values
Missing observations can be problematic in analysis, and some time series measures cannot be computed
if there are missing values in the series. Sometimes the value for a particular observation is simply not
known. In addition, missing data can result from any of the following:
• Each degree of differencing reduces the length of a series by 1.
• Each degree of seasonal differencing reduces the length of a series by one season.
• If you create new series that contain forecasts beyond the end of the existing series (by clicking a Save
button and making suitable choices), the original series and the generated residual series will have
missing data for the new observations.
• Some transformations (for example, the log transformation) produce missing data for certain values of
the original series.
Missing data at the beginning or end of a series pose no particular problem; they simply shorten the
useful length of the series. Gaps in the middle of a series (embedded missing data) can be a much more
serious problem. The extent of the problem depends on the analytical procedure you are using.
The Replace Missing Values dialog box allows you to create new time series variables from existing ones,
replacing missing values with estimates computed with one of several methods. Default new variable
names are the rst six characters of the existing variable used to create it, followed by an underscore and
a sequential number. For example, for the variable price, the new variable name would be price_1. The
new variables retain any dened value labels from the original variables.
To Replace Missing Values for Time Series Variables
1. From the menus choose:
Transform > Replace Missing Values...
2. Select the estimation method you want to use to replace missing values.
3. Select the variable(s) for which you want to replace missing values.
Optionally, you can:
• Enter variable names to override the default new variable names.
• Change the estimation method for a selected variable.
Estimation Methods for Replacing Missing Values
Series mean. Replaces missing values with the mean for the entire series.
Mean of nearby points. Replaces missing values with the mean of valid surrounding values. The span of
nearby points is the number of valid values above and below the missing value used to compute the
mean.
Median of nearby points. Replaces missing values with the median of valid surrounding values. The span
of nearby points is the number of valid values above and below the missing value used to compute the
median.
Linear interpolation. Replaces missing values using a linear interpolation. The last valid value before the
missing value and the rst valid value after the missing value are used for the interpolation. If the rst or
last case in the series has a missing value, the missing value is not replaced.
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Linear trend at point. Replaces missing values with the linear trend for that point. The existing series is
regressed on an index variable scaled 1 to n. Missing values are replaced with their predicted values.
Chapter 8. Data Transformations 93
94 IBM SPSS Statistics 27 Core System User's Guide
Chapter 9. File handling and le transformations
File handling and le transformations
Data les are not always organized in the ideal form for your specic needs. You may want to combine
data les, sort the data in a different order, select a subset of cases, or change the unit of analysis by
grouping cases together. A wide range of le transformation capabilities is available, including the ability
to:
Sort data. You can sort cases based on the value of one or more variables.
Transpose cases and variables. The IBM SPSS Statistics data le format reads rows as cases and
columns as variables. For data les in which this order is reversed, you can switch the rows and columns
and read the data in the correct format.
Merge les. You can merge two or more data les. You can combine les with the same variables but
different cases or the same cases but different variables.
Select subsets of cases. You can restrict your analysis to a subset of cases or perform simultaneous
analyses on different subsets.
Aggregate data. You can change the unit of analysis by aggregating cases based on the value of one or
more grouping variables.
Weight data. You can weight cases for analysis based on the value of a weight variable.
Restructure data. You can restructure data to create a single case (record) from multiple cases or create
multiple cases from a single case.
Sort cases
This dialog box sorts cases (rows) of the active dataset based on the values of one or more sorting
variables. You can sort cases in ascending or descending order.
• If you select multiple sort variables, cases are sorted by each variable within categories of the
preceding variable on the Sort list. For example, if you select gender as the rst sorting variable and
minority as the second sorting variable, cases will be sorted by minority classication within each
gender category.
• The sort sequence is based on the locale-dened order (and is not necessarily the same as the
numerical order of the character codes). The default locale is the operating system locale. You can
control the locale with the Language setting on the General tab of the Options dialog box (Edit menu).
To Sort Cases
1. From the menus choose:
Data > Sort Cases...
2. Select one or more sorting variables.
Optionally, you can do the following:
Index the saved le. Indexing table lookup les can improve performance when merging data les
with STAR JOIN.
Save the sorted le. You can save the sorted le, with the option of saving it as encrypted. Encryption
allows you to protect condential information stored in the le. Once encrypted, the le can only be
opened by providing the password assigned to the le.
To save the sorted le with encryption:
3. Select Save le with sorted data and click File.
4. Select Encrypt le with password in the Save Sorted Data As dialog box.
5. Click Save.
6. In the Encrypt File dialog box, provide a password and re-enter it in the Conrm password text box.
Passwords are limited to 10 characters and are case-sensitive.
Warning: Passwords cannot be recovered if they are lost. If the password is lost the le cannot be
opened.
Creating strong passwords
• Use eight or more characters.
• Include numbers, symbols and even punctuation in your password.
• Avoid sequences of numbers or characters, such as "123" and "abc", and avoid repetition, such as
"111aaa".
• Do not create passwords that use personal information such as birthdays or nicknames.
• Periodically change the password.
Note: Storing encrypted les to an IBM SPSS Collaboration and Deployment Services Repository is not
supported.
Note: Encrypted data les and output documents cannot be opened in versions of IBM SPSS Statistics
prior to version 21. Encrypted syntax les cannot be opened in versions prior to version 22.
Sort variables
You can sort the variables in the active dataset based on the values of any of the variable attributes (e.g.,
variable name, data type, measurement level), including custom variable attributes.
• Values can be sorted in ascending or descending order.
• You can save the original (pre-sorted) variable order in a custom variable attribute.
• Sorting by values of custom variable attributes is limited to custom variable attributes that are currently
visible in Variable View.
For more information on custom variable attributes, see “Custom Variable Attributes” on page 51.
To Sort Variables
In Variable View of the Data Editor:
1. Right-click the attribute column heading and from the pop-up menu choose Sort Ascending or Sort
Descending.
or
2. From the menus in Variable View or Data View, choose:
Data > Sort Variables
3. Select the attribute you want to use to sort variables.
4. Select the sort order (ascending or descending).
• The list of variable attributes matches the attribute column names displayed in Variable View of the
Data Editor.
• You can save the original (pre-sorted) variable order in a custom variable attribute. For each variable,
the value of the attribute is an integer value indicating its position prior to sorting; so by sorting
variables based on the value of that custom attribute you can restore the original variable order.
Transpose
Transpose creates a new data le in which the rows and columns in the original data le are transposed
so that cases (rows) become variables and variables (columns) become cases. Transpose automatically
creates new variable names and displays a list of the new variable names.
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• A new string variable that contains the original variable name, case_lbl, is automatically created.
• If the active dataset contains an ID or name variable with unique values, you can use it as the name
variable, and its values will be used as variable names in the transposed data le. If it is a numeric
variable, the variable names start with the letter V, followed by the numeric value.
• User-missing values are converted to the system-missing value in the transposed data le. To retain
any of these values, change the denition of missing values in the Variable View in the Data Editor.
To Transpose Variables and Cases
1. From the menus choose:
Data > Transpose...
2. Select one or more variables to transpose into cases.
Merging Data Files
You can merge data from two les in two different ways. You can:
• Merge the active dataset with another open dataset or IBM SPSS Statistics data le containing the same
variables but different cases.
• Merge the active dataset with another open dataset or IBM SPSS Statistics data le containing the same
cases but different variables.
To Merge Files
1. From the menus choose:
Data > Merge Files
2. Select Add Cases or Add Variables.
Add Cases
Add Cases merges the active dataset with a second dataset or external IBM SPSS Statistics data le that
contains the same variables (columns) but different cases (rows). For example, you might record the
same information for customers in two different sales regions and maintain the data for each region in
separate les. The second dataset can be an external IBM SPSS Statistics data le or a dataset available
in the current session.
Unpaired Variables. Variables to be excluded from the new, merged data le. Variables from the active
dataset are identied with an asterisk (*). Variables from the other dataset are identied with a plus sign
(+). By default, this list contains:
• Variables from either data le that do not match a variable name in the other le. You can create pairs
from unpaired variables and include them in the new, merged le.
• Variables dened as numeric data in one le and string data in the other le. Numeric variables cannot
be merged with string variables.
• String variables of unequal width. The dened width of a string variable must be the same in both data
les.
Variables in New Active Dataset. Variables to be included in the new, merged data le. By default, all of
the variables that match both the name and the data type (numeric or string) are included on the list.
• You can remove variables from the list if you do not want them to be included in the merged le.
• Any unpaired variables included in the merged le will contain missing data for cases from the le that
does not contain that variable.
Indicate case source as variable. Indicates the source data le for each case. This variable has a value of
0 for cases from the active dataset and a value of 1 for cases from the external data le.
1. Open at least one of the data les that you want to merge. If you have multiple datasets open, make
one of the datasets that you want to merge the active dataset. The cases from this le will appear rst
in the new, merged data le.
Chapter 9. File handling and
le transformations 97
2. From the menus choose:
Data > Merge Files > Add Cases...
3. Select the dataset or external IBM SPSS Statistics data le to merge with the active dataset.
4. Remove any variables that you do not want from the Variables in New Active Dataset list.
5. Add any variable pairs from the Unpaired Variables list that represent the same information recorded
under different variable names in the two les. For example, date of birth might have the variable
name brthdate in one le and datebrth in the other le.
To Select a Pair of Unpaired Variables
1. Click one of the variables on the Unpaired Variables list.
2. Ctrl-click the other variable on the list. (Press the Ctrl key and click the left mouse button at the same
time.)
3. Click Pair to move the variable pair to the Variables in New Active Dataset list. (The variable name
from the active dataset is used as the variable name in the merged le.)
Add Cases: Rename
You can rename variables from either the active dataset or the other dataset before moving them from
the unpaired list to the list of variables to be included in the merged data le. Renaming variables enables
you to:
• Use the variable name from the other dataset rather than the name from the active dataset for variable
pairs.
• Include two variables with the same name but of unmatched types or different string widths. For
example, to include both the numeric variable sex from the active dataset and the string variable sex
from the other dataset, one of them must be renamed rst.
Add Cases: Dictionary Information
Any existing dictionary information (variable and value labels, user-missing values, display formats) in the
active dataset is applied to the merged data le.
• If any dictionary information for a variable is undened in the active dataset, dictionary information
from the other dataset is used.
• If the active dataset contains any dened value labels or user-missing values for a variable, any
additional value labels or user-missing values for that variable in the other dataset are ignored.
Merging More Than Two Data Sources
Using command syntax, you can merge up to 50 datasets and/or data les. For more information, see the
ADD FILES command in the Command Syntax Reference (available from the Help menu).
Add Variables
Add Variables merges the active data le with another open data le or external IBM SPSS Statistics data
le that contains the same cases (rows) but different variables (columns). For example, you might want to
merge a data le that contains pre-test results with one that contains post-test results.
Merge Method tab
Use the Merge Method tab to dene the merge type.
One-to-one merge based on le order
Order of cases in the les determines how cases are matched. This is the default setting when no
variables exist with the same name and basic type (string or numeric) in both les. This setting
generates MATCH FILES command syntax in the following format (where [name] is either a dataset
or external le specication (enclosed in quotation marks)):
MATCH FILES FILE=* /FILE="[name]"
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One-to-one merge based on key values
Cases are matched based on the values of one or more key variables. This is the default setting when
one or more variables have the same name and basic type (string or numeric) in both les. This setting
generates MATCH FILES command syntax in the following format (where [name] is either a dataset
or external le specication (enclosed in quotation marks)):
MATCH FILES FILE=* /FILE="[name]" /BY [key varlist]
One-to-many merge based on key values
One le contains case data, and one le is lookup table. Cases from the lookup table are merged with
cases with matching key values in the case data le. The same key value can occur multiple times in
the case data le. One case in the lookup table can be merged with many cases in the case data le.
• All cases in the case data le are included in the merged le.
• Cases in the table lookup le that do not have cases with matching key values in the case data le
not included.
• The table lookup le cannot contain duplicate key values. If the les have multiple key variables, the
key value is the combination of those values.
This setting generates MATCH FILES syntax with a TABLE subcommand for the lookup table.
Select Lookup Table
The following settings are enabled only when One-to-many merge based on key values is selected.
[active dataset name]*
The active dataset name followed by an asterisk.
• By default, this option is not selected. When selected, this setting generates syntax in the
following format (where [name] is either a dataset or external le specication (enclosed in
quotation marks)):
MATCH FILES TABLE=* /FILE=”[name]” /BY [key varlist]
[second dataset name or le name]
The name of the second dataset or le.
• This is the default setting.
• When the le is external, only the le name (not the entire path) is provided (the full path is
included in the generated syntax).
• When the second le is an external le (and sorting is selected, or it has string keys that require
a change in the dened length), the le must rst be opened and assigned a unique name.
• When the second le is an external le that needs to be opened (based on the previous
condition), and the active dataset is unnamed, the active dataset must be named before the
second data le is opened.
• When the second le is opened for sorting or changing string key lengths, it remains open after
the merge action. Because the le was changed, you are prompted to save changes when the
le is closed.
• When selected, this setting generates syntax in the following format (where [name] is either a
dataset or external le specication (enclosed in quotation marks)):
MATCH FILES FILE=* /TABLE=”[name]” /BY [key varlist]
Sort les by key values before merging
For key value merges, both les must be sorted in order of the key variable values.
• This setting is enabled only when one of the key values merge options is selected.
• If one of the les is an external le, it will be opened and sorted. The sorted le will not be saved
unless you explicitly save the le.
• If the les are already sorted, you can save time by clearing this option.
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• When selected, this setting generates SORT CASES syntax.
Key Variables
For key value merges, variables with the same name and basic data type (string or numeric) are
included as key variables by default. Use the Variables tab to add, remove, or change the order of the
key variables.
Notes:
• The selected merge always generates MATCH FILES command syntax (never STAR JOIN syntax).
• SORT CASES and ALTER TYPE command syntax takes precedence over MATCH FILES command
syntax.
• DROP subcommand syntax, and optional RENAME subcommand syntax, is included based on
selections that were made on the Variables tab.
• BY subcommand syntax is included if one of the key values merge options is selected.
• When string keys have different dened lengths, ALTER TYPE syntax is automatically generated to
ensure equally dened lengths.
Variables tab
Use the Variables tab to add, remove, and rename variables to include in the merged le.
• Variables from the active data le are identied with an asterisk (*).
• Variables from the other data le are identied with a plus sign (+).
Excluded Variables
Variables to exclude from the new, merged data le.
• When the One-to-one merge based on le order setting is selected on the Merge Method tab, all
variables in the second dataset whose names are the same as names in active dataset are excluded.
• When the One-to-one merge based on key values or One-to-many merge based on key values
setting is selected on the Merge Method tab, all duplicate names variables in the second dataset
(that are a different basic type (string/numeric) than the same variable names in the active dataset)
are excluded.
Included Variables
Variables to include in the new, merged data le. If you want to include an excluded variable with a
duplicate name in the merged data le, use Rename to change the name.
• When the One-to-one merge based on le order setting is selected on the Merge Method tab, all
variables in the active dataset and all uniquely named variables in the second dataset are included.
• When the One-to-one merge based on key values or One-to-many merge based on key values
setting is selected on the Merge Method tab, all uniquely named variables in both datasets are
included. Variables in the active dataset, with duplicate names in second dataset that are a different
basic type (string/numeric) in the second dataset, are also included.
Key Variables
For key value merges, cases are merged based on key variable values.
• The default list assignment is determined by the selected Merge Method. Variables are never
automatically assigned to the Key Variables list.
– When the One-to-one merge based on le order setting is selected on the Merge Method tab,
no variables are included, the Move control is disabled, and manually dragging and dropping
variables has no effect.
– When the One-to-one merge based on key values or One-to-many merge based on key values
setting is selected on the Merge Method tab, all variables with same name and same basic type
(string/numeric) in both datasets are included.
• Each key variable must have the same name and same basic data type (string or numeric) in both
les.
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• If a key variable has different names in the two les, use Rename to change one of the names.
• If a string key variable has different dened lengths in the two les, the variable with the shorter
length is automatically adjusted to the longer length. The modied version of the original le is not
save unless you explicitly save it.
Add Variables: Rename
You can rename variables from either the active dataset or the other data le before moving them to the
list of variables to be included in the merged data le. This is primarily useful if you want to include two
variables with the same name that contain different information in the two les or if a key variable has
different names in the two les.
Merging More Than Two Data Sources
Using command syntax, you can merge more than two data les.
• Use MATCH FILES to merge multiple les that don't contain key variables or multiple les already
sorted on key variable values.
• Use STAR JOIN to merge multiple les where there is one case data le and multiple table lookup les.
Files do not need to be sorted in order of key variable values, and each table lookup le can use a
different key variable.
Aggregate Data
Aggregate Data aggregates groups of cases in the active dataset into single cases and creates a new,
aggregated le or creates new variables in the active dataset that contain aggregated data. Cases are
aggregated based on the value of zero or more break (grouping) variables. If no break variables are
specied, then the entire dataset is a single break group.
• If you create a new, aggregated data le, the new data le contains one case for each group dened by
the break variables. For example, if there is one break variable with two values, the new data le will
contain only two cases. If no break variable is specied, the new data le will contain one case.
• If you add aggregate variables to the active dataset, the data le itself is not aggregated. Each case with
the same value(s) of the break variable(s) receives the same values for the new aggregate variables. For
example, if gender is the only break variable, all males would receive the same value for a new
aggregate variable that represents average age. If no break variable is specied, all cases would receive
the same value for a new aggregate variable that represents average age.
Break Variable(s). Cases are grouped together based on the values of the break variables. Each unique
combination of break variable values denes a group. When creating a new, aggregated data le, all break
variables are saved in the new le with their existing names and dictionary information. The break
variable, if specied, can be either numeric or string.
Aggregated Variables. Source variables are used with aggregate functions to create new aggregate
variables. The aggregate variable name is followed by an optional variable label, the name of the
aggregate function, and the source variable name in parentheses.
You can override the default aggregate variable names with new variable names, provide descriptive
variable labels, and change the functions used to compute the aggregated data values. You can also
create a variable that contains the number of cases in each break group.
To Aggregate a Data File
1. From the menus choose:
Data > Aggregate...
2. Optionally select break variables that dene how cases are grouped to create aggregated data. If no
break variables are specied, then the entire dataset is a single break group.
3. Select one or more aggregate variables.
4. Select an aggregate function for each aggregate variable.
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Saving Aggregated Results
You can add aggregate variables to the active dataset or create a new, aggregated data le.
• Add aggregated variables to active dataset. New variables based on aggregate functions are added to
the active dataset. The data le itself is not aggregated. Each case with the same value(s) of the break
variable(s) receives the same values for the new aggregate variables.
• Create a new dataset containing only the aggregated variables. Saves aggregated data to a new dataset
in the current session. The dataset includes the break variables that dene the aggregated cases and all
aggregate variables dened by aggregate functions. The active dataset is unaffected.
• Write a new data le containing only the aggregated variables. Saves aggregated data to an external
data le. The le includes the break variables that dene the aggregated cases and all aggregate
variables dened by aggregate functions. The active dataset is unaffected.
Sorting Options for Large Data Files
For very large data les, it may be more efcient to aggregate presorted data.
File is already sorted on break variable(s). If the data have already been sorted by values of the break
variables, this option enables the procedure to run more quickly and use less memory. Use this option
with caution.
• Data must by sorted by values of the break variables in the same order as the break variables specied
for the Aggregate Data procedure.
• If you are adding variables to the active dataset, select this option only if the data are sorted by
ascending values of the break variables.
Sort le before aggregating. In very rare instances with large data les, you may nd it necessary to sort
the data le by values of the break variables prior to aggregating. This option is not recommended unless
you encounter memory or performance problems.
Aggregate Data: Aggregate Function
This dialog box species the function to use to calculate aggregated data values for selected variables on
the Aggregate Variables list in the Aggregate Data dialog box. Aggregate functions include:
• Summary functions for numeric variables, including mean, median, standard deviation, and sum
• Number of cases, including unweighted, weighted, nonmissing, and missing
• Percentage, fraction or count of values above or below a specied value
• Percentage, fraction, or count of values inside or outside of a specied range
Aggregate Data: Variable Name and Label
Aggregate Data assigns default variable names for the aggregated variables in the new data le. This
dialog box enables you to change the variable name for the selected variable on the Aggregate Variables
list and provide a descriptive variable label. See the topic “Variable names” on page 46
for more
information.
Split le
Split File splits the data le into separate groups for analysis based on the values of one or more grouping
variables. If you select multiple grouping variables, cases are grouped by each variable within categories
of the preceding variable on the Groups Based On list. For example, if you select gender as the rst
grouping variable and minority as the second grouping variable, cases will be grouped by minority
classication within each gender category.
• You can specify up to eight grouping variables.
• Each eight bytes of a long string variable (string variables longer than eight bytes) counts as a variable
toward the limit of eight grouping variables.
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• Cases should be sorted by values of the grouping variables and in the same order that variables are
listed in the Groups Based On list. If the data le isn't already sorted, select Sort the le by grouping
variables.
Compare groups. Split-le groups are presented together for comparison purposes. For pivot tables, a
single pivot table is created and each split-le variable can be moved between table dimensions. For
charts, a separate chart is created for each split-le group and the charts are displayed together in the
Viewer.
Organize output by groups. All results from each procedure are displayed separately for each split-le
group.
To Split a Data File for Analysis
1. From the menus choose:
Data > Split File...
2. Select Compare groups or Organize output by groups.
3. Select one or more grouping variables.
Select cases
Select Cases provides several methods for selecting a subgroup of cases based on criteria that include
variables and complex expressions. You can also select a random sample of cases. The criteria used to
dene a subgroup can include:
• Variable values and ranges
• Date and time ranges
• Case (row) numbers
• Arithmetic expressions
• Logical expressions
• Functions
All cases. Turns case ltering off and uses all cases.
If condition is satised. Use a conditional expression to select cases. If the result of the conditional
expression is true, the case is selected. If the result is false or missing, the case is not selected.
Random sample of cases. Selects a random sample based on an approximate percentage or an exact
number of cases.
Based on time or case range. Selects cases based on a range of case numbers or a range of dates/times.
Use lter variable. Use the selected numeric variable from the data le as the lter variable. Cases with
any value other than 0 or missing for the lter variable are selected.
Output
This section controls the treatment of unselected cases. You can choose one of the following alternatives
for the treatment of unselected cases:
• Filter out unselected cases. Unselected cases are not included in the analysis but remain in the
dataset. You can use the unselected cases later in the session if you turn ltering off. If you select a
random sample or if you select cases based on a conditional expression, this generates a variable
named lter_$ with a value of 1 for selected cases and a value of 0 for unselected cases.
• Copy selected cases to a new dataset. Selected cases are copied to a new dataset, leaving the original
dataset unaffected. Unselected cases are not included in the new dataset and are left in their original
state in the original dataset.
• Delete unselected cases. Unselected cases are deleted from the dataset. Deleted cases can be
recovered only by exiting from the le without saving any changes and then reopening the le. The
deletion of cases is permanent if you save the changes to the data le.
Chapter 9. File handling and
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Note: If you delete unselected cases and save the le, the cases cannot be recovered.
To Select a Subset of Cases
1. From the menus choose:
Data > Select Cases...
2. Select one of the methods for selecting cases.
3. Specify the criteria for selecting cases.
Select cases: If
This dialog box allows you to select subsets of cases using conditional expressions. A conditional
expression returns a value of true, false, or missing for each case.
• If the result of a conditional expression is true, the case is included in the selected subset.
• If the result of a conditional expression is false or missing, the case is not included in the selected
subset.
• Most conditional expressions use one or more of the six relational operators (<, >, <=, >=, =, and ~=) on
the calculator pad.
• Conditional expressions can include variable names, constants, arithmetic operators, numeric (and
other) functions, logical variables, and relational operators.
Select cases: Random sample
This dialog box allows you to select a random sample based on an approximate percentage or an exact
number of cases. Sampling is performed without replacement; so, the same case cannot be selected
more than once.
Approximately. Generates a random sample of approximately the specied percentage of cases. Since
this routine makes an independent pseudo-random decision for each case, the percentage of cases
selected can only approximate the specied percentage. The more cases there are in the data le, the
closer the percentage of cases selected is to the specied percentage.
Exactly. A user-specied number of cases. You must also specify the number of cases from which to
generate the sample. This second number should be less than or equal to the total number of cases in the
data le. If the number exceeds the total number of cases in the data le, the sample will contain
proportionally fewer cases than the requested number.
Select cases: Range
This dialog box selects cases based on a range of case numbers or a range of dates or times.
• Case ranges are based on row number as displayed in the Data Editor.
• Date and time ranges are available only for time series data with dened date variables (Data menu,
Dene Dates).
Note: If unselected cases are ltered (rather than deleted), subsequently sorting the dataset will turn off
ltering applied by this dialog.
Weight cases
Weight Cases gives cases different weights (by simulated replication) for statistical analysis.
• The values of the weighting variable should indicate the number of observations represented by single
cases in your data le.
• Cases with zero, negative, or missing values for the weighting variable are excluded from analysis.
• Fractional values are valid and some procedures, such as Frequencies, Crosstabs, and Custom Tables,
will use fractional weight values. However, most procedures treat the weighting variable as a replication
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weight and will simply round fractional weights to the nearest integer. Some procedures ignore the
weighting variable completely, and this limitation is noted in the procedure-specic documentation.
Once you apply a weight variable, it remains in effect until you select another weight variable or turn off
weighting. If you save a weighted data le, weighting information is saved with the data le. You can turn
off weighting at any time, even after the le has been saved in weighted form.
Weights in Crosstabs. The Crosstabs procedure has several options for handling case weights.
Weights in scatterplots and histograms. Scatterplots and histograms have an option for turning case
weights on and off, but this does not affect cases with a zero, negative, or missing value for the weight
variable. These cases remain excluded from the chart even if you turn weighting off from within the chart.
To Weight Cases
1. From the menus choose:
Data > Weight Cases...
2. Select Weight cases by.
3. Select a frequency variable.
The values of the frequency variable are used as case weights. For example, a case with a value of 3 for
the frequency variable will represent three cases in the weighted data le.
Restructuring Data
Use the Restructure Data Wizard to restructure your data for the procedure that you want to use. The
wizard replaces the current le with a new, restructured le. The wizard can:
• Restructure selected variables into cases
• Restructure selected cases into variables
• Transpose all data
To Restructure Data
1. From the menus choose:
Data > Restructure...
2. Select the type of restructuring that you want to do.
3. Select the data to restructure.
Optionally, you can:
• Create identication variables, which allow you to trace a value in the new le back to a value in the
original le
• Sort the data prior to restructuring
• Dene options for the new le
• Paste the command syntax into a syntax window
Restructure Data Wizard: Select Type
Use the Restructure Data Wizard to restructure your data. In the rst dialog box, select the type of
restructuring that you want to do.
• Restructure selected variables into cases. Choose this when you have groups of related columns in
your data and you want them to appear in groups of rows in the new data le. If you choose this, the
wizard will display the steps for Variables to Cases.
• Restructure selected cases into variables. Choose this when you have groups of related rows in your
data and you want them to appear in groups of columns in the new data le. If you choose this, the
wizard will display the steps for Cases to Variables.
Chapter 9. File handling and
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• Transpose all data. Choose this when you want to transpose your data. All rows will become columns
and all columns will become rows in the new data. This choice closes the Restructure Data Wizard and
opens the Transpose Data dialog box.
Deciding How to Restructure the Data
A variable contains information that you want to analyze--for example, a measurement or a score. A case
is an observation--for example, an individual. In a simple data structure, each variable is a single column
in your data and each case is a single row. So, for example, if you were measuring test scores for all
students in a class, all score values would appear in only one column, and there would be a row for each
student.
When you analyze data, you are often analyzing how a variable varies according to some condition. The
condition can be a specic experimental treatment, a demographic, a point in time, or something else. In
data analysis, conditions of interest are often referred to as factors. When you analyze factors, you have a
complex data structure. You may have information about a variable in more than one column in your data
(for example, a column for each level of a factor), or you may have information about a case in more than
one row (for example, a row for each level of a factor). The Restructure Data Wizard helps you to
restructure les with a complex data structure.
The structure of the current le and the structure that you want in the new le determine the choices that
you make in the wizard.
How are the data arranged in the current le? The current data may be arranged so that factors are
recorded in a separate variable (in groups of cases) or with the variable (in groups of variables).
• Groups of cases. Does the current le have variables and conditions recorded in separate columns? For
example:
Table 10. Data with variables and conditions in separate columns
var factor
8 1
9 1
3 2
1 2
In this example, the rst two rows are a case group because they are related. They contain data for the
same factor level. In IBM SPSS Statistics data analysis, the factor is often referred to as a grouping
variable when the data are structured this way.
• Groups of columns. Does the current le have variables and conditions recorded in the same column?
For example:
Table 11. Data with variables and conditions in same column
var_1 var_2
8 3
9 1
In this example, the two columns are a variable group because they are related. They contain data for
the same variable--var_1 for factor level 1 and var_2 for factor level 2. In IBM SPSS Statistics data
analysis, the factor is often referred to as a repeated measure when the data are structured this way.
How should the data be arranged in the new le? This is usually determined by the procedure that you
want to use to analyze your data.
• Procedures that require groups of cases. Your data must be structured in case groups to do analyses
that require a grouping variable. Examples are univariate, multivariate, and variance components with
General Linear Model, Mixed Models, and OLAP Cubes and independent samples with T Test or
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Nonparametric Tests. If your current data structure is variable groups and you want to do these
analyses, select Restructure selected variables into cases.
• Procedures that require groups of variables. Your data must be structured in variable groups to
analyze repeated measures. Examples are repeated measures with General Linear Model, time-
dependent covariate analysis with Cox Regression Analysis, paired samples with T Test, or related
samples with Nonparametric Tests. If your current data structure is case groups and you want to do
these analyses, select Restructure selected cases into variables.
Example of Variables to Cases
In this example, test scores are recorded in separate columns for each factor, A and B.
Table 12. Test scores recorded in separate columns for each factor
score_a score_b
1014 864
684 636
810 638
You want to do an independent-samples t test. You have a column group consisting of score_a and
score_b, but you don't have the grouping variable that the procedure requires. Select Restructure
selected variables into cases in the Restructure Data Wizard, restructure one variable group into a new
variable named score, and create an index named group. The new data le is shown in the following
gure.
Table 13. New, restructured data for variables to cases
group score
SCORE_A 1014
SCORE_B 864
SCORE_A 684
SCORE_B 636
SCORE_A 810
SCORE_B 638
When you run the independent-samples t test, you can now use group as the grouping variable.
Example of Cases to Variables
In this example, test scores are recorded twice for each subject—before and after a treatment.
Table 14. Current data for cases to variables
id scor time
1 1014 bef
1 864 aft
2 684 bef
2 636 aft
You want to do a paired-samples t test. Your data structure is case groups, but you don't have the
repeated measures for the paired variables that the procedure requires. Select Restructure selected
Chapter 9. File handling and
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cases into variables in the Restructure Data Wizard, use id to identify the row groups in the current data,
and use time to create the variable group in the new le.
Table 15. New, restructured data for cases to variables
id aft bef
1 864 1014
2 636 684
When you run the paired-samples t test, you can now use bef and aft as the variable pair.
Restructure Data Wizard (Variables to Cases): Number of Variable Groups
Note: The wizard presents this step if you choose to restructure variable groups into rows.
In this step, decide how many variable groups in the current le that you want to restructure in the new
le.
How many variable groups are in the current le? Think about how many variable groups exist in the
current data. A group of related columns, called a variable group, records repeated measures of the
same variable in separate columns. For example, if you have three columns in the current data--w1, w2,
and w3--that record width, you have one variable group. If you have an additional three columns--h1, h2,
and h3--that record height, you have two variable groups.
How many variable groups should be in the new le? Consider how many variable groups you want to
have represented in the new data le. You do not have to restructure all variable groups into the new le.
• One. The wizard will create a single restructured variable in the new le from one variable group in the
current le.
• More than one. The wizard will create multiple restructured variables in the new le. The number that
you specify affects the next step, in which the wizard automatically creates the specied number of new
variables.
Restructure Data Wizard (Variables to Cases): Select Variables
Note: The wizard presents this step if you choose to restructure variable groups into rows.
In this step, provide information about how the variables in the current le should be used in the new le.
You can also create a variable that identies the rows in the new le.
How should the new rows be identied? You can create a variable in the new data le that identies the
row in the current data le that was used to create a group of new rows. The identier can be a sequential
case number or it can be the values of the variable. Use the controls in Case Group Identication to dene
the identication variable in the new le. Click a cell to change the default variable name and provide a
descriptive variable label for the identication variable.
What should be restructured in the new le? In the previous step, you told the wizard how many
variable groups you want to restructure. The wizard created one new variable for each group. The values
for the variable group will appear in that variable in the new le. Use the controls in Variable to be
Transposed to dene the restructured variable in the new le.
To Specify One Restructured Variable
1. Put the variables that make up the variable group that you want to transform into the Variable to be
Transposed list. All of the variables in the group must be of the same type (numeric or string).
You can include the same variable more than once in the variable group (variables are copied rather than
moved from the source variable list); its values are repeated in the new le.
To Specify Multiple Restructured Variables
1. Select the rst target variable that you want to dene from the Target Variable drop-down list.
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2. Put the variables that make up the variable group that you want to transform into the Variable to be
Transposed list. All of the variables in the group must be of the same type (numeric or string). You can
include the same variable more than once in the variable group. (A variable is copied rather than
moved from the source variable list, and its values are repeated in the new le.)
3. Select the next target variable that you want to dene, and repeat the variable selection process for all
available target variables.
• Although you can include the same variable more than once in the same target variable group, you
cannot include the same variable in more than one target variable group.
• Each target variable group list must contain the same number of variables. (Variables that are listed
more than once are included in the count.)
• The number of target variable groups is determined by the number of variable groups that you specied
in the previous step. You can change the default variable names here, but you must return to the
previous step to change the number of variable groups to restructure.
• You must dene variable groups (by selecting variables in the source list) for all available target
variables before you can proceed to the next step.
What should be copied into the new le? Variables that aren't restructured can be copied into the new
le. Their values will be propagated in the new rows. Move variables that you want to copy into the new
le into the Fixed Variable(s) list.
Restructure Data Wizard (Variables to Cases): Create Index Variables
Note: The wizard presents this step if you choose to restructure variable groups into rows.
In this step, decide whether to create index variables. An index is a new variable that sequentially
identies a row group based on the original variable from which the new row was created.
How many index variables should be in the new le? Index variables can be used as grouping variables
in procedures. In most cases, a single index variable is sufcient; however, if the variable groups in your
current le reflect multiple factor levels, multiple indices may be appropriate.
• One. The wizard will create a single index variable.
• More than one. The wizard will create multiple indices and enter the number of indices that you want to
create. The number that you specify affects the next step, in which the wizard automatically creates the
specied number of indices.
• None. Select this if you do not want to create index variables in the new le.
Example of One Index for Variables to Cases
In the current data, there is one variable group, width, and one factor, time. Width was measured three
times and recorded in w1, w2, and w3.
Table 16. Current data for one index
subject w1 w2 w3
1 6.7 4.3 5.7
2 7.1 5.9 5.6
We'll restructure the variable group into a single variable, width, and create a single numeric index. The
new data are shown in the following table.
Table 17. New, restructured data with one index
subject index width
1 1 6.7
1 2 4.3
Chapter 9. File handling and le transformations 109
Table 17. New, restructured data with one index (continued)
subject index width
1 3 5.7
2 1 7.1
2 2 5.9
2 3 5.6
Index starts with 1 and increments for each variable in the group. It restarts each time a new row is
encountered in the original le. We can now use index in procedures that require a grouping variable.
Example of Two Indices for Variables to Cases
When a variable group records more than one factor, you can create more than one index; however, the
current data must be arranged so that the levels of the rst factor are a primary index within which the
levels of subsequent factors cycle. In the current data, there is one variable group, width, and two factors,
A and B. The data are arranged so that levels of factor B cycle within levels of factor A.
Table 18. Current data for two indices
subject w_a1b1 w_a1b2 w_a2b1 w_a2b2
1 5.5 6.4 5.8 5.9
2 7.4 7.1 5.6 6.7
We'll restructure the variable group into a single variable, width, and create two indices. The new data are
shown in the following table.
Table 19. New, restructured data with two indices
subject index_a index_b width
1 1 1 5.5
1 1 2 6.4
1 2 1 5.8
1 2 2 5.9
2 1 1 7.4
2 1 2 7.1
2 2 1 5.6
2 2 2 6.7
Restructure Data Wizard (Variables to Cases): Create One Index Variable
Note: The wizard presents this step if you choose to restructure variable groups into rows and create one
index variable.
In this step, decide what values you want for the index variable. The values can be sequential numbers or
the names of the variables in an original variable group. You can also specify a name and a label for the
new index variable.
See the topic “Example of One Index for Variables to Cases” on page 109 for more information.
• Sequential numbers. The wizard will automatically assign sequential numbers as index values.
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• Variable names. The wizard will use the names of the selected variable group as index values. Choose a
variable group from the list.
• Names and labels. Click a cell to change the default variable name and provide a descriptive variable
label for the index variable.
Restructure Data Wizard (Variables to Cases): Create Multiple Index Variables
Note: The wizard presents this step if you choose to restructure variable groups into rows and create
multiple index variables.
In this step, specify the number of levels for each index variable. You can also specify a name and a label
for the new index variable.
See the topic “Example of Two Indices for Variables to Cases” on page 110
for more information.
How many levels are recorded in the current le? Consider how many factor levels are recorded in the
current data. A level denes a group of cases that experienced identical conditions. If there are multiple
factors, the current data must be arranged so that the levels of the rst factor are a primary index within
which the levels of subsequent factors cycle.
How many levels should be in the new le? Enter the number of levels for each index. The values for
multiple index variables are always sequential numbers. The values start at 1 and increment for each
level. The rst index increments the slowest, and the last index increments the fastest.
Total combined levels. You cannot create more levels than exist in the current data. Because the
restructured data will contain one row for each combination of treatments, the wizard checks the number
of levels that you create. It will compare the product of the levels that you create to the number of
variables in your variable groups. They must match.
Names and labels. Click a cell to change the default variable name and provide a descriptive variable
label for the index variables.
Restructure Data Wizard (Variables to Cases): Options
Note: The wizard presents this step if you choose to restructure variable groups into rows.
In this step, specify options for the new, restructured le.
Drop unselected variables? In the Select Variables step (step 3), you selected variable groups to be
restructured, variables to be copied, and an identication variable from the current data. The data from
the selected variables will appear in the new le. If there are other variables in the current data, you can
choose to discard or keep them.
Keep missing data? The wizard checks each potential new row for null values. A null value is a system-
missing or blank value. You can choose to keep or discard rows that contain only null values.
Create a count variable? The wizard can create a count variable in the new le. It contains the number
of new rows generated by a row in the current data. A count variable may be useful if you choose to
discard null values from the new le because that makes it possible to generate a different number of
new rows for a given row in the current data. Click a cell to change the default variable name and provide
a descriptive variable label for the count variable.
Restructure Data Wizard (Cases to Variables): Select Variables
Note: The wizard presents this step if you choose to restructure case groups into columns.
In this step, provide information about how the variables in the current le should be used in the new le.
What identies case groups in the current data? A case group is a group of rows that are related
because they measure the same observational unit--for example, an individual or an institution. The
wizard needs to know which variables in the current le identify the case groups so that it can consolidate
each group into a single row in the new le. Move variables that identify case groups in the current le into
the Identier Variable(s) list. Variables that are used to split the current data le are automatically used to
identify case groups. Each time a new combination of identication values is encountered, the wizard will
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create a new row, so cases in the current le should be sorted by values of the identication variables in
the same order that variables are listed in the Identier Variable(s) list. If the current data le isn't already
sorted, you can sort it in the next step.
How should the new variable groups be created in the new le? In the original data, a variable appears
in a single column. In the new data le, that variable will appear in multiple new columns. Index
variables are variables in the current data that the wizard should use to create the new columns. The
restructured data will contain one new variable for each unique value in these columns. Move the
variables that should be used to form the new variable groups to the Index Variable(s) list. When the
wizard presents options, you can also choose to order the new columns by index.
What happens to the other columns? The wizard automatically decides what to do with the variables
that remain in the Current File list. It checks each variable to see if the data values vary within a case
group. If they do, the wizard restructures the values into a variable group in the new le. If they don't, the
wizard copies the values into the new le. When determining if a variable varies within a group, user-
missing values are treated like valid values, but system-missing values are not. If the group contains one
valid or use-missing value plus the system-missing value, then it is treated as a variable that does not
vary within the group, and the wizard copies the values into the new le.
Restructure Data Wizard (Cases to Variables): Sort Data
Note: The wizard presents this step if you choose to restructure case groups into columns.
In this step, decide whether to sort the current le before restructuring it. Each time the wizard
encounters a new combination of identication values, a new row is created, so it is important that the
data are sorted by the variables that identify case groups.
How are the rows ordered in the current le? Consider how the current data are sorted and which
variables you are using to identify case groups (specied in the previous step).
• Yes. The wizard will automatically sort the current data by the identication variables in the same order
that variables are listed in the Identier Variable(s) list in the previous step. Choose this when the data
aren't sorted by the identication variables or when you aren't sure. This choice requires a separate
pass of the data, but it guarantees that the rows are correctly ordered for restructuring.
• No. The wizard will not sort the current data. Choose this when you are sure that the current data are
sorted by the variables that identify case groups.
Restructure Data Wizard (Cases to Variables): Options
Note: The wizard presents this step if you choose to restructure case groups into columns.
In this step, specify options for the new, restructured le.
How should the new variable groups be ordered in the new le?
• By variable. The wizard groups the new variables created from an original variable together.
• By index. The wizard groups the variables according to the values of the index variables.
Example. The variables to be restructured are w and h, and the index is month:
w, h, month
Grouping by variable results in:
w.jan, w.feb, h.jan
Grouping by index results in:
w.jan, h.jan, w.feb
Create a count variable? The wizard can create a count variable in the new le. It contains the number of
rows in the current data that were used to create a row in the new data le.
Create indicator variables? The wizard can use the index variables to create indicator variables in the
new data le. It creates one new variable for each unique value of the index variable. The indicator
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variables signal the presence or absence of a value for a case. An indicator variable has the value of 1 if
the case has a value; otherwise, it is 0.
Example. The index variable is product. It records the products that a customer purchased. The original
data are:
Table 20. All products in a single variable (column)
customer product
1 chick
1 eggs
2 eggs
3 chick
Creating an indicator variable results in one new variable for each unique value of product. The
restructured data are:
Table 21. Separate indicator variables for each product type
customer indchick indeggs
1 1 1
2 0 1
3 1 0
In this example, the restructured data could be used to get frequency counts of the products that
customers buy.
Restructure Data Wizard: Finish
This is the nal step of the Restructure Data Wizard. Decide what to do with your specications.
• Restructure now. The wizard will create the new, restructured le. Choose this if you want to replace
the current le immediately.
Note: If original data are weighted, the new data will be weighted unless the variable that is used as the
weight is restructured or dropped from the new le.
• Paste syntax. The wizard will paste the syntax it generates into a syntax window. Choose this when you
are not ready to replace the current le, when you want to modify the syntax, or when you want to save
it for future use.
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Chapter 10. Working with output
Working with output
When you run a procedure, the results are displayed in a window called the Viewer. In this window, you
can easily navigate to the output that you want to see. You can also manipulate the output and create a
document that contains precisely the output that you want.
Viewer
Results are displayed in the Viewer. You can use the Viewer to:
• Browse results
• Show or hide selected tables and charts
• Change the display order of results by moving selected items
• Move items between the Viewer and other applications
The Viewer is divided into two panes:
• The left pane contains an outline view of the contents.
• The right pane contains statistical tables, charts, and text output.
You can click an item in the outline to go directly to the corresponding table or chart. You can click and
drag the right border of the outline pane to change the width of the outline pane.
Showing and hiding results
In the Viewer, you can selectively show and hide individual tables or results from an entire procedure.
This process is useful when you want to shorten the amount of visible output in the contents pane.
To hide tables and charts
1. Double-click the item's book icon in the outline pane of the Viewer.
or
2. Click the item to select it.
3. From the menus choose:
View > Hide
or
4. Click the closed book (Hide) icon on the Outlining toolbar.
The open book (Show) icon becomes the active icon, indicating that the item is now hidden.
To hide procedure results
1. Click the box to the left of the procedure name in the outline pane.
This hides all results from the procedure and collapses the outline view.
Moving, deleting, and copying output
You can rearrange the results by copying, moving, or deleting an item or a group of items.
To move output in the Viewer
1. Select the items in the outline or contents pane.
2. Drag and drop the selected items into a different location.
To delete output in the Viewer
1. Select the items in the outline or contents pane.
2. Press the Delete key.
or
3. From the menus choose:
Edit > Delete
Changing initial alignment
By default, all results are initially left-aligned. To change the initial alignment of new output items:
1. From the menus choose:
Edit > Options
2. Click the Viewer tab.
3. In the Initial Output State group, select the item type (for example, pivot table, chart, text output).
4. Select the alignment option you want.
Changing alignment of output items
1. In the outline or contents pane, select the items that you want to align.
2. From the menus choose:
Format > Align Left
or
Format > Center
or
Format > Align Right
Viewer outline
The outline pane provides a table of contents of the Viewer document. You can use the outline pane to
navigate through your results and control the display. Most actions in the outline pane have a
corresponding effect on the contents pane.
• Selecting an item in the outline pane displays the corresponding item in the contents pane.
• Moving an item in the outline pane moves the corresponding item in the contents pane.
• Collapsing the outline view hides the results from all items in the collapsed levels.
Controlling the outline display. To control the outline display, you can:
• Expand and collapse the outline view
• Change the outline level for selected items
• Change the size of items in the outline display
• Change the font that is used in the outline display
To collapse and expand the outline view
1. Click the box to the left of the outline item that you want to collapse or expand.
or
2. Click the item in the outline.
3. From the menus choose:
View > Collapse
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or
View > Expand
To change the outline level
1. Click the item in the outline pane.
2. From the menus choose:
Edit > Outline > Promote
or
Edit > Outline > Demote
To change the size of outline items
1. From the menus choose:
View > Outline Size
2. Select the outline size (Small, Medium, or Large).
To change the font in the outline
1. From the menus choose:
View > Outline Font...
2. Select a font.
Adding items to the Viewer
In the Viewer, you can add items such as titles, new text, charts, or material from other applications.
To add a title or text
Text items that are not connected to a table or chart can be added to the Viewer.
1. Click the table, chart, or other object that will precede the title or text.
2. From the menus choose:
Insert > New Title
or
Insert > New Text
3. Double-click the new object.
4. Enter the text.
To add a text le
1. In the outline pane or contents pane of the Viewer, click the table, chart, or other object that will
precede the text.
2. From the menus choose:
Insert > Text File...
3. Select a text le.
To edit the text, double-click it.
Pasting Objects into the Viewer
Objects from other applications can be pasted into the Viewer. You can use either Paste After or Paste
Special. Either type of pasting puts the new object after the currently selected object in the Viewer. Use
Paste Special when you want to choose the format of the pasted object.
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Finding and replacing information in the Viewer
1. To nd or replace information in the Viewer, from the menus choose:
Edit > Find
or
Edit > Replace
You can use Find and Replace to:
• Search the entire document or just the selected items.
• Search down or up from the current location.
• Search both panes or restrict the search to the contents or outline pane.
• Search for hidden items. These include any items hidden in the contents pane (for example, Notes
tables, which are hidden by default) and hidden rows and columns in pivot tables.
• Restrict the search criteria to case-sensitive matches.
• Restrict the search criteria in pivot tables to matches of the entire cell contents.
• Restrict the search criteria in pivot tables to footnote markers only. This option is not available if the
selection in the Viewer includes anything other than pivot tables.
Hidden Items and Pivot Table Layers
• Layers beneath the currently visible layer of a multidimensional pivot table are not considered hidden
and will be included in the search area even when hidden items are not included in the search.
• Hidden items include hidden items in the contents pane (items with closed book icons in the outline
pane or included within collapsed blocks of the outline pane) and rows and columns in pivot tables
either hidden by default (for example, empty rows and columns are hidden by default) or manually
hidden by editing the table and selectively hiding specic rows or columns. Hidden items are only
included in the search if you explicitly select Include hidden items.
• In both cases, the hidden or nonvisible element that contains the search text or value is displayed when
it is found, but the item is returned to its original state afterward.
Finding a range of values in pivot tables
To nd values that fall within a specied range of values in pivot tables:
1. Activate a pivot table or select one or more pivot tables in the Viewer. Make sure that only pivot tables
are selected. If any other objects are selected, the Range option is not available.
2. From the menus choose:
Edit > Find
3. Click the Range tab.
4. Select the type of range: Between, Greater than or equal to, or Less than or equal to.
5. Select the value or values that dene the range.
• If either value contains non-numeric characters, both values are treated as strings.
• If both values are numbers, only numeric values are searched.
• You cannot use the Range tab to replace values.
This feature is not available for legacy tables. See the topic “Legacy tables” on page 141 for more
information.
Closing output items
You can close all currently open output items that were opened from a particular Viewer window.
1. Select the Viewer window that you want.
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2. From the menus, choose:
Window > Close output items
Copying output into other applications
Output objects can be copied and pasted into other applications, such as a word-processing program or a
spreadsheet. You can paste output in a variety of formats. Depending on the target application and the
selected output object(s), some or all of the following formats may be available:
Metale. WMF and EMF metale format. These formats are available only on Windows operating
systems.
RTF (rich text format). Multiple selected objects, text output, and pivot tables can be copied and pasted
in RTF format. For pivot tables, in most applications this means that the tables are pasted as tables that
can then be edited in the other application. Pivot tables that are too wide for the document width will
either be wrapped, scaled down to t the document width, or left unchanged, depending on the pivot
table options settings. See the topic “Pivot Tables options” on page 187 for more information.
Notes:
• Microsoft Word may not display extremely wide tables properly.
• Microsoft Ofce version 16 (or higher) is required when copying and pasting Boxplots and Histograms.
Image. JPG and PNG image formats.
BIFF. Pivot tables and text output can be pasted into a spreadsheet in BIFF format. Numbers in pivot
tables retain numeric precision. This format is available only on Windows operating systems.
Text. Pivot tables and text output can be copied and pasted as text. This process can be useful for
applications such as e-mail, where the application can accept or transmit only text.
Microsoft Ofce Graphic Object. Charts that support this format can be copied to Microsoft Ofce
applications and edited in those applications as native Microsoft Ofce charts. Because of differences
between SPSS Statistics/SPSS Modeler charts and Microsoft Ofce charts, some features of SPSS
Statistics/SPSS Modeler charts are not retained in the copied version. Copying multiple selected charts in
Microsoft Ofce Graphic Object format is not supported.
If the target application supports multiple available formats, it may have a Paste Special menu item that
allows you to select the format, or it may automatically display a list of available formats.
Copying and pasting multiple output objects
The following limitations apply when pasting multiple output objects into other applications:
• RTF format. In most applications, pivot tables are pasted as tables that can be edited in that
application. Charts, trees, and model views are pasted as images.
• Metale and image formats. All the selected output objects are pasted as a single object in the other
application.
• BIFF format. Charts, trees, and model views are excluded.
You can also use “Export output” on page 120 to export multiple output objects to other applications/
formats.
Copy special
When copying and pasting large amounts of output, particularly very large pivot tables, you can improve
the speed of the operation by using Edit > Copy Special to limit the number of formats copied to the
clipboard.
You can also save the selected formats as the default set of formats to copy to the clipboard. This setting
persists across sessions.
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119
Copy as
You can right-click a selected object in the Output Viewer and select Edit > Copy as to copy to the most
popular formats (for example, All, Image, or Microsoft Ofce Graphic Object). Selecting Edit > Copy
copies All. Note that if Copy as is grayed out or not present for a selected object, this copy format is not
available for that particular object.
Interactive output
Interactive output objects contain multiple, related output objects. The selection in one object can
change what is displayed or highlighted in the other object. For example, selecting a row in a table might
highlight an area in a map or display a chart for a different category.
Interactive output objects do not support editing features, such as changing text, colors, fonts, or table
borders. The individual objects can be copied from the interactive object to the Viewer. Tables copied
from interactive output can be edited in the pivot table editor.
Copying objects from interactive output
File>Copy to Viewer copies individual output objects to the Viewer window.
• The available options depend on the contents of the interactive output.
• Chart and Map create chart objects.
• Table creates a pivot table that can be edited in the pivot table editor.
• Snapshot creates an image of the current view.
• Model creates a copy of the current interactive output object.
Edit>Copy Object copies individual output objects to the clipboard.
• Pasting the copied object into the Viewer is equivalent to File>Copy to Viewer.
• Pasting the object into another application pastes the object as an image.
Zoom and Pan
For maps, you can use View>Zoom to zoom the view of the map. Within a zoomed map view, you can use
View>Pan to move the view.
Print settings
File>Print Settings controls how interactive objects are printed.
• Print visible view only. Prints only the view that is currently displayed. This option is the default
setting.
• Print all views. Prints all views contained in the interactive output.
• The selected option also determines the default action for exporting the output object.
Export output
Export Output saves Viewer output in HTML, text, Word/RTF, Excel, PowerPoint (requires PowerPoint 97
or later), and PDF formats. Charts can also be exported in a number of different graphics formats.
Note: Export to PowerPoint is available only on Windows operating systems and is not available in the
Student Version.
To export output
1. Make the Viewer the active window (click anywhere in the window).
2. From the menus choose:
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File > Export...
3. Enter a le name (or prex for charts) and select an export format.
Objects to Export. You can export all objects in the Viewer, all visible objects, or only selected objects.
Document Type. The available options are:
• Word/RTF. Pivot tables are exported as Word tables with all formatting attributes intact (for example,
cell borders, font styles, and background colors). Text output is exported as formatted RTF. Charts, tree
diagrams, and model views are included in PNG format. Note that Microsoft Word might not display
extremely wide tables properly.
• Excel. Pivot table rows, columns, and cells are exported as Excel rows, columns, and cells, with all
formatting attributes intact (for example, cell borders, font styles, and background colors). Text output
is exported with all font attributes intact. Each line in the text output is a row in the Excel le, with the
entire contents of the line in a single cell. Charts, tree diagrams, and model views are included in PNG
format. Output can be exported as Excel 97-2004 or Excel 2007 and higher.
• HTML. Pivot tables are exported as HTML tables. Text output is exported as preformatted HTML. Charts,
tree diagrams, and model views are embedded in the document in the selected graphic format. A
browser compatible with HTML 5 is required for viewing output that is exported in HTML format.
• Portable Document Format. All output is exported as it appears in Print Preview, with all formatting
attributes intact.
• PowerPoint le. Pivot tables are exported as Word tables and are embedded on separate slides in the
PowerPoint le, with one slide for each pivot table. All formatting attributes of the pivot table are
retained (for example, cell borders, font styles, and background colors). Charts, tree diagrams, and
model views are exported in TIFF format. Text output is not included.
Export to PowerPoint is available only on Windows operating systems.
• Text. Text output formats include plain text, UTF-8, and UTF-16. Pivot tables can be exported in tab-
separated or space-separated format. All text output is exported in space-separated format. For charts,
tree diagrams, and model views, a line is inserted in the text le for each graphic, indicating the image
le name.
• None (Graphics Only). Available export formats include: EPS, JPEG, TIFF, PNG, and BMP. On Windows
operating systems, EMF (enhanced metale) format is also available.
Open the containing folder. Opens the folder that contains the les that are created by the export.
Output Management System. You can also automatically export all output or user-specied types of
output as Word, Excel, PDF, HTML, text, or IBM SPSS Statistics format data les. See Chapter 22, “Output
Management System,” on page 243 for more information.
HTML options
HTML export requires a browser that is compatible with HTML 5. The following options are available for
exporting output in HTML format:
Layers in pivot tables. By default, inclusion or exclusion of pivot table layers is controlled by the table
properties for each pivot table. You can override this setting and include all layers or exclude all but the
currently visible layer. See the topic “Table properties: printing” on page 136 for more information.
Export layered tables as interactive. Layered tables are displayed as they appear in the Viewer, and you
can interactively change the displayed layer in the browser. If this option is not selected, each table layer
is displayed as a separate table.
Tables as HTML. This controls style information included for exported pivot tables.
• Export with styles and xed column width. All pivot table style information (font styles, background
colors, etc.) and column widths are preserved.
• Export without styles. Pivot tables are converted to default HTML tables. No style attributes are
preserved. Column width is determined automatically.
Chapter 10. Working with output
121
Include footnotes and captions. Controls the inclusion or exclusion of all pivot table footnotes and
captions.
Views of Models. By default, inclusion or exclusion of model views is controlled by the model properties
for each model. You can override this setting and include all views or exclude all but the currently visible
view. See the topic “Model properties” on page 144 for more information. (Note: all model views,
including tables, are exported as graphics.)
Note: For HTML, you can also control the image le format for exported charts. See the topic “Graphics
format options” on page 125 for more information.
To set HTML export options
1. Select HTML as the export format.
2. Click Change Options.
Word/RTF options
The following options are available for exporting output in Word format:
Layers in pivot tables. By default, inclusion or exclusion of pivot table layers is controlled by the table
properties for each pivot table. You can override this setting and include all layers or exclude all but the
currently visible layer. See the topic “Table properties: printing” on page 136
for more information.
Wide Pivot Tables. Controls the treatment of tables that are too wide for the dened document width. By
default, the table is wrapped to t. The table is divided into sections, and row labels are repeated for each
section of the table. Alternatively, you can shrink wide tables or make no changes to wide tables and
allow them to extend beyond the dened document width.
Preserve break points. If you have dened break points, these settings will be preserved in the Word
tables.
Include footnotes and captions. Controls the inclusion or exclusion of all pivot table footnotes and
captions.
Views of Models. By default, inclusion or exclusion of model views is controlled by the model properties
for each model. You can override this setting and include all views or exclude all but the currently visible
view. See the topic “Model properties” on page 144 for more information. (Note: all model views,
including tables, are exported as graphics.)
Page Setup for Export. This opens a dialog where you can dene the page size and margins for the
exported document. The document width used to determine wrapping and shrinking behavior is the page
width minus the left and right margins.
To set Word export options
1. Select Word/RTF as the export format.
2. Click Change Options.
Excel options
The following options are available for exporting output in Excel format:
Create a worksheet or workbook or modify an existing worksheet. By default, a new workbook is
created. If a le with the specied name already exists, it will be overwritten. If you select the option to
create a worksheet, if a worksheet with the specied name already exists in the specied le, it will be
overwritten. If you select the option to modify an existing worksheet, you must also specify the worksheet
name. (This is optional for creating a worksheet.) Worksheet names cannot exceed 31 characters and
cannot contain forward or back slashes, square brackets, question marks, or asterisks.
When exporting to Excel 97-2004, if you modify an existing worksheet, charts, model views, and tree
diagrams are not included in the exported output.
Location in worksheet. Controls the location within the worksheet for the exported output. By default,
exported output will be added after the last column that has any content, starting in the rst row, without
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modifying any existing contents. This is a good choice for adding new columns to an existing worksheet.
Adding exported output after the last row is a good choice for adding new rows to an existing worksheet.
Adding exported output starting at a specic cell location will overwrite any existing content in the area
where the exported output is added.
Layers in pivot tables. By default, inclusion or exclusion of pivot table layers is controlled by the table
properties for each pivot table. You can override this setting and include all layers or exclude all but the
currently visible layer. See the topic “Table properties: printing” on page 136 for more information.
Include footnotes and captions. Controls the inclusion or exclusion of all pivot table footnotes and
captions.
Views of Models. By default, inclusion or exclusion of model views is controlled by the model properties
for each model. You can override this setting and include all views or exclude all but the currently visible
view. See the topic “Model properties” on page 144 for more information. (Note: all model views,
including tables, are exported as graphics.)
To set Excel export options
1. Select Excel as the export format.
2. Click Change Options.
PowerPoint options
The following options are available for PowerPoint:
Layers in pivot tables. By default, inclusion or exclusion of pivot table layers is controlled by the table
properties for each pivot table. You can override this setting and include all layers or exclude all but the
currently visible layer. See the topic “Table properties: printing” on page 136
for more information.
Wide Pivot Tables. Controls the treatment of tables that are too wide for the dened document width. By
default, the table is wrapped to t. The table is divided into sections, and row labels are repeated for each
section of the table. Alternatively, you can shrink wide tables or make no changes to wide tables and
allow them to extend beyond the dened document width.
Include footnotes and captions. Controls the inclusion or exclusion of all pivot table footnotes and
captions.
Use Viewer outline entries as slide titles. Includes a title on each slide that is created by the export.
Each slide contains a single item that is exported from the Viewer. The title is formed from the outline
entry for the item in the outline pane of the Viewer.
Views of Models. By default, inclusion or exclusion of model views is controlled by the model properties
for each model. You can override this setting and include all views or exclude all but the currently visible
view. See the topic “Model properties” on page 144 for more information. (Note: all model views,
including tables, are exported as graphics.)
Page Setup for Export. This opens a dialog where you can dene the page size and margins for the
exported document. The document width used to determine wrapping and shrinking behavior is the page
width minus the left and right margins.
To set PowerPoint export options
1. Select PowerPoint as the export format.
2. Click Change Options.
Note: Export to PowerPoint is available only on Windows operating systems.
PDF options
The following options are available for PDF:
Embed bookmarks. This option includes bookmarks in the PDF document that correspond to the Viewer
outline entries. Like the Viewer outline pane, bookmarks can make it much easier to navigate documents
with a large number of output objects.
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Embed fonts. Embedding fonts ensures that the PDF document will look the same on all computers.
Otherwise, if some fonts used in the document are not available on the computer being used to view (or
print) the PDF document, font substitution may yield suboptimal results.
Layers in pivot tables. By default, inclusion or exclusion of pivot table layers is controlled by the table
properties for each pivot table. You can override this setting and include all layers or exclude all but the
currently visible layer. See the topic “Table properties: printing” on page 136 for more information.
Views of Models. By default, inclusion or exclusion of model views is controlled by the model properties
for each model. You can override this setting and include all views or exclude all but the currently visible
view. See the topic “Model properties” on page 144 for more information. (Note: all model views,
including tables, are exported as graphics.)
To set PDF export options
1. Select Portable Document Format as the export format.
2. Click Change Options.
Other Settings That Affect PDF Output
Page Setup/Page Attributes. Page size, orientation, margins, content and display of page headers and
footers, and printed chart size in PDF documents are controlled by page setup and page attribute options.
Table Properties/TableLooks. Scaling of wide and/or long tables and printing of table layers are
controlled by table properties for each table. These properties can also be saved in TableLooks.
Default/Current Printer. The resolution (DPI) of the PDF document is the current resolution setting for
the default or currently selected printer (which can be changed using Page Setup). The maximum
resolution is 1200 DPI. If the printer setting is higher, the PDF document resolution will be 1200 DPI.
Note: High-resolution documents may yield poor results when printed on lower-resolution printers.
Text options
The following options are available for text export:
Pivot Table Format. Pivot tables can be exported in tab-separated or space-separated format. For space-
separated format, you can also control:
• Column Width. Autot does not wrap any column contents, and each column is as wide as the widest
label or value in that column. Custom sets a maximum column width that is applied to all columns in
the table, and values that exceed that width wrap onto the next line in that column.
• Row/Column Border Character. Controls the characters used to create row and column borders. To
suppress display of row and column borders, enter blank spaces for the values.
Layers in pivot tables. By default, inclusion or exclusion of pivot table layers is controlled by the table
properties for each pivot table. You can override this setting and include all layers or exclude all but the
currently visible layer. See the topic “Table properties: printing” on page 136
for more information.
Include footnotes and captions. Controls the inclusion or exclusion of all pivot table footnotes and
captions.
Views of Models. By default, inclusion or exclusion of model views is controlled by the model properties
for each model. You can override this setting and include all views or exclude all but the currently visible
view. See the topic “Model properties” on page 144 for more information. (Note: all model views,
including tables, are exported as graphics.)
To set text export options
1. Select Text as the export format.
2. Click Change Options.
Graphics only options
The following options are available for exporting graphics only:
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Views of Models. By default, inclusion or exclusion of model views is controlled by the model properties
for each model. You can override this setting and include all views or exclude all but the currently visible
view. See the topic “Model properties” on page 144 for more information. (Note: all model views,
including tables, are exported as graphics.)
Graphics format options
For HTML and text documents and for exporting charts only, you can select the graphic format, and for
each graphic format you can control various optional settings.
To select the graphic format and options for exported charts:
1. Select HTML, Text, or None (Graphics only) as the document type.
2. Select the graphic le format from the drop-down list.
3. Click Change Options to change the options for the selected graphic le format.
JPEG Chart Export Options
• Image size. Percentage of original chart size, up to 200 percent.
• Convert to grayscale. Converts colors to shades of gray.
BMP chart export options
• Image size. Percentage of original chart size, up to 200 percent.
• Compress image to reduce le size. A lossless compression technique that creates smaller les
without affecting image quality.
PNG chart export options
Image size. Percentage of original chart size, up to 200 percent.
Color Depth. Determines the number of colors in the exported chart. A chart that is saved under any
depth will have a minimum of the number of colors that are actually used and a maximum of the number
of colors that are allowed by the depth. For example, if the chart contains three colors--red, white, and
black--and you save it as 16 colors, the chart will remain as three colors.
• If the number of colors in the chart exceeds the number of colors for that depth, the colors will be
dithered to replicate the colors in the chart.
• Current screen depth is the number of colors currently displayed on your computer monitor.
EMF and TIFF chart export options
Image size. Percentage of original chart size, up to 200 percent.
Note: EMF (enhanced metale) format is available only on Windows operating systems.
EPS chart export options
Image size. You can specify the size as a percentage of the original image size (up to 200 percent), or you
can specify an image width in pixels (with height determined by the width value and the aspect ratio). The
exported image is always proportional to the original.
Include TIFF preview image. Saves a preview with the EPS image in TIFF format for display in
applications that cannot display EPS images on screen.
Fonts. Controls the treatment of fonts in EPS images.
• Use font references. If the fonts that are used in the chart are available on the output device, the fonts
are used. Otherwise, the output device uses alternate fonts.
• Replace fonts with curves. Turns fonts into PostScript curve data. The text itself is no longer editable
as text in applications that can edit EPS graphics. This option is useful if the fonts that are used in the
chart are not available on the output device.
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Viewer printing
There are two options for printing the contents of the Viewer window:
All visible output. Prints only items that are currently displayed in the contents pane. Hidden items
(items with a closed book icon in the outline pane or hidden in collapsed outline layers) are not printed.
Selection. Prints only items that are currently selected in the outline and/or contents panes.
To print output and charts
1. Make the Viewer the active window (click anywhere in the window).
2. From the menus choose:
File > Print...
3. Select the print settings that you want.
4. Click OK to print.
Print Preview
Print Preview shows you what will print on each page for Viewer documents. It is a good idea to check
Print Preview before actually printing a Viewer document, because Print Preview shows you items that
may not be visible by looking at the contents pane of the Viewer, including:
• Page breaks
• Hidden layers of pivot tables
• Breaks in wide tables
• Headers and footers that are printed on each page
If any output is currently selected in the Viewer, the preview displays only the selected output. To view a
preview for all output, make sure nothing is selected in the Viewer.
Page Attributes: Headers and Footers
Headers and footers are the information that is printed at the top and bottom of each page. You can enter
any text that you want to use as headers and footers. You can also use the toolbar in the middle of the
dialog box to insert:
• Date and time
• Page numbers
• Viewer lename
• Outline heading labels
• Page titles and subtitles
• Make Default uses the settings specied here as the default settings for new Viewer documents. (Note:
this makes the current settings on both the Header/Footer tab and the Options tab the default settings.)
• Outline heading labels indicate the rst-, second-, third-, and/or fourth-level outline heading for the rst
item on each page.
• Page titles and subtitles print the current page titles and subtitles. These can be created with New Page
Title on the Viewer Insert menu or with the TITLE and SUBTITLE commands. If you have not specied
any page titles or subtitles, this setting is ignored.
Note: Font characteristics for new page titles and subtitles are controlled on the Viewer tab of the
Options dialog box (accessed by choosing Options on the Edit menu). Font characteristics for existing
page titles and subtitles can be changed by editing the titles in the Viewer.
To see how your headers and footers will look on the printed page, choose Print Preview from the File
menu.
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To insert page headers and footers
1. Make the Viewer the active window (click anywhere in the window).
2. From the menus, choose:
File > Page Attributes...
3. Click the Header/Footer tab.
4. Enter the header and/or footer that you want to appear on each page.
Page Attributes: Options
This dialog box controls the printed chart size, the space between printed output items, and page
numbering.
• Printed Chart Size. Controls the size of the printed chart relative to the dened page size. The chart's
aspect ratio (width-to-height ratio) is not affected by the printed chart size. The overall printed size of a
chart is limited by both its height and width. When the outer borders of a chart reach the left and right
borders of the page, the chart size cannot increase further to ll more page height.
• Space between items. Controls the space between printed items. Each pivot table, chart, and text
object is a separate item. This setting does not affect the display of items in the Viewer.
• Number pages starting with. Numbers pages sequentially, starting with the specied number.
• Make Default. This option uses the settings that are specied here as the default settings for new
Viewer documents. (Note that this option makes the current Header/Footer settings and Options
settings the default.)
To change printed chart size, page numbering, and space between printed Items
1. Make the Viewer the active window (click anywhere in the window).
2. From the menus choose:
File > Page Attributes...
3. Click the Options tab.
4. Change the settings and click OK.
Saving output
The contents of the Viewer can be saved to the following formats:
• Viewer les (*.spv). The format that is used to display les in the Viewer window.
To save results in other formats (for example, text, Word, Excel), use Export on the File menu.
To save a Viewer document
1. From the Viewer window menus choose:
File > Save
2. Enter the name of the document, and then click Save.
Optionally, you can do the following:
Lock les to prevent editing in IBM SPSS Smartreader
If a Viewer document is locked, you can manipulate pivot tables (swap rows and columns, change
the displayed layer, etc.) but you cannot edit any output or save any changes to the Viewer
document in IBM SPSS Smartreader (a separate product for working with Viewer documents). This
setting has no effect on Viewer documents opened in IBM SPSS Statistics or IBM SPSS Modeler.
Encrypt les with a password
You can protect condential information stored in a Viewer document by encrypting the document
with a password. Once encrypted, the document can only be opened by providing the password.
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IBM SPSS Smartreader users will also be required to provide the password in order to open the
le.
To encrypt a Viewer document:
a. Select Encrypt le with password in the Save Output As dialog box.
b. Click Save.
c. In the Encrypt File dialog box, provide a password and re-enter it in the Conrm password text
box. Passwords are limited to 10 characters and are case-sensitive.
Warning: Passwords cannot be recovered if they are lost. If the password is lost the le cannot be
opened.
Creating strong passwords
• Use eight or more characters.
• Include numbers, symbols and even punctuation in your password.
• Avoid sequences of numbers or characters, such as "123" and "abc", and avoid repetition,
such as "111aaa".
• Do not create passwords that use personal information such as birthdays or nicknames.
• Periodically change the password.
Note: Storing encrypted les to an IBM SPSS Collaboration and Deployment Services Repository is
not supported.
Modifying encrypted les
• If you open an encrypted le, make modications to it and choose File > Save, the modied le
will be saved with the same password.
• You can change the password on an encrypted le by opening the le, repeating the steps for
encrypting it, and specifying a different password in the Encrypt File dialog box.
• You can save an unencrypted version of an encrypted le by opening the le, choosing File >
Save As and deselecting Encrypt le with password in the Save Output As dialog box.
Note: Encrypted data les and output documents cannot be opened in versions of IBM SPSS
Statistics prior to version 21. Encrypted syntax les cannot be opened in versions prior to version
22.
Store required model information with the output document
This option applies only when there are model viewer items in the output document that require
auxiliary information to enable some of the interactive features. Click More Info to display a list of
these model viewer items and the interactive features that require auxiliary information. Storing
this information with the output document might substantially increase the document size. If you
choose not to store this information, you can still open these output items but the specied
interactive features will not be available.
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Chapter 11. Pivot tables
Pivot tables
Many results are presented in tables that can be pivoted interactively. That is, you can rearrange the rows,
columns, and layers.
Note: If you require tables that are compatible with IBM SPSS Statistics releases prior to 20, then it is
recommended to render them as legacy tables. See the topic “Legacy tables” on page 141 for more
information.
Manipulating a pivot table
Options for manipulating a pivot table include:
• Transposing rows and columns
• Moving rows and columns
• Creating multidimensional layers
• Grouping and ungrouping rows and columns
• Showing and hiding rows, columns, and other information
• Rotating row and column labels
• Finding denitions of terms
Activating a pivot table
Before you can manipulate or modify a pivot table, you need to activate the table. To activate a table:
1. Double-click the table.
or
2. Right-click the table and from the pop-up menu choose Edit.
Pivoting a table
1. Activate the pivot table.
2. From the menus choose:
Pivot > Pivoting Trays
A table has three dimensions: rows, columns, and layers. A dimension can contain multiple elements (or
none at all). You can change the organization of the table by moving elements between or within
dimensions. To move an element, just drag and drop it where you want it.
Changing display order of elements within a dimension
To change the display order of elements within a table dimension (row, column, or layer):
1. If pivoting trays are not already on, from the Pivot Table menu choose:
Pivot > Pivoting Trays
2. Drag and drop the elements within the dimension in the pivoting tray.
Moving rows and columns within a dimension element
1. In the table itself (not the pivoting trays), click the label for the row or column you want to move.
2. Drag the label to the new position.
Transposing rows and columns
If you just want to flip the rows and columns, there's a simple alternative to using the pivoting trays:
1. From the menus choose:
Pivot > Transpose Rows and Columns
This has the same effect as dragging all of the row elements into the column dimension and dragging all
of the column elements into the row dimension.
Grouping rows or columns
1. Select the labels for the rows or columns that you want to group together (click and drag or Shift+click
to select multiple labels).
2. From the menus choose:
Edit > Group
A group label is automatically inserted. Double-click the group label to edit the label text.
Note: To add rows or columns to an existing group, you must rst ungroup the items that are currently in
the group. Then you can create a new group that includes the additional items.
Ungrouping rows or columns
1. Click anywhere in the group label for the rows or columns that you want to ungroup.
2. From the menus choose:
Edit > Ungroup
Ungrouping automatically deletes the group label.
Rotating row or column labels
You can rotate labels between horizontal and vertical display for the innermost column labels and the
outermost row labels in a table.
1. From the menus choose:
Format > Rotate Inner Column Labels
or
Format > Rotate Outer Row Labels
Only the innermost column labels and the outermost row labels can be rotated.
Sorting rows
To sort the rows of a pivot table:
1. Activate the table.
2. Select any cell in the column you want to use to sort on. To sort just a selected group of rows, select
two or more contiguous cells in the column you want to use to sort on.
3. From the menus, choose:
Edit > Sort rows
4. Select Ascending or Descending from the submenu.
• If the row dimension contains groups, sorting affects only the group that contains the selection.
• You cannot sort across group boundaries.
• You cannot sort tables with more than one item in the row dimension.
Note: This feature is not available in legacy tables.
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Related information
“Legacy tables” on page 141
Inserting rows and columns
To insert a row or column in a pivot table:
1. Activate the table.
2. Select any cell in the table.
3. From the menus, choose:
Insert Before
or
Insert After
From the submenu, choose:
Row
or
Column
• A plus sign (+) is inserted in each cell of the new row or column to prevent the new row or column from
being automatically hidden because it is empty.
• In a table with nested or layered dimensions, a column or row is inserted at every corresponding
dimension level.
Note: This feature is not available in legacy tables.
Related information
“Legacy tables” on page 141
Controlling display of variable and value labels
If variables contain descriptive variable or value labels, you can control the display of variable names and
labels and data values and value labels in pivot tables.
1. Activate the pivot table.
2. From the menus, choose:
View > Variable labels
or
View > Value labels
3. Select one of the follow options from the submenu:
• Name or Value. Only variable names (or values) are displayed. Descriptive labels are not displayed.
• Label. Only descriptive labels are displayed. Variable names (or values) are not displayed.
• Both. Both names (or values) and descriptive labels are displayed.
Note: This feature is not available for legacy tables.
To control the default label display for pivot tables and other output objects, use Edit>Options>Output.
Related information
“Legacy tables” on page 141
“Output options” on page 184
Changing the output language
To change the output language in a pivot table:
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1. Activate the table
2. From the menus, choose:
View > Language
3. Select one of the available languages.
Changing the language affects only text that is generated by the application, such as table titles, row and
column labels, and footnote text. Variable names and descriptive variable and value labels are not
affected.
Note: This feature is not available for legacy tables.
To control the default language for pivot tables and other output objects, use Edit>Options>Language.
Related information
“Legacy tables” on page 141
“Language options” on page 181
Navigating large tables
To use the navigation window to navigate large tables:
1. Activate the table.
2. From the menus choose:
View > Navigation
Undoing changes
You can undo the most recent change or all changes to an activated pivot table. Both actions apply only to
changes made since the most recent activation of the table.
To undo the most recent change:
1. From the menus, choose:
Edit > Undo
To undo all changes:
2. From the menus, choose:
Edit > Restore
Note: Edit > Restore is not available for legacy tables.
Working with layers
You can display a separate two-dimensional table for each category or combination of categories. The
table can be thought of as stacked in layers, with only the top layer visible.
Creating and displaying layers
To create layers:
1. Activate the pivot table.
2. If pivoting trays are not already on, from the Pivot Table menu, choose:
Pivot > Pivoting Trays
3. Drag an element from the row or column dimension into the layer dimension.
Moving elements to the layer dimension creates a multidimensional table, but only a single two-
dimensional "slice" is displayed. The visible table is the table for the top layer. For example, if a yes/no
categorical variable is in the layer dimension, then the multidimensional table has two layers: one for the
"yes" category and one for the "no" category.
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Changing the displayed layer
1. Choose a category from the drop-down list of layers (in the pivot table itself, not the pivoting tray).
Go to layer category
Go to Layer Category allows you to change layers in a pivot table. This dialog box is particularly useful
when there are many layers or the selected layer has many categories.
Showing and hiding items
Many types of cells can be hidden, including:
• Dimension labels
• Categories, including the label cell and data cells in a row or column
• Category labels (without hiding the data cells)
• Footnotes, titles, and captions
Hiding rows and columns in a table
Showing hidden rows and columns in a table
1. From the menus choose:
View > Show All Categories
This displays all hidden rows and columns in the table. (If Hide empty rows and columns is selected in
Table Properties for this table, a completely empty row or column remains hidden.)
Hiding and showing dimension labels
1. Select the dimension label or any category label within the dimension.
2. From the View menu or the pop-up menu choose Hide Dimension Label or Show Dimension Label.
Hiding and showing table titles
To hide a title:
1. Activate the pivot table.
2. Select the title.
3. From the View menu choose Hide.
To show hidden titles:
4. From the View menu choose Show All.
TableLooks
A TableLook is a set of properties that dene the appearance of a table. You can select a previously
dened TableLook or create your own TableLook.
• Before or after a TableLook is applied, you can change cell formats for individual cells or groups of cells
by using cell properties. The edited cell formats remain intact, even when you apply a new TableLook.
• Optionally, you can reset all cells to the cell formats that are dened by the current TableLook. This
option resets any cells that were edited. If As Displayed is selected in the TableLook Files list, any
edited cells are reset to the current table properties.
• Only table properties that are dened in the Table Properties dialog are saved in TableLooks.
TableLooks do not include individual cell modications.
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Note: TableLooks created in earlier versions of IBM SPSS Statistics cannot be used in version 16.0 or
later.
To apply a TableLook
1. Activate a pivot table.
2. From the menus, choose:
Format > TableLooks...
3. Select a TableLook from the list of les. To select a le from another directory, click Browse.
4. Click OK to apply the TableLook to the selected pivot table.
To edit or create a TableLook
1. In the TableLooks dialog box, select a TableLook from the list of les.
2. Click Edit Look.
3. Adjust the table properties for the attributes that you want, and then click OK.
4. Click Save Look to save the edited TableLook, or click Save As to save it as a new TableLook.
• Editing a TableLook affects only the selected pivot table. An edited TableLook is not applied to any
other tables that use that TableLook unless you select those tables and reapply the TableLook.
• Only table properties that are dened in the Table Properties dialog are saved in TableLooks.
TableLooks do not include individual cell modications.
Related information
Detailed examples
Table properties
Table Properties allows you to set general properties of a table, set cell styles for various parts of a table,
and save a set of those properties as a TableLook. You can:
• Control general properties, such as hiding empty rows or columns and adjusting printing properties.
• Control the format and position of footnote markers.
• Determine specic formats for cells in the data area, for row and column labels, and for other areas of
the table.
• Control the width and color of the lines that form the borders of each area of the table.
To change pivot table properties
1. Activate the pivot table.
2. From the menus choose:
Format > Table Properties...
3. Select a tab (General, Footnotes, Cell Formats, Borders, or Printing).
4. Select the options that you want.
5. Click OK or Apply.
The new properties are applied to the selected pivot table. To apply new table properties to a TableLook
instead of just the selected table, edit the TableLook (Format menu, TableLooks).
Table properties: general
Several properties apply to the table as a whole. You can:
• Show or hide empty rows and columns. (An empty row or column has nothing in any of the data cells.)
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• Control the default number of rows to display in long tables. To display all the rows in a table,
regardless of how long it is, clear Display table by rows. Note: This feature applies only to legacy
tables.
• Control the placement of row labels, which can be in the upper left corner or nested.
• Control maximum and minimum column width (expressed in points).
To change general table properties:
1. Click the General tab.
2. Select the options that you want.
3. Click OK or Apply.
Set rows to display
Note: This feature only applies to legacy tables.
By default, tables with many rows are displayed in sections of 100 rows. To control the number of rows
displayed in a table:
1. Select Display table by rows.
2. Click Set Rows to Display.
or
3. From the View menu of an activated pivot table, choose Display table by rows and Set Rows to
Display.
Rows to display. Controls the maximum number of rows to display at one time. Navigation controls allow
you move to different sections of the table. The minimum value is 10. The default is 100.
Widow/orphan tolerance. Controls the maximum number of rows of the inner most row dimension of the
table to split across displayed views of the table. For example, if there are six categories in each group of
the inner most row dimension, specifying a value of six would prevent any group from splitting across
displayed views. This setting can cause the total number of rows in a displayed view to exceed the
specied maximum number of rows to display.
Table properties: notes
The Notes tab of the Table Properties dialog controls footnote formatting and table comment text.
Footnotes. The properties of footnote markers include style and position in relation to text.
• The style of footnote markers is either numbers (1, 2, 3, ...) or letters (a, b, c, ...).
• The footnote markers can be attached to text as superscripts or subscripts.
Comment Text. You can add comment text to each table.
• Comment text is displayed in a tooltip when you hover over a table in the Viewer.
• Screen readers read the comment text when the table has focus.
• The tooltip in the Viewer displays only the rst 200 characters of the comment, but screen readers read
the entire text.
• When you export output to HTML, the comment text is used as alt text.
You can automatically add comments to all tables when they are created (Edit menu>Options>Pivot
Tables).
Table properties: cell formats
For formatting, a table is divided into areas: title, layers, corner labels, row labels, column labels, data,
caption, and footnotes. For each area of a table, you can modify the associated cell formats. Cell formats
include text characteristics (such as font, size, color, and style), horizontal and vertical alignment,
background colors, and inner cell margins.
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Cell formats are applied to areas (categories of information). They are not characteristics of individual
cells. This distinction is an important consideration when pivoting a table.
For example,
• If you specify a bold font as a cell format of column labels, the column labels will appear bold no matter
what information is currently displayed in the column dimension. If you move an item from the column
dimension to another dimension, it does not retain the bold characteristic of the column labels.
• If you make column labels bold simply by highlighting the cells in an activated pivot table and clicking
the Bold button on the toolbar, the contents of those cells will remain bold no matter what dimension
you move them to, and the column labels will not retain the bold characteristic for other items moved
into the column dimension.
To change cell formats:
1. Select the Cell Formats tab.
2. Select an Area from the drop-down list or click an area of the sample.
3. Select characteristics for the area. Your selections are reflected in the sample.
4. Click OK or Apply.
Alternating row colors
To apply a different background and/or text color to alternate rows in the Data area of the table:
1. Select Data from the Area drop-down list.
2. Select (check) Alternate row color in the Background Color group.
3. Select the colors to use for the alternate row background and text.
Alternate row colors affect only the Data area of the table. They do not affect row or column label areas.
Table properties: borders
For each border location in a table, you can select a line style and a color. If you select None as the style,
there will be no line at the selected location.
To change table borders:
1. Click the Borders tab.
2. Select a border location, either by clicking its name in the list or by clicking a line in the Sample area.
3. Select a line style or select None.
4. Select a color.
5. Click OK or Apply.
Table properties: printing
You can control the following properties for printed pivot tables:
• Print all layers or only the top layer of the table, and print each layer on a separate page.
• Shrink a table horizontally or vertically to t the page for printing.
• Control widow/orphan lines by controlling the minimum number of rows and columns that will be
contained in any printed section of a table if the table is too wide and/or too long for the dened page
size.
Note: If a table is too long to t on the current page because there is other output above it, but it will t
within the dened page length, the table is automatically printed on a new page, regardless of the
widow/orphan setting.
• Include continuation text for tables that don't t on a single page. You can display continuation text at
the bottom of each page and at the top of each page. If neither option is selected, the continuation text
will not be displayed.
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To control pivot table printing properties:
1. Click the Printing tab.
2. Select the printing options that you want.
3. Click OK or Apply.
Cell properties
Cell properties are applied to a selected cell. You can change the font, value format, alignment, margins,
and colors. Cell properties override table properties; therefore, if you change table properties, you do not
change any individually applied cell properties.
To change cell properties:
1. Activate a table and select the cell(s) in the table.
2. From the Format menu or the pop-up menu choose Cell Properties.
Font and background
The Font and Background tab controls the font style and color and background color for the selected cells
in the table.
Format value
The Format Value tab controls value formats for the selected cells. You can select formats for numbers,
dates, time, or currencies, and you can adjust the number of decimal digits that are displayed.
Note: The list of Currency formats contains Dollar format (numbers with a leading dollar sign) and ve
custom currency formats. By default, all custom currency formats are set to the default number format,
which contains no currency or other custom symbols. Use Edit>Options>Currency to dene custom
currency formats.
Alignment and margins
The Alignment and Margins tab controls horizontal and vertical alignment of values and top, bottom, left,
and right margins for the selected cells. Mixed horizontal alignment aligns the content of each cell
according to its type. For example, dates are right-aligned and text values are left-aligned.
Footnotes and captions
You can add footnotes and captions to a table. You can also hide footnotes or captions, change footnote
markers, and renumber footnotes.
Adding footnotes and captions
To add a caption to a table:
1. From the Insert menu choose Caption.
A footnote can be attached to any item in a table. To add a footnote:
1. Click a title, cell, or caption within an activated pivot table.
2. From the Insert menu choose Footnote.
3. Insert the footnote text in the provided area.
To hide or show a caption
To hide a caption:
1. Select the caption.
2. From the View menu choose Hide.
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To show hidden captions:
1. From the View menu choose Show All.
To hide or show a footnote in a table
To hide a footnote:
1. Right-click the cell that contains the footnote reference and select Hide Footnotes from the pop-up
menu
or
2. Select the footnote in the footnote area of the table and select Hide from the pop-up menu.
Note: For legacy tables, select the footnote area of the table, select Edit Footnote from the pop-up
menu, and then deselect (clear) the Visible property for any footnotes you want to hide.
If a cell contains multiple footnotes, use the latter method to selectively hide footnotes.
To hide all footnotes in the table:
1. Select all of the footnotes in the footnote area of the table (use click and drag or Shift+click to select
the footnotes) and select Hide from the View menu.
Note: For legacy tables, select the footnote area of the table and select Hide from the View menu.
To show hidden footnotes:
1. Select Show All Footnotes from the View menu.
Footnote marker
Footnote Marker changes the characters that can be used to mark a footnote. By default, standard
footnote markers are sequential letters or numbers, depending on the table properties settings. You can
also assign a special marker. Special markers are not affected when you renumber footnotes or switch
between numbers and letters for standard markers. The display of numbers or letters for standard
markers and the subscript or superscript position of footnote markers are controlled by the Footnotes tab
of the Table Properties dialog.
Note: For changing footnote markers in legacy tables, see “Editing footnotes in legacy tables” on page
138.
To change footnote markers:
1. Select a footnote.
2. From the Format menu, choose Footnote Marker.
Special markers are limited to 2 characters. Footnotes with special markers precede footnotes with
sequential letters or numbers in the footnote area of the table; so changing to a special marker can
reorder the footnote list.
Renumbering footnotes
When you have pivoted a table by switching rows, columns, and layers, the footnotes may be out of order.
To renumber the footnotes:
1. From the Format menu choose Renumber Footnotes.
Editing footnotes in legacy tables
For legacy tables, you can use the Edit Footnotes dialog to enter and modify footnote text and font
settings, change footnote markers, and selectively hide or delete footnotes.
When you insert a new footnote in a legacy table, the Edit Footnotes dialog automatically opens. To use
the Edit Footnotes dialog to edit existing footnotes (without creating a new footnote):
1. Double-click the footnote area of the table or from the menus choose: Format > Edit Footnote.
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Marker. By default, standard footnote markers are sequential letters or numbers, depending on the table
properties settings. To assign a special marker, simply enter the new marker value in the Marker column.
Special markers are not affected when you renumber footnotes or switch between numbers and letters
for standard markers. The display of numbers or letters for standard markers and the subscript or
superscript position of footnote markers are controlled by the Footnotes tab of the Table Properties
dialog. See the topic “Table properties: notes” on page 135 for more information.
To change a special marker back to a standard marker, right-click on the marker in the Edit Footnotes
dialog, select Footnote Marker from the pop-up menu, and select Standard marker in the Footnote
Marker dialog box.
Footnote. The content of the footnote. The display reflects the current font and background settings. The
font settings can be changed for individual footnotes using the Format subdialog. See the topic “Footnote
font and color settings” on page 139 for more information. A single background color is applied to all
footnotes and can be changed in the Font and Background tab of the Cell Properties dialog. See the topic
“ Font and background” on page 137 for more information.
Visible. All footnotes are visible by default. Deselect (clear) the Visible checkbox to hide a footnote.
Footnote font and color settings
For legacy tables, you can use the Format dialog to change the font family, style, size and color for one or
more selected footnotes:
1. In the Edit Footnotes dialog, select (click) one or more footnotes in the Footnotes grid.
2. Click the Format button.
The selected font family, style, size, and colors are applied to all the selected footnotes.
Background color, alignment, and margins can be set in the Cell Properties dialog and apply to all
footnotes. You cannot change these settings for individual footnotes. See the topic “ Font and
background” on page 137 for more information.
Data cell widths
Set Data Cell Width is used to set all data cells to the same width.
To set the width for all data cells:
1. From the menus choose:
Format > Set Data Cell Widths...
2. Enter a value for the cell width.
Changing column width
1. Click and drag the column border.
Displaying hidden borders in a pivot table
For tables without many visible borders, you can display the hidden borders. This can simplify tasks like
changing column widths.
1. From the View menu choose Gridlines.
Selecting rows, columns, and cells in a pivot table
You can select an entire row or column or a specied set of data and label cells.
To select multiple cells:
Select > Data and Label Cells
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Printing pivot tables
Several factors can affect the way that printed pivot tables look, and these factors can be controlled by
changing pivot table attributes.
• For multidimensional pivot tables (tables with layers), you can either print all layers or print only the top
(visible) layer. See the topic “Table properties: printing” on page 136
for more information.
• For long or wide pivot tables, you can automatically resize the table to t the page or control the
location of table breaks and page breaks. See the topic “Table properties: printing” on page 136 for
more information.
• For tables that are too wide or too long for a single page, you can control the location of table breaks
between pages.
Use Print Preview on the File menu to see how printed pivot tables will look.
Controlling table breaks for wide and long tables
Pivot tables that are either too wide or too long to print within the dened page size are automatically
split and printed in multiple sections. You can:
• Control the row and column locations where large tables are split.
• Specify rows and columns that should be kept together when tables are split.
• Rescale large tables to t the dened page size.
To specify row and column breaks for printed pivot tables:
1. Activate the pivot table.
2. Click any cell in the column to the left of where you want to insert the break, or click any cell in the row
before the row where you want to insert the break.
Note: For legacy tables, you must click a column label or row label cell.
3. From the menus, choose:
Format > Breakpoints > Vertical Breakpoint
or
Format > Breakpoints > Horizontal Breakpoint
Note: For legacy tables, choose Format > Break Here for both vertical and horizontal breakpoints.
To specify rows or columns to keep together:
1. Select the labels of the rows or columns that you want to keep together. Click and drag or Shift+click
to select multiple row or column labels.
2. From the menus, choose:
Format > Breakpoints > Keep Together
Note: For legacy tables, choose Format > Keep Together.
To view breakpoints and keep together groups:
1. From the menus, choose:
Format > Breakpoints > Display Breakpoints
Breakpoints are shown as vertical or horizontal lines. Keep together groups appear as grayed out
rectangular regions that are enclosed by a darker border.
Note: Displaying breakpoints and keep together groups is not supported for legacy tables.
To clear breakpoints and keep together groups
To clear a breakpoint:
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1. Click any cell in the column to the left of a vertical breakpoint, or click any cell in the row above a
horizontal breakpoint.
Note: For legacy tables, you must click a column label or row label cell.
2. From the menus, choose:
Format > Breakpoints > Clear Breakpoint or Group
Note: For legacy tables, choose Format > Remove Break Here.
To clear a keep together group:
3. Select the column or row labels that specify the group.
4. From the menus, choose:
Format > Breakpoints > Clear Breakpoint or Group
Note: For legacy tables, choose Format > Remove Keep Together.
All breakpoints and keep together groups are automatically cleared when you pivot or reorder any row or
column. This behavior does not apply to legacy tables.
Creating a chart from a pivot table
1. Double-click the pivot table to activate it.
2. Select the rows, columns, or cells you want to display in the chart.
3. Right-click anywhere in the selected area.
4. Choose Create Graph from the pop-up menu and select a chart type.
Legacy tables
You can choose to render tables as legacy tables (referred to as full-featured tables in release 19) which
are then fully compatible with IBM SPSS Statistics releases prior to 20. Legacy tables may render slowly
and are only recommended if compatibility with releases prior to 20 is required. For information on how
to create legacy tables, see “Pivot Tables options” on page 187.
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Chapter 12. Models
Some results are presented as models, which appear in the output Viewer as a special type of
visualization. The visualization displayed in the output Viewer is not the only view of the model that is
available. A single model contains many different views. You can activate the model in the Model Viewer
and interact with the model directly to display the available model views. You can also choose to print and
export all the views in the model.
Interacting with a model
To interact with a model, you rst activate it:
1. Double-click the model.
or
2. Right-click the model and from the pop-up menu choose Edit Content.
3. From the submenu choose In Separate Window.
Activating the model displays the model in the Model Viewer. See the topic “Working with the Model
Viewer” on page 143 for more information.
Working with the Model Viewer
The Model Viewer is an interactive tool for displaying the available model views and editing the look of the
model views. (For information about displaying the Model Viewer, see “Interacting with a model” on page
143 .) There are two different styles of Model Viewer:
• Split into main/auxiliary views. In this style the main view appears in the left part of the Model
Viewer. The main view displays some general visualization (for example, a network graph) for the
model. The main view itself may have more than one model view. The drop-down list below the main
view allows you to choose from the available main views.
The auxiliary view appears in the right part of the Model Viewer. The auxiliary view typically displays a
more detailed visualization (including tables) of the model compared to the general visualization in the
main view. Like the main view, the auxiliary view may have more than one model view. The drop-down
list below the auxiliary view allows you to choose from the available main views. The auxiliary can also
display specic visualizations for elements that are selected in the main view. For example, depending
on the type of model, you may be able to select a variable node in the main view to display a table for
that variable in the auxiliary view.
• One view at a time, with thumbnails. In this style there is only one view visible, and other views are
accessed via thumbnails on the left of the Model Viewer. Each view displays some visualization for the
model.
The specic visualizations that are displayed depend on the procedure that created the model. For
information about working with specic models, refer to the documentation for the procedure that
created the model.
Model view tables
Tables displayed in the Model Viewer are not pivot tables. You cannot manipulate these tables as you can
manipulate pivot tables.
Setting model properties
Within the Model Viewer, you can set specic properties for the model. See the topic “Model properties”
on page 144 for more information.
Copying model views
You can also copy individual model views within the Model Viewer. See the topic “Copying model views”
on page 144 for more information.
Model properties
Depending on your Model Viewer, choose:
File > Properties
or
File > Print View
Each model has associated properties that let you specify which views are printed from the output
Viewer. By default, only the view that is visible in the output Viewer is printed. This is always a main view,
and only one main view. You can also specify that all available model views are printed. These include all
the main views and all the auxiliary views (except for auxiliary views based on selection in the main view;
these are not printed). Note that you can also print individual model views within the Model Viewer itself.
See the topic “Printing a model” on page 144 for more information.
Copying model views
From the Edit menu within the Model Viewer, you can copy the currently displayed main view or the
currently display auxiliary view. Only one model view is copied. You can paste the model view into the
output Viewer, where the individual model view is subsequently rendered as a visualization that can be
edited in the Graphboard Editor. Pasting into the output Viewer allows you to display multiple model
views simultaneously. You can also paste into other applications, where the view may appear as an image
or a table depending on the target application.
Printing a model
Printing from the Model Viewer
You can print a single model view within the Model Viewer itself.
1. Activate the model in the Model Viewer. See the topic “Interacting with a model” on page 143 for more
information.
2. From the menus choose View > Edit Mode, if available.
3. On the General toolbar palette in the main or auxiliary view (depending on which one you want to
print), click the print icon. (If this palette is not displayed, choose Palettes>General from the View
menu.)
Note: If your Model Viewer does not support a print icon, then choose File > Print.
Printing from the output Viewer
When you print from the output Viewer, the number of views that are printed for a specic model depend
on the model's properties. The model can be set to print only the displayed view or all of the available
model views. See the topic “Model properties” on page 144 for more information.
Exporting a model
By default, when you export models from the output Viewer, inclusion or exclusion of model views is
controlled by the model properties for each model. For more information about model properties, see
“Model properties” on page 144 . On export, you can override this setting and include all model views or
only the currently visible model view. In the Export Output dialog box, click Change Options... in the
Document group. For more information about exporting and this dialog box, see “Export output” on page
120 . Note that all model views, including tables, are exported as graphics. Also note that auxiliary views
based on selections in the main view are never exported.
Saving elds used in the model to a new dataset
You can save elds used in the model to a new dataset.
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1. Activate the model in the Model Viewer. See the topic “Interacting with a model” on page 143 for more
information.
2. From the menus choose:
Generate > Field Selection (Model input and target)
Dataset name. Specify a valid dataset name. Datasets are available for subsequent use in the same
session but are not saved as les unless explicitly saved prior to the end of the session. Dataset names
must conform to variable naming rules. See the topic “Variable names” on page 46 for more information.
Saving predictors to a new dataset based on importance
You can save predictors to a new dataset based on the information in the predictor importance chart.
1. Activate the model in the Model Viewer. See the topic “Interacting with a model” on page 143 for more
information.
2. From the menus choose:
Generate > Field Selection (Predictor Importance)
Top number of variables. Includes or excludes the most important predictors up to the specied
number.
Importance greater than. Includes or excludes all predictors with relative importance greater than
the specied value.
3. After you click OK, the New Dataset dialog appears.
Dataset name. Specify a valid dataset name. Datasets are available for subsequent use in the same
session but are not saved as les unless explicitly saved prior to the end of the session. Dataset names
must conform to variable naming rules. See the topic “Variable names” on page 46 for more information.
Ensemble Viewer
Models for Ensembles
The model for an ensemble provides information about the component models in the ensemble and the
performance of the ensemble as a whole.
The main (view-independent) toolbar allows you to choose whether to use the ensemble or a reference
model for scoring. If the ensemble is used for scoring you can also select the combining rule. These
changes do not require model re-execution; however, these choices are saved to the model for scoring
and/or downstream model evaluation. They also affect PMML exported from the ensemble viewer.
Combining Rule. When scoring an ensemble, this is the rule used to combine the predicted values from
the base models to compute the ensemble score value.
• Ensemble predicted values for categorical targets can be combined using voting, highest probability, or
highest mean probability. Voting selects the category that has the highest probability most often across
the base models. Highest probability selects the category that achieves the single highest probability
across all base models. Highest mean probability selects the category with the highest value when the
category probabilities are averaged across base models.
• Ensemble predicted values for continuous targets can be combined using the mean or median of the
predicted values from the base models.
The default is taken from the specications made during model building. Changing the combining rule
recomputes the model accuracy and updates all views of model accuracy. The Predictor Importance chart
also updates. This control is disabled if the reference model is selected for scoring.
Show All Combining rules. When selected , results for all available combining rules are shown in the
model quality chart. The Component Model Accuracy chart is also updated to show reference lines for
each voting method.
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Model Summary
The Model Summary view is a snapshot, at-a-glance summary of the ensemble quality and diversity.
Quality. The chart displays the accuracy of the nal model, compared to a reference model and a naive
model. Accuracy is presented in larger is better format; the "best" model will have the highest accuracy.
For a categorical target, accuracy is simply the percentage of records for which the predicted value
matches the observed value. For a continuous target, accuracy is 1 minus the ratio of the mean absolute
error in prediction (the average of the absolute values of the predicted values minus the observed values)
to the range of predicted values (the maximum predicted value minus the minimum predicted value).
For bagging ensembles, the reference model is a standard model built on the whole training partition. For
boosted ensembles, the reference model is the rst component model.
The naive model represents the accuracy if no model were built, and assigns all records to the modal
category. The naive model is not computed for continuous targets.
Diversity. The chart displays the "diversity of opinion" among the component models used to build the
ensemble, presented in larger is more diverse format. It is a measure of how much predictions vary
across the base models. Diversity is not available for boosted ensemble models, nor is it shown for
continuous targets.
Predictor Importance
Typically, you will want to focus your modeling efforts on the predictor elds that matter most and
consider dropping or ignoring those that matter least. The predictor importance chart helps you do this by
indicating the relative importance of each predictor in estimating the model. Since the values are relative,
the sum of the values for all predictors on the display is 1.0. Predictor importance does not relate to
model accuracy. It just relates to the importance of each predictor in making a prediction, not whether or
not the prediction is accurate.
Predictor importance is not available for all ensemble models. The predictor set may vary across
component models, but importance can be computed for predictors used in at least one component
model.
Predictor Frequency
The predictor set can vary across component models due to the choice of modeling method or predictor
selection. The Predictor Frequency plot is a dot plot that shows the distribution of predictors across
component models in the ensemble. Each dot represents one or more component models containing the
predictor. Predictors are plotted on the y-axis, and are sorted in descending order of frequency; thus the
topmost predictor is the one that is used in the greatest number of component models and the
bottommost one is the one that was used in the fewest. The top 10 predictors are shown.
Predictors that appear most frequently are typically the most important. This plot is not useful for
methods in which the predictor set cannot vary across component models.
Component Model Accuracy
The chart is a dot plot of predictive accuracy for component models. Each dot represents one or more
component models with the level of accuracy plotted on the y-axis. Hover over any dot to obtain
information on the corresponding individual component model.
Reference lines. The plot displays color coded lines for the ensemble as well as the reference model and
naïve models. A checkmark appears next to the line corresponding to the model that will be used for
scoring.
Interactivity. The chart updates if you change the combining rule.
Boosted ensembles. A line chart is displayed for boosted ensembles.
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Component Model Details
The table displays information on component models, listed by row. By default, component models are
sorted in ascending model number order. You can sort the rows in ascending or descending order by the
values of any column.
Model. A number representing the sequential order in which the component model was created.
Accuracy. Overall accuracy formatted as a percentage.
Method. The modeling method.
Predictors. The number of predictors used in the component model.
Model Size. Model size depends on the modeling method: for trees, it is the number of nodes in the tree;
for linear models, it is the number of coefcients; for neural networks, it is the number of synapses.
Records. The weighted number of input records in the training sample.
Automatic Data Preparation
This view shows information about which elds were excluded and how transformed elds were derived
in the automatic data preparation (ADP) step. For each eld that was transformed or excluded, the table
lists the eld name, its role in the analysis, and the action taken by the ADP step. Fields are sorted by
ascending alphabetical order of eld names.
The action Trim outliers, if shown, indicates that values of continuous predictors that lie beyond a cutoff
value (3 standard deviations from the mean) have been set to the cutoff value.
Split Model Viewer
The Split Model Viewer lists the models for each split, and provides summaries about the split models.
Split. The column heading shows the eld(s) used to create splits, and the cells are the split values.
Double-click any split to open a Model Viewer for the model built for that split.
Accuracy. Overall accuracy formatted as a percentage.
Model Size. Model size depends on the modeling method: for trees, it is the number of nodes in the tree;
for linear models, it is the number of coefcients; for neural networks, it is the number of synapses.
Records. The weighted number of input records in the training sample.
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Chapter 13. Automated Output Modication
Automated output modication applies formatting and other changes to the contents of the active Viewer
window. Changes that can be applied include:
• All or selected viewer objects
• Selected types of output objects (for example, charts, logs, pivot tables)
• Pivot table content based on conditional expressions
• Outline (navigation) pane content
The types of changes you can make include:
• Delete objects
• Index objects (add a sequential numbering scheme)
• Change the visible property of objects
• Change the outline label text
• Transpose rows and columns in pivot tables
• Change the selected layer of pivot tables
• Change the formatting of selected areas or specic cells in a pivot table based on conditional
expressions (for example, make all signicance values less than 0.05 bold)
To specify automated output modication:
1. From the menus, choose:Utilities > Style Output
2. Select one or more objects in the Viewer.
3. Select the options you want in the Select dialog. (You can also select objects before you open the
dialog.)
4. Select the output changes you want in the Style Output dialog.
Style Output: Select
The Style Output: Select dialog species basic selection criteria for changes that you specify on the Style
Output dialog.
You can also select objects in the Viewer after opening the Style Output: Select dialog.
Selected only. Changes are applied only to the selected objects that meet the specied criteria.
• Select as last command. If selected, changes are only applied to the output from the last procedure. If
not selected, changes are applied to the specic instance of the procedure. For example, if there are
three instances of the Frequencies procedure and you select the second instance, changes are applied
only to that instance. If you paste the syntax based on your selections, this option selects the second
instance of that procedure. If output from multiple procedures is selected, this option applies only to
the procedure for which the output is the last block of output in the Viewer.
• Select as a group. If selected, all of the objects in the selection are treated as a single group on the
main Style Output dialog. If not selected, the selected objects are treated as individual selections, and
you can set the properties for each object individually.
All objects of this type. Changes are applied to all objects of the selected type that meet the specied
criteria. This option is only available if there is a single object type selected in the Viewer. Object types
include tables, warnings, logs, charts, tree diagrams, text, models, and outline headers.
All objects of this sub-type. Changes are applied to all tables of the same subtype as the selected tables
that meet the specied criteria. This option is only available if there is a single table subtype selected in
the Viewer. For example, the selection can include two separate Frequencies tables, but not a
Frequencies table and a Descriptives table.
Objects with a similar name. Changes are applied to all objects with a similar name that meet the
specied criteria.
• Criteria. The options are Contains, Exactly, Starts with, and Ends with.
• Value. The name as it is displayed in the outline pane of the Viewer.
• Update. Selects all the objects in the Viewer that meet the specied criteria for the specied value.
Style Output
The Style Output dialog species the changes you want to make to the selected output objects in the
Viewer.
Create a Backup of the Output. Changes made by the automated output modication process cannot be
undone. To preserve the original Viewer document, create a backup copy.
Selections and Properties
The list of objects or groups of objects that you can modify is determined by the objects you select in the
Viewer and the selections you make in the Style Output: Select dialog.
Selection. The name of the selected procedure or group of object types. When there is an integer in
parentheses after the selection text, changes are applied only to that instance of that procedure in the
sequence of objects in the Viewer. For example, "Frequencies(2)" applies change only to the second
instance of the Frequencies procedure in the Viewer output.
Type. The type of object. For example, log, title, table, chart. For individual table types, the table subtype
is also displayed.
Delete. Species whether the selection should be deleted.
Visible. Species whether the selection should be visible or hidden. The default option is "As Is," which
means that current visibility property of the selection is preserved.
Properties. A summary of changes to apply to the selection.
Add. Adds a row to the list and opens the Style Output: Select dialog. You can select other objects in the
Viewer and specify the selection conditions.
Duplicate. Duplicates the selected row.
Move Up and Move Down. Moves the selected row up or down in the list. The order can be important
since changes specied in subsequent rows can overwrite changes that are specied in previous rows.
Create a report of the property changes. Displays a table that summarizes the changes in the Viewer.
Object Properties
You specify the changes that you want to make to each selection from the Selections and Properties
section in the Object Properties section. The available properties are determined by the selected row in
the Selections and Properties section.
Command. The name of the procedure if the selection refers to a single procedure. The selection can
include multiple instances of the same procedure.
Type. The type of object.
Subtype. If the selection refers to a single table type, the table subtype name is displayed.
Outline Label. The label in the outline pane that is associated with the selection. You can replace the
label text or add information to the label. For more information, see the topic Style Output: Labels and
Text.
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Indexing Format. Adds a sequential number, letter, or roman numeral to the objects in the selection. For
more information, see the topic Style Output: Indexing.
Table Title. The title of table or tables. You can replace the title or add information to the title. For more
information, see the topic Style Output: Labels and Text.
TableLook. The TableLook used for tables. For more information, see the topic Style Output: TableLooks.
Transpose. Transposes rows and columns in tables.
Top Layer. For tables with layers, the category that is displayed for each layer.
Conditional styling. Conditional style changes for tables. For more information, see the topic Table Style.
Sort. Sorts table contents by the values of the selected column label. The available column labels are
displayed in a dropdown list. This option is only available if the selection contains a single table subtype.
Sort Direction. Species the sort direction for tables.
Comment Text. You can add comment text to each table.
• Comment text is displayed in a tooltip when you hover over a table in the Viewer.
• Screen readers read the comment text when the table has focus.
• The tooltip in the Viewer displays only the rst 200 characters of the comment, but screen readers read
the entire text.
• When you export output to HTML, the comment text is used as alt text.
Contents. The text of logs, titles, and text objects. You can replace the text or add information to the text.
For more information, see the topic Style Output: Labels and Text.
Font. The font for logs, titles, and text objects.
Font Size. The font size for logs, titles, and text objects.
Text Color. Text color for logs, titles, and text objects.
Chart Template. The chart template that is used for charts, except charts that are created with the
Graphboard Template Chooser.
Graphboard Stylesheet. The style sheet used for charts that are created with the Graphboard Template
Chooser.
Size. The size of charts and tree diagrams.
Special Variables in Comment Text
You can include special variables to insert date, time, and other values in the Comment Text eld.
)DATE
Current date in the form dd-mmm-yyyy.
)ADATE
Current date in the form mm/dd/yyyy.
)SDATE
Current date in the form yyyy/mm/dd.
)EDATE
Current date in the form dd.mm.yyyy.
)TIME
Current 12-hour clock time in the form hh:mm:ss.
)ETIME
Current 24-hour clock time in the form hh:mm:ss.
)INDEX
The dened index value. For more information, see the topic Style Output: Indexing.
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)TITLE
The text of the outline label for the table.
)PROCEDURE
The name of the procedure that created the table.
)DATASET
The name of the dataset used to create the table.
\n
Inserts a line break.
Style Output: Labels and Text
The Style Output: Labels and Text dialog replaces or adds text to outline labels, text objects, and table
titles. It also species the inclusion and placement of index values for outline labels, text objects, and
table titles.
Add text to the label or text object.. You can add the text before or after the existing text or replace the
existing text.
Add indexing. Adds a sequential letter, number, or roman numeral. You can place the index before or
after the text. You can also specify one or more characters that are used as a separator between the text
and the index. For information about index formatting, see the topic Style Output: Indexing.
Style Output: Indexing
The Style Output: Indexing dialog species the index format and the starting value.
Type: The sequential index values can be numbers, lower or uppercase letters, lower or uppercase roman
numerals.
Starting value. The starting value can be any value that is valid for the type that is selected.
To display index values in the output, you must select Add indexing in the Style Output: Labels and Text
dialog for the selected object type.
• For outline labels, select Outline label in the Properties column in the Style Output dialog.
• For table titles, select Table Title in the Properties column in the Style Output dialog.
• For text objects, select Contents in the Properties column in the Style Output dialog.
Style Output: TableLooks
A TableLook is a set of properties that dene the appearance of a table. You can select a previously
dened TableLook or create your own TableLook.
• Before or after a TableLook is applied, you can change cell formats for individual cells or groups of cells
by using cell properties. The edited cell formats remain intact, even when you apply a new TableLook.
• Optionally, you can reset all cells to the cell formats that are dened by the current TableLook. This
option resets any cells that were edited. If As Displayed is selected in the TableLook Files list, any
edited cells are reset to the current table properties.
• Only table properties that are dened in the Table Properties dialog are saved in TableLooks.
TableLooks do not include individual cell modications.
Style Output: Size
The Style Output: Size dialog controls the size of charts and tree diagrams. You can specify the height and
width in centimeters, inches, or points.
Table Style
The Table Style dialog species conditions for automatically changing properties of pivot tables based on
specic conditions. For example, you can make all signicance values less than 0.05 bold and red. The
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Table Style dialog can be accessed from the Style Output dialog or from the dialogs for specic statistical
procedures.
• The Table Style dialog can be accessed from the Style Output dialog or from the dialogs for specic
statistical procedures.
• The statistical procedure dialogs that support the Table Style dialog are Bivariate Correlations,
Crosstabs, Custom Tables, Descriptives, Frequencies, Logistic Regression, Linear Regression, and
Means.
Table. The table or tables to which the conditions apply. When you access this dialog from the Style
Output dialog, the only choice is "All applicable tables." When you access this dialog from a statistical
procedure dialog, you can select the table type from a list of procedure-specic tables.
Value. The row or column label value that denes the area of the table to search for values that meet the
conditions. You can select a value from the list or enter a value. The values in the list are not affected by
the output language and apply to numerous variations of the value. The values available in the list depend
on the table type.
• Count. Rows or columns with any of these labels or the equivalent in the current output language:
"Frequency", "Count", "N".
• Mean. Rows or columns with the label "Mean" or the equivalent in the current output language.
• Median Rows or columns with the label "Median" or the equivalent in the current output language.
• Percent. Rows or columns with the label "Percent" or the equivalent in the current output language.
• Residual. Rows or columns with any of these labels or the equivalent in the current output language:
"Resid", "Residual", "Std. Residual".
• Correlation. Rows or columns with any of these labels or the equivalent in the current output language:
"Adjusted R Square", "Correlation Coefcient", "Correlations", "Pearson Correlation", "R Square".
• Signicance. Rows or columns with any of these labels or the equivalents in the current output
language: "Approx Sig.", "Asymp. Sig (2-sided)", "Exact Sig.", "Exact Sig. (1-sided)", "Exact Sig. (2-
sided)", "Sig.", "Sig. (1-tailed)", "Sig. (2-tailed)"
• All data cells. All data cells are included.
Dimension. Species whether to search rows, columns, or both for a label with the specied value.
Condition. Species the condition to nd. For more information, see the topic Table Style: Condition.
Formatting. Species the formatting to apply to the table cells or areas that meet the condition. For more
information, see the topic Table Style: Format.
Add. Adds a row to the list.
Duplicate. Duplicates the selected row.
Move Up and Move Down. Moves the selected row up or down in the list. The order can be important
since changes specied in subsequent rows can overwrite changes that are specied in previous rows.
Create a report of the conditional styling. Displays a table that summarizes the changes in the Viewer.
This option is available when the Table Style dialog is accessed from a statistical procedure dialog. The
Style Output dialog has a separate option to create a report.
Table Style: Condition
The Table Style: Condition dialog species the conditions under which the changes are applied. There are
two options.
• To all values of this type. The only condition is the value specied in the Value column in the Table
Style dialog. This option is the default.
• Based on the following conditions. Within the table area specied by the Value and Dimension
columns in the Table Style dialog, nd values that meet the specied conditions.
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Values. The list contains comparison expressions, such as Exactly, Less than, Greater Than, and
Between.
• Absolute value is available for comparison expressions that only require one value. For example, you
could nd correlations with an absolute value greater than 0.5.
• Top and Bottom are the highest and lowest n values in the specied table area. The value for Number
must be an integer.
• System-missing. Finds system-missing values in the specied table area.
Table Style: Format
The Table Style: Format dialog species changes to apply, based on the conditions specied in the Table
Style: Conditions dialog.
Use TableLook defaults. If no previous format changes have been made, either manually or by
automated output modication, this is equivalent to making no format changes. If previous changes have
been made, this removes those changes and restores the affected areas of the table to their default
format.
Apply new formatting. Applies the specied format changes. Format changes include font style and
color, background color, format for numeric values (including dates and times), and number of decimals
displayed.
Apply to. Species the area of the table to which to apply the changes.
• Cells only. Applies changes only to table cells that meet the condition.
• Entire column. Applies changes to the entire column that contains a cell that meet the condition. This
option includes the column label.
• Entire row. Applies changes to the entire row that contains a cell that meets the condition. This option
includes the row label.
Replace value. Replaces values with the specied new value. For Cells only, this option replaces
individual cell values that meet the condition. For Entire row and Entire column, this option replaces all
values in the row or column.
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Chapter 14. Working with Command Syntax
The powerful command language allows you to save and automate many common tasks. It also provides
some functionality not found in the menus and dialog boxes.
Most commands are accessible from the menus and dialog boxes. However, some commands and options
are available only by using the command language. The command language also allows you to save your
jobs in a syntax le so that you can repeat your analysis at a later date or run it in an automated job with
the a production job.
A syntax le is simply a text le that contains commands. While it is possible to open a syntax window
and type in commands, it is often easier if you let the software help you build your syntax le using one of
the following methods:
• Pasting command syntax from dialog boxes
• Copying syntax from the output log
• Copying syntax from the journal le
Detailed command syntax reference information is available in two forms: integrated into the overall Help
system and as a separate PDF le, called the Command Syntax Reference, also available from the Help
menu. Context-sensitive Help for the current command in a syntax window is available by pressing the F1
key.
Syntax Rules
When you run commands from a command syntax window during a session, you are running commands in
interactive mode.
The following rules apply to command specications in interactive mode:
• Each command must start on a new line. Commands can begin in any column of a command line and
continue for as many lines as needed. The exception is the END DATA command, which must begin in
the rst column of the rst line after the end of data.
• Each command should end with a period as a command terminator. It is best to omit the terminator on
BEGIN DATA, however, so that inline data are treated as one continuous specication.
• The command terminator must be the last nonblank character in a command.
• In the absence of a period as the command terminator, a blank line is interpreted as a command
terminator.
Note: For compatibility with other modes of command execution (including command les run with
INSERT or INCLUDE commands in an interactive session), each line of command syntax should not
exceed 256 characters.
• Most subcommands are separated by slashes (/). The slash before the rst subcommand on a
command is usually optional.
• Variable names must be spelled out fully.
• Text included within apostrophes or quotation marks must be contained on a single line.
• A period (.) must be used to indicate decimals, regardless of your regional or locale settings.
• Variable names ending in a period can cause errors in commands created by the dialog boxes. You
cannot create such variable names in the dialog boxes, and you should generally avoid them.
Command syntax is case insensitive, and three- or four-letter abbreviations can be used for many
command specications. You can use as many lines as you want to specify a single command. You can
add space or break lines at almost any point where a single blank is allowed, such as around slashes,
parentheses, arithmetic operators, or between variable names. For example,
FREQUENCIES
VARIABLES=JOBCAT GENDER
/PERCENTILES=25 50 75
/BARCHART.
and
freq var=jobcat gender /percent=25 50 75 /bar.
are both acceptable alternatives that generate the same results.
INCLUDE Files
For command les run via the INCLUDE command, batch mode syntax rules apply.
The following rules apply to command specications in batch mode:
• All commands in the command le must begin in column 1. You can use plus (+) or minus (–) signs in
the rst column if you want to indent the command specication to make the command le more
readable.
• If multiple lines are used for a command, column 1 of each continuation line must be blank.
• Command terminators are optional.
• A line cannot exceed 256 characters; any additional characters are truncated.
Unless you have existing command les that already use the INCLUDE command, you should probably
use the INSERT command instead, since it can accommodate command les that conform to either set of
rules. If you generate command syntax by pasting dialog box choices into a syntax window, the format of
the commands is suitable for any mode of operation. See the Command Syntax Reference (available in
PDF format from the Help menu) for more information.
Pasting Syntax from Dialog Boxes
The easiest way to build a command syntax le is to make selections in dialog boxes and paste the syntax
for the selections into a syntax window. By pasting the syntax at each step of a lengthy analysis, you can
build a job le that allows you to repeat the analysis at a later date or run an automated job with the
Production Facility.
In the syntax window, you can run the pasted syntax, edit it, and save it in a syntax le.
To Paste Syntax from Dialog Boxes
1. Open the dialog box and make the selections that you want.
2. Click Paste.
The command syntax is pasted to the designated syntax window. If you do not have an open syntax
window, a new syntax window opens automatically, and the syntax is pasted there. By default, the syntax
is pasted after the last command. You can choose to have syntax pasted at the position of the cursor or to
overwrite selected syntax. The setting is specied from the Syntax Editor tab in the Options dialog box.
Copying Syntax from the Output Log
You can build a syntax le by copying command syntax from the log that appears in the Viewer. To use
this method, you must select Display commands in the log in the Viewer settings (Edit menu, Options,
Viewer tab) before running the analysis. Each command will then appear in the Viewer along with the
output from the analysis.
In the syntax window, you can run the pasted syntax, edit it, and save it in a syntax le.
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To Copy Syntax from the Output Log
1. Before running the analysis, from the menus choose:
Edit > Options...
2. On the Viewer tab, select Display commands in the log.
As you run analyses, the commands for your dialog box selections are recorded in the log.
3. Open a previously saved syntax le or create a new one. To create a new syntax le, from the menus
choose:
File > New > Syntax
4. In the Viewer, double-click a log item to activate it.
5. Select the text that you want to copy.
6. From the Viewer menus choose:
Edit > Copy
7. In a syntax window, from the menus choose:
Edit > Paste
Using the Syntax Editor
The Syntax Editor provides an environment specically designed for creating, editing, and running
command syntax. The Syntax Editor features:
• Auto-Completion. As you type, you can select commands, subcommands, keywords, and keyword
values from a context-sensitive list. You can choose to be prompted automatically with the list or
display the list on demand.
• Color Coding. Recognized elements of command syntax (commands, subcommands, keywords, and
keyword values) are color coded so, at a glance, you can spot unrecognized terms. Also, a number of
common syntactical errors--such as unmatched quotes--are color coded for quick identication.
• Breakpoints. You can stop execution of command syntax at specied points, allowing you to inspect
the data or output before proceeding.
• Bookmarks. You can set bookmarks that allow you to quickly navigate large command syntax les.
• Auto-Indentation. You can automatically format your syntax with an indentation style similar to syntax
pasted from a dialog box.
• Step Through. You can step through command syntax one command at a time, advancing to the next
command with a single click.
Note: When working with right to left languages, it is recommended to check the Optimize for right to left
languages box on the Syntax Editor tab in the Options dialog box.
Syntax Editor Window
The Syntax Editor window is divided into four areas:
• The editor pane is the main part of the Syntax Editor window and is where you enter and edit command
syntax.
• The gutter is adjacent to the editor pane and displays information such as line numbers and breakpoint
positions.
• The navigation pane is to the left of the gutter and editor pane and displays a list of all commands in the
Syntax Editor window and provides single click navigation to any command.
• The error pane is below the editor pane and displays runtime errors.
Gutter Contents
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157
Line numbers, breakpoints, bookmarks, command spans, and a progress indicator are displayed in the
gutter to the left of the editor pane in the syntax window.
• Line numbers do not account for any external les referenced in INSERT and INCLUDE commands. You
can show or hide line numbers by choosing View > Show Line Numbers from the menus.
• Breakpoints stop execution at specied points and are represented as a red circle adjacent to the
command on which the breakpoint is set.
• Bookmarks mark specic lines in a command syntax le and are represented as a square enclosing the
number (1-9) assigned to the bookmark. Hovering over the icon for a bookmark displays the number of
the bookmark and the name, if any, assigned to the bookmark.
• Command spans are icons that provide visual indicators of the start and end of a command. You can
show or hide command spans by choosing View > Show Command Spans from the menus.
• The progress of a given syntax run is indicated with a downward pointing arrow in the gutter, stretching
from the rst command run to the last command run. This is most useful when running command
syntax containing breakpoints and when stepping through command syntax. See the topic “Running
Command Syntax” on page 163 for more information.
Navigation Pane
The navigation pane contains a list of all recognized commands in the syntax window, displayed in the
order in which they occur in the window. Clicking on a command in the navigation pane positions the
cursor at the start of the command.
• You can use the Up and Down arrow keys to move through the list of commands or click a command to
navigate to it. A double click will select the command.
• Command names for commands containing certain types of syntactical errors--such as unmatched
quotes--are colored red and in bold text by default. See the topic “Color Coding” on page 159
for more
information.
• The rst word of each line of unrecognized text is shown in gray.
• You can show or hide the navigation pane by choosing View > Show Navigation Pane from the menus.
Error Pane
The error pane displays runtime errors from the most previous run.
• The information for each error contains the starting line number of the command containing the error.
• You can use the Up and Down arrow keys to move through the list of errors.
• Clicking on an entry in the list will position the cursor on the rst line of the command that generated
the error.
• You can show or hide the error pane by choosing View > Show Error Pane from the menus.
Using Multiple Views
You can split the editor pane into two panes arranged with one above the other.
1. From the menus choose:
Window > Split
Actions in the navigation and error panes--such as clicking on an error--act on the pane where the cursor
is positioned.
You can remove the splitter by double-clicking it or choosing Window > Remove Split.
Terminology
Commands. The basic unit of syntax is the command. Each command begins with the command name,
which consists of one, two, or three words--for example, DESCRIPTIVES, SORT CASES, or ADD VALUE
LABELS.
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Subcommands. Most commands contain subcommands. Subcommands provide for additional
specications and begin with a forward slash followed by the name of the subcommand.
Keywords. Keywords are xed terms that are typically used within a subcommand to specify options
available for the subcommand.
Keyword Values. Keywords can have values such as a xed term that species an option or a numeric
value.
Example
CODEBOOK gender jobcat salary
/VARINFO VALUELABELS MISSING
/OPTIONS VARORDER=MEASURE.
• The name of the command is CODEBOOK.
• VARINFO and OPTIONS are subcommands.
• VALUELABELS, MISSING, and VARORDER are keywords.
• MEASURE is a keyword value associated with VARORDER.
Auto-Completion
The Syntax Editor provides assistance in the form of auto-completion of commands, subcommands,
keywords, and keyword values. By default, you are prompted with a context-sensitive list of available
terms as you type. Pressing Enter or Tab will insert the currently highlighted item in the list at the position
of the cursor. You can display the list on demand by pressing Ctrl+Spacebar and you can close the list by
pressing the Esc key.
The Auto Complete menu item on the Tools menu toggles the automatic display of the auto-complete list
on or off. You can also enable or disable automatic display of the list from the Syntax Editor tab in the
Options dialog box. Toggling the Auto Complete menu item overrides the setting on the Options dialog but
does not persist across sessions.
Note: The auto-completion list will close if a space is entered. For commands consisting of multiple
words--such as ADD FILES--select the command before entering any spaces.
Color Coding
The Syntax Editor color codes recognized elements of command syntax, such as commands and
subcommands, as well as various syntactical errors like unmatched quotes or parentheses. Unrecognized
text is not color coded.
Commands. By default, recognized commands are colored blue and in bold text. If, however, there is a
recognized syntactical error within the command--such as a missing parenthesis--the command name is
colored red and in bold text by default.
Note: Abbreviations of command names--such as FREQ for FREQUENCIES--are not colored, but such
abbreviations are valid.
Subcommands. Recognized subcommands are colored green by default. If, however, the subcommand is
missing a required equals sign or an invalid equals sign follows it, the subcommand name is colored red
by default.
Keywords. Recognized keywords are colored maroon by default. If, however, the keyword is missing a
required equals sign or an invalid equals sign follows it, the keyword is colored red by default.
Keyword values. Recognized keyword values are colored orange by default. User-specied values of
keywords such as integers, real numbers, and quoted strings are not color coded.
Comments. Text within a comment is colored gray by default.
Quotes. Quotes and text within quotes are colored black by default.
Syntactical Errors. Text associated with the following syntactical errors is colored red by default.
Chapter 14. Working with Command Syntax
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• Unmatched Parentheses, Brackets, and Quotes. Unmatched parentheses and brackets within
comments and quoted strings are not detected. Unmatched single or double quotes within quoted
strings are syntactically valid.
Certain commands contain blocks of text that are not command syntax--such as BEGIN DATA-END
DATA, BEGIN GPL-END GPL, and BEGIN PROGRAM-END PROGRAM. Unmatched values are not
detected within such blocks.
• Long lines. Long lines are lines containing more than 251 characters.
• End statements. Several commands require either an END statement prior to the command terminator
(for example, BEGIN DATA-END DATA) or require a matching END command at some point later in the
command stream (for example, LOOP-END LOOP). In both cases, the command will be colored red, by
default, until the required END statement is added.
Note: You can navigate to the next or previous syntactical error by choosing Next Error or Previous error
from the Validation Errors submenu of the Tools menu.
From the Syntax Editor tab in the Options dialog box, you can change default colors and text styles and
you can turn color coding off or on. You can also turn color coding of commands, subcommands,
keywords, and keyword values off or on by choosing Tools > Color Coding from the menus. You can turn
color coding of syntactical errors off or on by choosing Tools > Validation. Choices made on the Tools
menu override settings in the Options dialog box but do not persist across sessions.
Note: Color coding of command syntax within macros is not supported.
Breakpoints
Breakpoints allow you to stop execution of command syntax at specied points within the syntax window
and continue execution when ready.
• Breakpoints are set at the level of a command and stop execution prior to running the command.
• Breakpoints cannot occur within LOOP-END LOOP, DO IF-END IF, DO REPEAT-END REPEAT, INPUT
PROGRAM-END INPUT PROGRAM, and MATRIX-END MATRIX blocks. They can, however, be set at the
beginning of such blocks and will stop execution prior to running the block.
• Breakpoints cannot be set on lines containing non-IBM SPSS Statistics command syntax, such as occur
within BEGIN PROGRAM-END PROGRAM, BEGIN DATA-END DATA, and BEGIN GPL-END GPL blocks.
• Breakpoints are not saved with the command syntax le and are not included in copied text.
• By default, breakpoints are honored during execution. You can toggle whether breakpoints are honored
or not from Tools > Honor Breakpoints.
To Insert a Breakpoint
1. Click anywhere in the gutter to the left of the command text.
or
2. Position the cursor within the command.
3. From the menus choose:
Tools > Toggle Breakpoint
The breakpoint is represented as a red circle in the gutter to the left of the command text and on the
same line as the command name.
Clearing Breakpoints
To clear a single breakpoint:
1. Click the icon representing the breakpoint in the gutter to the left of the command text.
or
2. Position the cursor within the command.
3. From the menus choose:
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Tools > Toggle Breakpoint
To clear all breakpoints:
4. From the menus choose:
Tools > Clear All Breakpoints
See “Running Command Syntax” on page 163 for information about the run-time behavior in the
presence of breakpoints.
Bookmarks
Bookmarks allow you to quickly navigate to specied positions in a command syntax le. You can have up
to 9 bookmarks in a given le. Bookmarks are saved with the le, but are not included when copying text.
To Insert a Bookmark
1. Position the cursor on the line where you want to insert the bookmark.
2. From the menus choose:
Tools > Toggle Bookmark
The new bookmark is assigned the next available number, from 1 to 9. It is represented as a square
enclosing the assigned number and displayed in the gutter to the left of the command text.
Clearing Bookmarks
To clear a single bookmark:
1. Position the cursor on the line containing the bookmark.
2. From the menus choose:
Tools > Toggle Bookmark
To clear all bookmarks:
1. From the menus choose:
Tools > Clear All Bookmarks
Renaming a Bookmark
You can associate a name with a bookmark. This is in addition to the number (1-9) assigned to the
bookmark when it was created.
1. From the menus choose:
Tools > Rename Bookmark
2. Enter a name for the bookmark and click OK.
The specied name replaces any existing name for the bookmark.
Navigating with Bookmarks
To navigate to the next or previous bookmark:
1. From the menus choose:
Tools > Next Bookmark
or
Tools > Previous Bookmark
To navigate to a specic bookmark:
1. From the menus choose:
Tools > Go To Bookmark
2. Select the bookmark.
Chapter 14. Working with Command Syntax
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Commenting or Uncommenting Text
You can comment out entire commands as well as text that is not recognized as command syntax and you
can uncomment text that has previously been commented out.
To comment out text
1. Select the text. Note that a command will be commented out if any part of it is selected.
2. From the menus choose:
Tools > Toggle Comment Selection
You can comment out a single command by positioning the cursor anywhere within the command and
choosing Tools > Toggle Comment Selection.
To uncomment text
1. Select the text to uncomment. Note that a command will be uncommented if any part of it is selected.
2. From the menus choose:
Tools > Toggle Comment Selection
You can uncomment a single command by positioning the cursor anywhere within the command and
choosing Tools > Toggle Comment Selection. Note that this feature will not remove comments within a
command (text set off by /* and */) or comments created with the COMMENT keyword.
Formatting Syntax
You can indent or outdent selected lines of syntax and you can automatically indent selections so that the
syntax is formatted in a manner similar to syntax pasted from a dialog box.
• The default indent is four spaces and applies to indenting selected lines of syntax as well as to
automatic indentation. You can change the indent size from the Syntax Editor tab in the Options dialog
box.
• Note that using the Tab key in the Syntax Editor does not insert a tab character. It inserts a space.
To indent text
1. Select the text or position the cursor on a single line that you want to indent.
2. From the menus choose:
Tools > Indent Syntax > Indent
You can also indent a selection or line by pressing the Tab key.
To outdent text
1. Select the text or position the cursor on a single line that you want to outdent.
2. From the menus choose:
Tools > Indent Syntax > Outdent
To automatically indent text
1. Select the text.
2. From the menus choose:
Tools > Indent Syntax > Auto Indent
When you automatically indent text, any existing indentation is removed and replaced with the
automatically generated indents. Note that automatically indenting code within a BEGIN PROGRAM block
may break the code if it depends on specic indentation to function, such as Python code containing
loops and conditional blocks.
Syntax formatted with the auto-indent feature may not run in batch mode. For example, auto-indenting an
INPUT PROGRAM-END INPUT PROGRAM, LOOP-END LOOP, DO IF-END IF or DO REPEAT-END
REPEAT block will cause the syntax to fail in batch mode because commands in the block will be indented
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and will not start in column 1 as required for batch mode. You can, however, use the -i switch in batch
mode to force the Batch Facility to use interactive syntax rules. See the topic “Syntax Rules” on page 155
for more information.
Running Command Syntax
1. Highlight the commands that you want to run in the syntax window.
2. Click the Run button (the right-pointing triangle) on the Syntax Editor toolbar. It runs the selected
commands or the command where the cursor is located if there is no selection.
or
3. Choose one of the items from the Run menu.
• All. Runs all commands in the syntax window, honoring any breakpoints.
• Selection. Runs the currently selected commands, honoring any breakpoints. This includes any partially
highlighted commands. If there is no selection, the command where the cursor is positioned is run.
• To End. Runs all commands starting from the rst command in the current selection to the last
command in the syntax window, honoring any breakpoints. If nothing is selected, the run starts from
the command where the cursor is positioned.
• Step Through. Runs the command syntax one command at a time starting from the rst command in
the syntax window (Step Through From Start) or from the command where the cursor is positioned
(Step Through From Current). If there is selected text, the run starts from the rst command in the
selection. After a given command has run, the cursor advances to the next command and you continue
the step through sequence by choosing Continue.
LOOP-END LOOP, DO IF-END IF, DO REPEAT-END REPEAT, INPUT PROGRAM-END INPUT
PROGRAM, and MATRIX-END MATRIX blocks are treated as single commands when using Step Through.
You can not step into one of these blocks.
• Continue. Continues a run stopped by a breakpoint or Step Through.
Progress Indicator
The progress of a given syntax run is indicated with a downward pointing arrow in the gutter, spanning the
last set of commands run. For instance, you choose to run all commands in a syntax window that contains
breakpoints. At the rst breakpoint, the arrow will span the region from the rst command in the window
to the command prior to the one containing the breakpoint. At the second breakpoint, the arrow will
stretch from the command containing the rst breakpoint to the command prior to the one containing the
second breakpoint.
Run-time Behavior with Breakpoints
• When running command syntax containing breakpoints, execution stops at each breakpoint.
Specically, the block of command syntax from a given breakpoint (or beginning of the run) to the next
breakpoint (or end of the run) is submitted for execution exactly as if you had selected that syntax and
chosen Run > Selection.
• You can work with multiple syntax windows, each with its own set of breakpoints, but there is only one
queue for executing command syntax. Once a block of command syntax has been submitted--such as
the block of command syntax up to the rst breakpoint--no other block of command syntax will be
executed until the previous block has completed, regardless of whether the blocks are in the same or
different syntax windows.
• With execution stopped at a breakpoint, you can run command syntax in other syntax windows, and
inspect Data Editor or Viewer windows. However, modifying the contents of the syntax window
containing the breakpoint or changing the cursor position in that window will cancel the run.
Character Set Encoding in Syntax Files
The character set encoding of a syntax le can be either Unicode or code page encoding. A Unicode le
can contain characters from many different character sets. Code page les are restricted to characters
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163
supported in a specic language or locale. For example, a code page le in a western European encoding
cannot contain Japanese or Chinese characters.
Reading syntax les
To read syntax les correctly, the syntax editor needs to know the character encoding of the le.
• Files with a Unicode UTF-8 byte order mark are read as Unicode UTF-8 encoding, regardless of any
encoding selection you make. This byte order mark is at the beginning of the le, but it is not displayed.
• By default, les without any encoding information are read as Unicode UTF-8 in Unicode mode or the
current locale character encoding in code page mode. To override the default behavior, select Unicode
(UTF-8) or Local Encoding.
• As Declared is enabled if the syntax le contains a code page encoding identier at the top of the le.
Starting with release 23, a comment is automatically inserted in syntax les that are saved in code page
encoding. For example, the rst line in the le could be:
* Encoding: en_US.windows-1252.
If you select As Declared, that encoding is used to read the le.
Saving syntax les
By default, syntax les are saved as Unicode UTF-8 in Unicode mode or the current locale character
encoding in code page mode. To override the default behavior, select Unicode (UTF-8) or Local Encoding
in the Save Syntax As dialog.
• If you save a new syntax le or save the le in a different encoding, a comment is inserted at the top of
the le that identies the encoding. If an encoding comment is already present, it is replaced.
• If you save a syntax le and then save it again without closing it, it is saved in the same encoding.
Multiple Execute Commands
Syntax pasted from dialog boxes or copied from the log or the journal may contain EXECUTE commands.
When you run commands from a syntax window, EXECUTE commands are generally unnecessary and may
slow performance, particularly with larger data les, because each EXECUTE command reads the entire
data le. For more information, see the EXECUTE command in the Command Syntax Reference (available
from the Help menu in any IBM SPSS Statistics window).
Lag Functions
One notable exception is transformation commands that contain lag functions. In a series of
transformation commands without any intervening EXECUTE commands or other commands that read the
data, lag functions are calculated after all other transformations, regardless of command order. For
example,
COMPUTE lagvar=LAG(var1).
COMPUTE var1=var1*2.
and
COMPUTE lagvar=LAG(var1).
EXECUTE.
COMPUTE var1=var1*2.
yield very different results for the value of lagvar, since the former uses the transformed value of var1
while the latter uses the original value.
Character Set Encoding in Syntax Files
The character set encoding of a syntax le can be either Unicode or code page encoding. A Unicode le
can contain characters from many different character sets. Code page les are restricted to characters
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supported in a specic language or locale. For example, a code page le in a western European encoding
cannot contain Japanese or Chinese characters.
Reading syntax les
To read syntax les correctly, the syntax editor needs to know the character encoding of the le.
• Files with a Unicode UTF-8 byte order mark are read as Unicode UTF-8 encoding, regardless of any
encoding selection you make. This byte order mark is at the beginning of the le, but it is not displayed.
• By default, les without any encoding information are read as Unicode UTF-8 in Unicode mode or the
current locale character encoding in code page mode. To override the default behavior, select Unicode
(UTF-8) or Local Encoding.
• As Declared is enabled if the syntax le contains a code page encoding identier at the top of the le.
Starting with release 23, a comment is automatically inserted in syntax les that are saved in code page
encoding. For example, the rst line in the le could be:
* Encoding: en_US.windows-1252.
If you select As Declared, that encoding is used to read the le.
Saving syntax les
By default, syntax les are saved as Unicode UTF-8 in Unicode mode or the current locale character
encoding in code page mode. To override the default behavior, select Unicode (UTF-8) or Local Encoding
in the Save Syntax As dialog.
• If you save a new syntax le or save the le in a different encoding, a comment is inserted at the top of
the le that identies the encoding. If an encoding comment is already present, it is replaced.
• If you save a syntax le and then save it again without closing it, it is saved in the same encoding.
Multiple Execute Commands
Syntax pasted from dialog boxes or copied from the log or the journal may contain EXECUTE commands.
When you run commands from a syntax window, EXECUTE commands are generally unnecessary and may
slow performance, particularly with larger data les, because each EXECUTE command reads the entire
data le. For more information, see the EXECUTE command in the Command Syntax Reference (available
from the Help menu in any IBM SPSS Statistics window).
Lag Functions
One notable exception is transformation commands that contain lag functions. In a series of
transformation commands without any intervening EXECUTE commands or other commands that read the
data, lag functions are calculated after all other transformations, regardless of command order. For
example,
COMPUTE lagvar=LAG(var1).
COMPUTE var1=var1*2.
and
COMPUTE lagvar=LAG(var1).
EXECUTE.
COMPUTE var1=var1*2.
yield very different results for the value of lagvar, since the former uses the transformed value of var1
while the latter uses the original value.
Encrypting syntax les
You can protect your syntax les by encrypting them with a password. Encrypted les can be opened only
by providing the password.
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165
Note: Encrypted syntax les cannot be used in production jobs or with the IBM SPSS Statistics Batch
Facility (available with IBM SPSS Statistics Server).
To save the contents of the syntax editor as an encrypted syntax le:
1. Make the Syntax Editor the active window (click anywhere in the window to make it active).
2. From the menus, choose:
File > Save As...
3. Select Encrypted Syntax from the Save as type drop-down list.
4. Click Save.
5. In the Encrypt File dialog box, provide a password and reenter it in the Conrm password text box.
Passwords are limited to 10 characters and are case-sensitive.
Warning: Passwords cannot be recovered if they are lost. If the password is lost the le cannot be
opened.
Creating strong passwords
• Use eight or more characters.
• Include numbers, symbols and even punctuation in your password.
• Avoid sequences of numbers or characters, such as "123" and "abc", and avoid repetition, such as
"111aaa".
• Do not create passwords that use personal information such as birthdays or nicknames.
• Periodically change the password.
Note: Storing encrypted les to an IBM SPSS Collaboration and Deployment Services Repository is not
supported.
Modifying encrypted les
• If you open an encrypted le, modify the le and choose File > Save, the modied le is saved with the
same password.
• You can change the password on an encrypted le by opening the le, repeating the steps for
encrypting it, and specifying a different password in the Encrypt File dialog box.
• You can save an unencrypted version of an encrypted le by opening the le, choosing File > Save As
and selecting Syntax from the Save as type drop-down list.
Note: Encrypted syntax les cannot be opened in versions of IBM SPSS Statistics prior to version 22.
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Chapter 15. Overview of the chart facility
High-resolution charts and plots are created by the procedures on the Graphs menu and by many of the
procedures on the Analyze menu. This chapter provides an overview of the chart facility.
Building and editing a chart
Before you can create a chart, you need to have your data in the Data Editor. You can enter the data
directly into the Data Editor; open a previously saved data le; or read a spreadsheet, tab-delimited data
le, or database le. The Tutorial selection on the Help menu has online examples of creating and
modifying a chart, and the online Help system provides information about creating and modifying all chart
types.
Building Charts
The Chart Builder allows you to build charts from predened gallery charts or from the individual parts
(for example, axes and bars). You build a chart by dragging and dropping the gallery charts or basic
elements onto the canvas, which is the large area to the right of the Variables list in the Chart Builder
dialog box.
As you are building the chart, the canvas displays a preview of the chart. Although the preview uses
dened variable labels and measurement levels, it does not display your actual data. Instead, it uses
randomly generated data to provide a rough sketch of how the chart will look.
Using the gallery is the preferred method for new users. For information about using the gallery, see
“Building a Chart from the Gallery” on page 167.
How to Start the Chart Builder
1. From the menus choose:
Graphs > Chart Builder
Building a Chart from the Gallery
The easiest method for building charts is to use the gallery. Following are general steps for building a
chart from the gallery.
1. Click the Gallery tab if it is not already displayed.
2. In the Choose From list, select a category of charts. Each category offers several types.
3. Drag the picture of the chart you want onto the canvas. You can also double-click the picture. If the
canvas already displays a chart, the gallery chart replaces the axis set and graphic elements on the
chart.
a. Drag variables from the Variables list and drop them into the axis drop zones and, if available, the
grouping drop zone. If an axis drop zone already displays a statistic and you want to use that
statistic, you do not have to drag a variable into the drop zone. You need to add a variable to a zone
only when the text in the zone is blue. If the text is black, the zone already contains a variable or
statistic.
Note: The measurement level of your variables is important. The Chart Builder sets defaults based
on the measurement level while you are building the chart. Furthermore, the resulting chart may
also look different for different measurement levels. You can temporarily change a variable's
measurement level by right-clicking the variable and choosing an option.
b. If you need to change statistics or modify attributes of the axes or legends (such as the scale
range), click the Element Properties tab in the side bar of the Chart Builder. (If the side bar is not
displayed, click the button in the upper right corner of the Chart Builder to display the side bar.)
c. In the Edit Properties Of list, select the item you want to change. (For information about the specic
properties, click Help.)
d. If you need to add more variables to the chart (for example, for clustering or paneling), click the
Groups/Point ID tab in the Chart Builder dialog box and select one or more options. Then drag
categorical variables to the new drop zones that appear on the canvas.
4. If you want to transpose the chart (for example, to make the bars horizontal), click the Basic Elements
tab and then click Transpose.
5. Click OK to create the chart. The chart is displayed in the Viewer.
Editing Charts
The Chart Editor provides a powerful, easy-to-use environment where you can customize your charts and
explore your data. The Chart Editor features:
• Simple, intuitive user interface. You can quickly select and edit parts of the chart using menus and
toolbars. You can also enter text directly on a chart.
• Wide range of formatting and statistical options. You can choose from a full range of styles and
statistical options.
• Powerful exploratory tools. You can explore your data in various ways, such as by labeling, reordering,
and rotating it. You can change chart types and the roles of variables in the chart. You can also add
distribution curves and t, interpolation, and reference lines.
• Flexible templates for consistent look and behavior. You can create customized templates and use
them to easily create charts with the look and options that you want. For example, if you always want a
specic orientation for axis labels, you can specify the orientation in a template and apply the template
to other charts.
How to View the Chart Editor
1. Double-click a chart in the Viewer.
Chart Editor Fundamentals
The Chart Editor provides various methods for manipulating charts.
Menus
Many actions that you can perform in the Chart Editor are done with the menus, especially when you are
adding an item to the chart. For example, you use the menus to add a t line to a scatterplot. After adding
an item to the chart, you often use the Properties dialog box to specify options for the added item.
Properties Dialog Box
Options for the chart and its chart elements can be found in the Properties dialog box.
To view the Properties dialog box, you can:
1. Double-click a chart element.
or
2. Select a chart element, and then from the menus choose:
Edit > Properties
Additionally, the Properties dialog box automatically appears when you add an item to the chart.
The Properties dialog box has tabs that allow you to set the options and make other changes to a chart.
The tabs that you see in the Properties dialog box are based on your current selection.
Some tabs include a preview to give you an idea of how the changes will affect the selection when you
apply them. However, the chart itself does not reflect your changes until you click Apply. You can make
changes on more than one tab before you click Apply. If you have to change the selection to modify a
different element on the chart, click Apply before changing the selection. If you do not click Apply before
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changing the selection, clicking Apply at a later point will apply changes only to the element or elements
currently selected.
Depending on your selection, only certain settings will be available. The help for the individual tabs
species what you need to select to view the tabs. If multiple elements are selected, you can change only
those settings that are common to all the elements.
Toolbars
The toolbars provide a shortcut for some of the functionality in the Properties dialog box. For example,
instead of using the Text tab in the Properties dialog box, you can use the Edit toolbar to change the font
and style of the text.
Saving the Changes
Chart modications are saved when you close the Chart Editor. The modied chart is subsequently
displayed in the Viewer.
Chart denition options
When you are dening a chart in the Chart Builder, you can add titles and change options for the chart
creation.
Adding and Editing Titles and Footnotes
You can add titles and footnotes to the chart to help a viewer interpret it. The Chart Builder also
automatically displays error bar information in the footnotes.
Add or modify titles and footnotes
1. Click the Titles/Footnotes tab or click a title or footnote displayed in the preview.
2. Use the Element Properties tab to edit the title/footnote text.
For Title 1, an Automatic title is generated, based on the chart type and the variables used in the chart.
This automatic title is used by default unless you select Custom or None.
How to Remove a Title or Footnote
1. Click the Titles/Footnotes tab.
2. Deselect the title or footnote that you want to remove.
How to Edit the Title or Footnote Text
When you add titles and footnotes, you cannot edit their associated text directly on the chart. As with
other items in the Chart Builder, you edit them using the Element Properties tab.
1. In the Edit Properties Of list, select a title, subtitle, or footnote (for example, Title 1).
2. In the content box, type the text associated with the title, subtitle, or footnote.
Setting General Options
The Chart Builder offers general options for the chart. These are options that apply to the overall chart,
rather than a specic item on the chart. General options include missing value handling, chart size, and
panel wrapping.
1. Click the Options tab in the side bar of the Chart Builder. (If the side bar is not displayed, click the
button in the upper right corner of the Chart Builder to display the side bar.)
2. Modify the general options. Details about these follow.
User-Missing Values
Break Variables. If there are missing values for the variables used to dene categories or subgroups,
select Include so that the category or categories of user-missing values (values identied as missing by
the user) are included in the chart. These "missing" categories also act as break variables in calculating
Chapter 15. Overview of the chart facility
169
the statistic. The "missing" category or categories are displayed on the category axis or in the legend,
adding, for example, an extra bar or a slice to a pie chart. If there are no missing values, the "missing"
categories are not displayed.
If you select this option and want to suppress display after the chart is drawn, open the chart in the Chart
Editor and choose Properties from the Edit menu. Use the Categories tab to move the categories that you
want to suppress to the Excluded list. Note, however, that the statistics are not recalculated if you hide
the "missing" categories. Therefore, something like a percent statistic will still take the "missing"
categories into account.
Note: This control does not affect system-missing values. These are always excluded from the chart.
Summary Statistics and Case Values. You can choose one of the following alternatives for exclusion of
cases having missing values:
• Exclude listwise to obtain a consistent base for the chart. If any of the variables in the chart has a
missing value for a given case, the whole case is excluded from the chart.
• Exclude variable-by-variable to maximize the use of the data. If a selected variable has any missing
values, the cases having those missing values are excluded when the variable is analyzed.
Chart Size and Panels
Chart Size. Specify a percentage greater than 100 to enlarge the chart or less than 100 to shrink it. The
percentage is relative to the default chart size.
Panels. When there are many panel columns, select Wrap Panels to allow panels to wrap across rows
rather than being forced to t in a specic row. Unless this option is selected, the panels are shrunk to
force them to t in a row.
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Chapter 16. Scoring data with predictive models
The process of applying a predictive model to a set of data is referred to as scoring the data. IBM SPSS
Statistics has procedures for building predictive models such as regression, clustering, tree, and neural
network models. Once a model has been built, the model specications can be saved in a le that
contains all of the information necessary to reconstruct the model. You can then use that model le to
generate predictive scores in other datasets. Note: Some procedures produce a model XML le, and some
procedures produce a compressed le archive (.zip le).
Example. The direct marketing division of a company uses results from a test mailing to assign propensity
scores to the rest of their contact database, using various demographic characteristics to identify
contacts most likely to respond and make a purchase.
Scoring is treated as a transformation of the data. The model is expressed internally as a set of numeric
transformations to be applied to a given set of elds (variables)--the predictors specied in the model--in
order to obtain a predicted result. In this sense, the process of scoring data with a given model is
inherently the same as applying any function, such as a square root function, to a set of data.
The scoring process consists of two basic steps:
1. Build the model and save the model le. You build the model using a dataset for which the outcome of
interest (often referred to as the target) is known. For example, if you want to build a model that will
predict who is likely to respond to a direct mail campaign, you need to start with a dataset that already
contains information on who responded and who did not respond. For example, this might be the
results of a test mailing to a small group of customers or information on responses to a similar
campaign in the past.
Note: For some model types there is no target outcome of interest. Clustering models, for example, do
not have a target, and some nearest neighbor models do not have a target.
2. Apply that model to a different dataset (for which the outcome of interest is not known) to obtain
predicted outcomes.
Scoring Wizard
You can use the Scoring Wizard to apply a model created with one dataset to another dataset and
generate scores, such as the predicted value and/or predicted probability of an outcome of interest.
To score a dataset with a predictive model
1. Open the dataset that you want to score.
2. Open the Scoring Wizard. From the menus choose:
Utilities > Scoring Wizard.
3. Select a model XML le or compressed le archive (.zip fle). Use the Browse button to navigate to a
different location to select a model le.
4. Match elds in the active dataset to elds used in the model. See the topic “ Matching model elds to
dataset elds” on page 172 for more information.
5. Select the scoring functions you want to use. See the topic “ Selecting scoring functions” on page 173
for more information.
Select a Scoring Model. The model le can be an XML le or a compressed le archive (.zip le) that
contains model PMML. The list only displays les with a .zip or .xml extension; the le extensions are not
displayed in the list. You can use any model le created by IBM SPSS Statistics. You can also use some
model les created by other applications, such as IBM SPSS Modeler, but some model les created by
other applications cannot be read by IBM SPSS Statistics, including any models that have multiple target
elds (variables).
Model Details. This area displays basic information about the selected model, such as model type, target
(if any), and predictors used to build the model. Since the model le has to be read to obtain this
information, there may be a delay before this information is displayed for the selected model. If the XML
le or .zip le is not recognized as a model that IBM SPSS Statistics can read, a message indicating that
the le cannot be read is displayed.
Matching model elds to dataset elds
In order to score the active dataset, the dataset must contain elds (variables) that correspond to all the
predictors in the model. If the model also contains split elds, then the dataset must also contain elds
that correspond to all the split elds in the model.
• By default, any elds in the active dataset that have the same name and type as elds in the model are
automatically matched.
• Use the drop-down list to match dataset elds to model elds. The data type for each eld must be the
same in both the model and the dataset in order to match elds.
• You cannot continue with the wizard or score the active dataset unless all predictors (and split elds if
present) in the model are matched with elds in the active dataset.
Dataset Fields. The drop-down list contains the names of all the elds in the active dataset. Fields that
do not match the data type of the corresponding model eld cannot be selected.
Model Fields. The elds used in the model.
Role. The displayed role can be one of the following:
• Predictor. The eld is used as a predictor in the model. That is, values of the predictors are used to
"predict" values of the target outcome of interest.
• Split. The values of the split elds are used to dene subgroups, which are each scored separately.
There is a separate subgroup for each unique combination of split eld values. (Note: splits are only
available for some models.)
• Record ID. Record (case) identier.
Measure. Measurement level for the eld as dened in the model. For models in which measurement
level can affect the scores, the measurement level as dened in the model is used, not the measurement
level as dened in the active dataset. For more information on measurement level, see “Variable
measurement level” on page 47.
Type. Data type as dened in the model. The data type in the active dataset must match the data type in
the model. Data type can be one of the following:
• String. Fields with a data type of string in the active dataset match the data type of string in the model.
• Numeric. Numeric elds with display formats other than date or time formats in the active dataset
match the numeric data type in the model. This includes F (numeric), Dollar, Dot, Comma, E (scientic
notation), and custom currency formats. Fields with Wkday (day of week) and Month (month of year)
formats are also considered numeric, not dates. For some model types, date and time elds in the
active dataset are also considered a match for the numeric data type in the model.
• Date. Numeric elds with display formats that include the date but not the time in the active dataset
match the date type in the model. This includes Date (dd-mm-yyyy), Adate (mm/dd/yyyy), Edate
(dd.mm.yyyy), Sdate (yyyy/mm/dd), and Jdate (dddyyyy).
• Time. Numeric elds with display formats that include the time but not the date in the active dataset
match the time data type in the model. This includes Time (hh:mm:ss) and Dtime (dd hh:mm:ss)
• Timestamp. Numeric elds with a display format that includes both the date and the time in the active
dataset match the timestamp data type in the model. This corresponds to the Datetime format (dd-mm-
yyyy hh:mm:ss) in the active dataset.
Note: In addition to eld name and type, you should make sure that the actual data values in the dataset
being scored are recorded in the same fashion as the data values in the dataset used to build the model.
For example, if the model was built with an Incomeeld that has income divided into four categories, and
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IncomeCategory in the active dataset has income divided into six categories or four different categories,
those elds don't really match each other and the resulting scores will not be reliable.
Missing Values
This group of options controls the treatment of missing values, encountered during the scoring process,
for the predictor variables dened in the model. A missing value in the context of scoring refers to one of
the following:
• A predictor contains no value. For numeric elds (variables), this means the system-missing value. For
string elds, this means a null string.
• The value has been dened as user-missing, in the model, for the given predictor. Values dened as
user-missing in the active dataset, but not in the model, are not treated as missing values in the scoring
process.
• The predictor is categorical and the value is not one of the categories dened in the model.
Use Value Substitution. Attempt to use value substitution when scoring cases with missing values. The
method for determining a value to substitute for a missing value depends on the type of predictive model.
• Linear Regression and Discriminant models. For independent variables in linear regression and
discriminant models, if mean value substitution for missing values was specied when building and
saving the model, then this mean value is used in place of the missing value in the scoring computation,
and scoring proceeds. If the mean value is not available, then the system-missing value is returned.
• Decision Tree models. For the CHAID and Exhaustive CHAID models, the biggest child node is selected
for a missing split variable. The biggest child node is the one with the largest population among the
child nodes using learning sample cases. For C&RT and QUEST models, surrogate split variables (if any)
are used rst. (Surrogate splits are splits that attempt to match the original split as closely as possible
using alternate predictors.) If no surrogate splits are specied or all surrogate split variables are
missing, the biggest child node is used.
• Logistic Regression models. For covariates in logistic regression models, if a mean value of the
predictor was included as part of the saved model, then this mean value is used in place of the missing
value in the scoring computation, and scoring proceeds. If the predictor is categorical (for example, a
factor in a logistic regression model), or if the mean value is not available, then the system-missing
value is returned.
Use System-Missing. Return the system-missing value when scoring a case with a missing value.
Selecting scoring functions
The scoring functions are the types of "scores" available for the selected model. For example, predicted
value of the target, probability of the predicted value, or probability of a selected target value.
Scoring function. The scoring functions available are dependent on the model. One or more of the
following will be available in the list:
• Predicted value. The predicted value of the target outcome of interest. This is available for all models,
except those that do not have a target.
• Probability of predicted value. The probability of the predicted value being the correct value,
expressed as a proportion. This is available for most models with a categorical target.
• Probability of selected value. The probability of the selected value being the correct value, expressed
as a proportion. Select a value from the drop-down list in the Value column. The available values are
dened by the model. This is available for most models with a categorical target.
• Condence. A probability measure associated with the predicted value of a categorical target. For
Binary Logistic Regression, Multinomial Logistic Regression, and Naive Bayes models, the result is
identical to the probability of the predicted value. For Tree and Ruleset models, the condence can be
interpreted as an adjusted probability of the predicted category and is always less than the probability
of the predicted value. For these models, the condence value is more reliable than the probability of
the predicted value.
• Node number. The predicted terminal node number for Tree models.
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173
• Standard error.The standard error of the predicted value. Available for Linear Regression models,
General Linear models, and Generalized Linear models with a scale target. This is available only if the
covariance matrix is saved in the model le.
• Cumulative Hazard. The estimated cumulative hazard function. The value indicates the probability of
observing the event at or before the specied time, given the values of the predictors.
• Nearest neighbor. The ID of the nearest neighbor. The ID is the value of the case labels variable, if
supplied, and otherwise the case number. Applies only to nearest neighbor models.
• Kth nearest neighbor. The ID of the kth nearest neighbor. Enter an integer for the value of k in the
Value column. The ID is the value of the case labels variable, if supplied, and otherwise the case
number. Applies only to nearest neighbor models.
• Distance to nearest neighbor. The distance to the nearest neighbor. Depending on the model, either
Euclidean or City Block distance will be used. Applies only to nearest neighbor models.
• Distance to kth nearest neigbor. The distance to the kth nearest neighbor. Enter an integer for the
value of k in the Value column. Depending on the model, either Euclidean or City Block distance will be
used. Applies only to nearest neighbor models.
Field Name. Each selected scoring function saves a new eld (variable) in the active dataset. You can use
the default names or enter new names. If elds with those names already exist in the active dataset, they
will be replaced. For information on eld naming rules, see “Variable names” on page 46.
Value. See the descriptions of the scoring functions for descriptions of functions that use a Value setting.
Scoring the active dataset
On the nal step of the wizard, you can score the active dataset or paste the generated command syntax
to a syntax window. You can then modify and/or save the generated command syntax.
Merging model and transformation XML les
Some predictive models are built with data that have been modied or transformed in various ways. In
order to apply those models to other datasets in a meaningful way, the same transformations must also
be performed on the dataset being scored, or the transformations must also be reflected in the model le.
Including transformations in the model le is a two-step process:
1. Save the transformations in a transformation XML le. This can only be done using TMS BEGIN and
TMS END in command syntax.
2. Combine the model le (XML le or .zip le) and the transformation XML le in a new, merged model
XML le.
To combine a model le and a transformation XML le in a new, merged model le:
3. From the menus choose:
Utilities > Merge Model XML
4. Select the model XML le.
5. Select the transformation XML le.
6. Enter a path and name for the new merged model XML le, or use Browse to select the location and
name.
Note: You cannot merge model .zip les for models that contain splits (separate model information for
each split group) or ensemble models with transformation XML les.
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Chapter 17. Utilities
Utilities
This chapter describes the functions found on the Utilities menu and the ability to reorder target variable
lists.
• For information on the Scoring Wizard, see Chapter 16, “Scoring data with predictive models,” on page
171.
• For information on merging model and transformation XML les, see “Merging model and
transformation XML les” on page 174.
Variable information
The Variables dialog box displays variable denition information for the currently selected variable,
including:
• Variable label
• Data format
• User-missing values
• Value labels
• Measurement level
Visible. The Visible column in the variable list indicates if the variable is currently visible in the Data
Editor and in dialog box variable lists.
Go To. Goes to the selected variable in the Data Editor window.
Paste. Pastes the selected variables into the designated syntax window at the cursor location.
To modify variable denitions, use the Variable view in the Data Editor.
There are two ways to open the Variables dialog box.
• From the menus, choose Utilities > Variables....
• Right-click a variable name in the Data Editor and select Variable Information... from the context
menu.
Data le comments
You can include descriptive comments with a data le. For IBM SPSS Statistics data les, these
comments are saved with the data le.
To add, modify, delete, or display data le comments
1. From the menus choose:
Utilities > Data File Comments...
2. To display the comments in the Viewer, select Display comments in output.
Comments can be any length but are limited to 80 bytes (typically 80 characters in single-byte languages)
per line; lines will automatically wrap at 80 characters. Comments are displayed in the same font as text
output to accurately reflect how they will appear when displayed in the Viewer.
A date stamp (the current date in parentheses) is automatically appended to the end of the list of
comments whenever you add or modify comments. This may lead to some ambiguity concerning the
dates associated with comments if you modify an existing comment or insert a new comment between
existing comments.
Variable sets
You can restrict the variables that are displayed in the Data Editor and in dialog box variable lists by
dening and using variable sets. This is particularly useful for data les with a large number of variables.
Small variable sets make it easier to nd and select the variables for your analysis.
Dening variable sets
Dene Variable Sets creates subsets of variables to display in the Data Editor and in dialog box variable
lists. Dened variable sets are saved with IBM SPSS Statistics data les.
Set Name. Set names can be up to 64 bytes. Any characters, including blanks, can be used.
Variables in Set. Any combination of numeric and string variables can be included in a set. The order of
variables in the set has no effect on the display order of the variables in the Data Editor or in dialog box
variable lists. A variable can belong to multiple sets.
To dene variable sets
1. From the menus choose:
Utilities > Dene Variable Sets...
2. Select the variables that you want to include in the set.
3. Enter a name for the set (up to 64 bytes).
4. Click Add Set.
Using variable sets to show and hide variables
Use Variable Sets restricts the variables displayed in the Data Editor and in dialog box variable lists to the
variables in the selected (checked) sets.
• The set of variables displayed in the Data Editor and in dialog box variable lists is the union of all
selected sets.
• A variable can be included in multiple selected sets.
• The order of variables in the selected sets and the order of selected sets have no effect on the display
order of variables in the Data Editor or in dialog box variable lists.
• Although the dened variable sets are saved with IBM SPSS Statistics data les, the list of currently
selected sets is reset to the default, built-in sets each time you open the data le.
The list of available variable sets includes any variable sets dened for the active dataset, plus two built-
in sets:
• ALLVARIABLES. This set contains all variables in the data le, including new variables created during a
session.
• NEWVARIABLES. This set contains only new variables created during the session.
Note: Even if you save the data le after creating new variables, the new variables are still included in
the NEWVARIABLES set until you close and reopen the data le.
At least one variable set must be selected. If ALLVARIABLES is selected, any other selected sets will not
have any visible effect, since this set contains all variables.
1. From the menus choose:
Utilities > Use Variable Sets...
2. Select the dened variable sets that contain the variables that you want to appear in the Data Editor
and in dialog box variable lists.
To display all variables
1. From the menus choose:
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Utilities > Show All Variables
Reordering target variable lists
Variables appear on dialog box target lists in the order in which they are selected from the source list. If
you want to change the order of variables on a target list—but you don't want to deselect all of the
variables and reselect them in the new order—you can move variables up and down on the target list
using the Ctrl key (Macintosh: Command key) with the up and down arrow keys. You can move multiple
variables simultaneously if they are contiguous (grouped together). You cannot move noncontiguous
groups of variables.
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Chapter 18. Options
Options
Options control a wide variety of settings:
• Session journal, which keeps a record of all commands run in every session
• Display order for variables in dialog box source lists
• Items that are displayed and hidden in new output results
• TableLook for new pivot tables
• Custom currency formats
Options control various settings.
To change options settings
1. From the menus, choose:
Edit > Options...
2. Click the tabs for the settings that you want to change.
3. Change the settings.
4. Click OK or Apply.
General options
Variable Lists
These settings control the display of variables in dialog box lists. You can display variable names or
variable labels. Names or labels can be displayed in alphabetical or le order or grouped by measurement
level. Display order affects only source variable lists. Target variable lists always reflect the order in which
variables were selected.
Roles
Some dialogs support the ability to pre-select variables for analysis based on dened roles. See the topic
“Roles” on page 50 for more information.
Use predened roles
By default, pre-select variables based on dened roles.
Use custom assignments
By default, do not use roles to pre-select variables.
You can also switch between predened roles and custom assignment within the dialogs that support this
functionality. The setting here controls only the initial default behavior in effect for each dataset.
Maximum Number of Threads
The number of threads that multithreaded procedures use when calculating results. The Automatic
setting is based on the number of available processing cores. Specify a lower value if you want to make
more processing resources available to other applications while multithreaded procedures are running.
This option is disabled in distributed analysis mode.
Output
No scientic notation for small numbers in tables
Suppresses the display of scientic notation for small decimal values in output. Very small decimal
values will be displayed as 0 (or 0.000). This setting only affects output with the "general" format,
which is determined by the application. This setting does not affect the display of signicance levels
or other statistics with a standard range of values. The format of many numeric values in pivot tables
is based on the format of the variable associated with the numeric value.
Apply locale's digit grouping format to numeric values
Applies the current locale’s digit grouping format to numeric values in pivot tables and charts as well
as in the Data Editor. For example, in a French locale with this setting enabled the value 34419,57
will be displayed as 34 419,57.
The grouping format does not apply to trees, Model Viewer items, numeric values with the DOT or
COMMA format, or numeric values with a DOLLAR or custom currency format. It does, however, apply
to the display of the days value for numeric values with a DTIME format--for example, to the value of
ddd in the format ddd hh:mm.
Display a leading zero for decimal values
Displays leading zeros for numeric values that consist only of a decimal part. For example, when
leading zeros are displayed, the value .123 is displayed as 0.123. This setting does not apply to
numeric values that have a currency or percent format. Except for xed ASCII les (*.dat), leading
zeros are not included when the data are saved to an external le.
Measurement system
The measurement system used (points, inches, or centimeters) for specifying attributes such as pivot
table cell margins, cell widths, and space between tables for printing.
Notication
Controls the manner in which the program noties you that it has nished running a procedure and
that the results are available in the Viewer.
Windows
Look and feel
Controls the basic appearance of windows and dialog boxes. If you notice any display issues after
changing the look and feel, try shutting down and restarting the application.
Open syntax window at startup
Syntax windows are text le windows used to enter, edit, and run commands. If you frequently work
with command syntax, select this option to automatically open a syntax window at the beginning of
each session. This is useful primarily for experienced users who prefer to work with command syntax
instead of dialog boxes.
Open only one dataset at a time
Closes the currently open data source each time you open a different data source using the menus
and dialog boxes. By default, every time you use the menus and dialog boxes to open a new data
source, that data source opens in a new Data Editor window, and any other data sources open in other
Data Editor windows remain open and available during the session until explicitly closed.
When you select this option, it takes effect immediately but does not close any datasets that were
open at the time the setting was changed. This setting has no effect on data sources opened using
command syntax, which relies on DATASET commands to control multiple datasets. See the topic
Chapter 6, “Working with Multiple Data Sources,” on page 61
for more information.
Display native macOS le dialogs
When selected, le selection dialogs in the macOS version of SPSS Statistics are presented in native
macOS format. Historically, le selection dialogs have been heavily customized to accommodate
specic SPSS Statistics le features. This settings allows you to default le selection dialogs to native
macOS format.
Note: This feature is available only in macOS environments.
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Auto-Recovery
These settings control the IBM SPSS Statistics automatic recovery feature. Automatic recovery is
designed to recover unsaved les and content in instances where the application quits unexpectedly. You
can select to enable/disable the automatic recovery feature (the feature is enabled by default), select a
time interval (in minutes) between saving les, set the maximum number of restore points to save, and
view or change the auto-recovery le location.
Note: Selecting to save les too frequently (for example, every 2 minutes) may result in decreased
system performance.
Upon relaunching SPSS Statistics after an unexpected exit, you are presented with an IBM SPSS Statistics
error report, which allows you to enter information about your session prior to the unexpected exit. After
leaving the exit report, you are presented with the Document Recovery dialog, which provides options for
recovering prior session data or deleting the saved session data. For more information, see “Auto-
Recovery” on page 2.
Language options
Language
Output language. Controls the language that is used in the output. Does not apply to simple text output.
The list of available languages depends on the currently installed language les. (Note: This setting does
not affect the user interface language.) Depending on the language, you might also need to use Unicode
character encoding for characters to render properly.
Note: Custom scripts that rely on language-specic text strings in the output might not run correctly when
you change the output language. For more information, see the topic “Script options” on page 189
.
User Interface. This setting controls the language that is used in menus, dialogs, and other user interface
features. (Note: This setting does not affect the output language.)
Character Encoding and Locale
This controls the default behavior for determining the encoding for reading and writing data les and
syntax les. You can change these settings only when there are no open data sources, and the settings
remain in effect for subsequent sessions until explicitly changed.
Unicode (universal character set). Use Unicode encoding (UTF-8) for reading and writing les. This mode
is referred to as Unicode mode.
Locale's writing system. Use the current locale selection to determine the encoding for reading and
writing les. This mode is referred to as code page mode.
Locale. You can select a locale from the list or enter any valid locale value. OS writing system sets the
locale to the writing system of the operating system. The application gets this information from the
operating system each time you start the application. The locale setting is primarily relevant in code page
mode, but it can also affect how some characters are rendered in Unicode mode.
There are a number of important implications for Unicode mode and Unicode les:
• IBM SPSS Statistics data les and syntax les that are saved in Unicode encoding should not be used in
releases of IBM SPSS Statistics before 16.0. For syntax les, you can specify the encoding when you
save the le. For data les, you should open the data le in code page mode and then resave it if you
want to read the le with earlier versions.
• When code page data les are read in Unicode mode, the dened width of all string variables is tripled.
To automatically set the width of each string variable to the longest observed value for that variable,
select Minimize string widths based on observed values in the Open Data dialog box.
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181
Bidirectional Text
If you use a combination of right-to-left (for example, Arabic or Hebrew) languages and left-to-right
languages (for example, English), select the direction for text flow. Individual words will still flow in the
correct direction, based on the language. This option controls only the text flow for complete blocks of
text (for example, all the text that is entered in an edit eld).
• Automatic. Text flow is determined by characters that are used in each word. This option is the default.
• Right-to-left. Text flows right to left.
• Left-to-right. Text flows left to right.
Viewer options
Viewer output display options affect only new output that is produced after you change the settings.
Output that is already displayed in the Viewer is not affected by changes in these settings.
Initial Output State
Controls which items are automatically displayed or hidden each time that you run a procedure and
how items are initially aligned. You can control the display of the following items: log, warnings, notes,
titles, pivot tables, charts, tree diagrams, and text output. You can also turn the display of commands
in the log on or off. You can copy command syntax from the log and save it in a syntax le.
Note: All output items are displayed left-aligned in the Viewer. Only the alignment of printed output is
affected by the justication settings. Centered and right-aligned items are identied by a small
symbol.
Title
Controls the font style, size, and color for new output titles. The font Size list provides a set of
predened sizes, but you can manually enter other, supported size values.
Page Title
Controls the font style, size, and color for new page titles and page titles that are generated by TITLE
and SUBTITLE command syntax or created by New Page Title on the Insert menu. The font Size list
provides a set of predened sizes, but you can manually enter other, supported size values.
Text Output
Font that is used for text output. Text output is designed for use with a monospaced (xed-pitch) font.
If you select a proportional font, tabular output does not align properly. The font Size list provides a
set of predened sizes, but you can manually enter other, supported size values.
Default Page Setup
Controls the default options for orientation and margins for printing.
Data Options
Transformation and Merge Options. Each time the program executes a command, it reads the data le.
Some data transformations (such as Compute and Recode) and le transformations (such as Add
Variables and Add Cases) do not require a separate pass of the data, and execution of these commands
can be delayed until the program reads the data to execute another command, such as a statistical or
charting procedure.
• For large data les, where reading the data can take some time, you may want to select Calculate
values before used to delay execution and save processing time. When this option is selected, the
results of transformations you make using dialog boxes such as Compute Variable will not appear
immediately in the Data Editor; new variables created by transformations will be displayed without any
data values; and data values in the Data Editor cannot be changed while there are pending
transformations. Any command that reads the data, such as a statistical or charting procedure, will
execute the pending transformations and update the data displayed in the Data Editor. Alternatively,
you can use Run Pending Transforms on the Transform menu.
• With the default setting of Calculate values immediately, when you paste command syntax from
dialogs, an EXECUTE command is pasted after each transformation command. See the topic “Multiple
Execute Commands” on page 164 for more information.
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Display Format for New Numeric Variables. Controls the default display width and number of decimal
places for new numeric variables. There is no default display format for new string variables. If a value is
too large for the specied display format, rst decimal places are rounded and then values are converted
to scientic notation. Display formats do not affect internal data values. For example, the value
123456.78 may be rounded to 123457 for display, but the original unrounded value is used in any
calculations.
Set Century Range for 2-Digit Years. Denes the range of years for date-format variables entered and/or
displayed with a two-digit year (for example, 10/28/86, 29-OCT-87). The automatic range setting is
based on the current year, beginning 69 years prior to and ending 30 years after the current year (adding
the current year makes a total range of 100 years). For a custom range, the ending year is automatically
determined based on the value that you enter for the beginning year.
Random Number Generator. Two different random number generators are available:
• Version 12 Compatible. The random number generator used in version 12 and previous releases. If you
need to reproduce randomized results generated in previous releases based on a specied seed value,
use this random number generator.
• Mersenne Twister. A newer random number generator that is more reliable for simulation purposes. If
reproducing randomized results from version 12 or earlier is not an issue, use this random number
generator.
Assigning Measurement Level. For data read from external le formats, older IBM SPSS Statistics data
les (prior to release 8.0) and new elds created in a session, measurement level for numeric elds is
determined by a set of rules, including the number of unique values. You can specify the minimum
number of data values for a numeric variable used to classify the variable as continuous (scale) or
nominal. Variables with fewer than the specied number of unique values are classied as nominal.
There are numerous other conditions that are evaluated prior to applying the minimum number of data
values rule when determining to apply the continuous (scale) or nominal measurement level. Conditions
are evaluated in the order listed in the table below. The measurement level for the rst condition that
matches the data is applied.
Table 22. Rules for determining default measurement level
Condition Measurement Level
Format is dollar or custom-currency Continuous
Format is date or time (excluding Month and Wkday) Continuous
All values of a variable are missing Nominal
Variable contains at least one non-integer value Continuous
Variable contains at least one negative value Continuous
Variable contains no valid values less than 10,000 Continuous
Variable has N or more valid, unique values* Continuous
Variable has no valid values less than 10 Continuous
Variable has less than N valid, unique values* Nominal
* N is the user-specied cut-off value. The default is 24.
Rounding and Truncation of Numeric Values. For the RND and TRUNC functions, this setting controls the
default threshold for rounding up values that are very close to a rounding boundary. The setting is
specied as a number of bits and is set to 6 at install time, which should be sufcient for most
applications. Setting the number of bits to 0 produces the same results as in release 10. Setting the
number of bits to 10 produces the same results as in releases 11 and 12.
• For the RND function, this setting species the number of least-signicant bits by which the value to be
rounded may fall short of the threshold for rounding up but still be rounded up. For example, when
Chapter 18. Options
183
rounding a value between 1.0 and 2.0 to the nearest integer this setting species how much the value
can fall short of 1.5 (the threshold for rounding up to 2.0) and still be rounded up to 2.0.
• For the TRUNC function, this setting species the number of least-signicant bits by which the value to
be truncated may fall short of the nearest rounding boundary and be rounded up before truncating. For
example, when truncating a value between 1.0 and 2.0 to the nearest integer this setting species how
much the value can fall short of 2.0 and be rounded up to 2.0.
Customize Variable View. Controls the default display and order of attributes in Variable View. See the
topic “Changing the default variable view” on page 184 for more information.
Change Dictionary. Controls the language version of the dictionary used for checking the spelling of
items in Variable View. See the topic “Spell checking ” on page 53 for more information.
Changing the default variable view
You can use Customize Variable View to control which attributes are displayed by default in Variable View
(for example, name, type, label) and the order in which they are displayed.
Click Customize Variable View.
1. Select (check) the variable attributes you want to display.
2. Use the up and down arrow buttons to change the display order of the attributes.
Currency options
You can create up to ve custom currency display formats that can include special prex and sufx
characters and special treatment for negative values.
The ve custom currency format names are CCA, CCB, CCC, CCD, and CCE. You cannot change the format
names or add new ones. To modify a custom currency format, select the format name from the source list
and make the changes that you want.
Prexes, sufxes, and decimal indicators dened for custom currency formats are for display purposes
only. You cannot enter values in the Data Editor using custom currency characters.
To create custom currency formats
1. Click the Currency tab.
2. Select one of the currency formats from the list (CCA, CCB, CCC, CCD, and CCE).
3. Enter the prex, sufx, and decimal indicator values.
4. Click OK or Apply.
Output options
Output options control the default setting for a number of output options.
Outline labeling. Controls display of variable names, variable labels, data values, and value labels in the
outline pane of the Viewer.
Pivot table labeling. Controls display of variable names, variable labels, data values, and value labels in
pivot tables.
Descriptive variable and value labels (Variable view in the Data Editor, Label and Values columns) often
make it easier to interpret your results. However, long labels can be awkward in some tables. Changing
labeling options here only affects the default display for new output.
One click descriptives. Controls options for descriptive statistics generated for selected variables in the
Data Editor. See the topic “Obtaining Descriptive Statistics for Selected Variables” on page 58 for more
information.
• Suppress tables with many categories. For variables with more than the specied number of unique
values, frequency tables will not be displayed.
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• Include a chart in the output. For nominal and ordinal variables and variables with an unknown
measurement level, a bar chart is displayed. For continuous (scale) variables, a histogram is displayed.
Output display. Controls which type of output is generated for procedures that can generate either Model
Viewer output or pivot table and chart output. For version 27, this setting only applies to the Generalized
Linear Mixed Models procedure.
Screen Reader Accessibility. Controls how pivot table row and column labels are read by screen readers.
You can read full row and column labels for each data cell or read only the labels that change as you move
between data cells in the table.
Chart options
Chart Template
New charts can use either the settings selected here or the settings from a chart template le.
Available chart templates are provided in the drop-down list. The Samples section updates to reflect
the style of the selected chart template.
When User specied is selected from the drop-down list, click Browse to select a chart template le.
To create a chart template le, create a chart with the attributes that you want and save it as a
template (choose Save Chart Template from the File menu).
Current Settings
Available settings include:
Font
Font used for all text in new charts.
Style Cycle Preference
The initial assignment of colors and patterns for new charts. Cycle through colors only uses only
colors to differentiate chart elements and does not use patterns. Cycle through patterns only
uses only line styles, marker symbols, or ll patterns to differentiate chart elements and does not
use color.
Frame
Controls the display of inner and outer frames on new charts.
Grid Lines
Controls the display of scale and category axis grid lines on new charts.
Style Cycles
Customizes the colors, line styles, marker symbols, and ll patterns for new charts. You can change
the order of the colors and patterns that are used when a new chart is created.
Chart Aspect Ratio
The width-to-height ratio of the outer frame of new charts. You can specify a width-to-height ratio
from 0.1 to 10.0. Values less than 1 make charts that are taller than they are wide. Values greater
than 1 make charts that are wider than they are tall. A value of 1 produces a square chart. Once a
chart is created, its aspect ratio cannot be changed.
Sample Settings
The available settings provide options for displaying sample charts as either bar charts or
scatterplots.
Data Element Colors
Specify the order in which colors should be used for the data elements (such as bars and markers) in your
new chart. Colors are used whenever you select a choice that includes color in the Style Cycle Preference
group in the main Chart Options dialog box.
For example, if you create a clustered bar chart with two groups and you select Cycle through colors,
then patterns in the main Chart Options dialog box, the rst two colors in the Grouped Charts list are
used as the bar colors on the new chart.
To Change the Order in Which Colors Are Used
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185
1. Select Simple Charts and then select a color that is used for charts without categories.
2. Select Grouped Charts to change the color cycle for charts with categories. To change a category's
color, select a category and then select a color for that category from the palette.
Optionally, you can:
• Insert a new category above the selected category.
• Move a selected category.
• Remove a selected category.
• Reset the sequence to the default sequence.
• Edit a color by selecting its well and then clicking Edit.
Data Element Lines
Specify the order in which styles should be used for the line data elements in your new chart. Line styles
are used whenever your chart includes line data elements and you select a choice that includes patterns
in the Style Cycle Preference group in the main Chart Options dialog box.
For example, if you create a line chart with two groups and you select Cycle through patterns only in the
main Chart Options dialog box, the rst two styles in the Grouped Charts list are used as the line patterns
on the new chart.
To Change the Order in Which Line Styles Are Used
1. Select Simple Charts and then select a line style that is used for line charts without categories.
2. Select Grouped Charts to change the pattern cycle for line charts with categories. To change a
category's line style, select a category and then select a line style for that category from the palette.
Optionally, you can:
• Insert a new category above the selected category.
• Move a selected category.
• Remove a selected category.
• Reset the sequence to the default sequence.
Data Element Markers
Specify the order in which symbols should be used for the marker data elements in your new chart.
Marker styles are used whenever your chart includes marker data elements and you select a choice that
includes patterns in the Style Cycle Preference group in the main Chart Options dialog box.
For example, if you create a scatterplot chart with two groups and you select Cycle through patterns
only in the main Chart Options dialog box, the rst two symbols in the Grouped Charts list are used as the
markers on the new chart.
To Change the Order in Which Marker Styles Are Used
1. Select Simple Charts and then select a marker symbol that is used for charts without categories.
2. Select Grouped Charts to change the pattern cycle for charts with categories. To change a category's
marker symbol, select a category and then select a symbol for that category from the palette.
Optionally, you can:
• Insert a new category above the selected category.
• Move a selected category.
• Remove a selected category.
• Reset the sequence to the default sequence.
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Data Element Fills
Specify the order in which ll styles should be used for the bar and area data elements in your new chart.
Fill styles are used whenever your chart includes bar or area data elements, and you select a choice that
includes patterns in the Style Cycle Preference group in the main Chart Options dialog box.
For example, if you create a clustered bar chart with two groups and you select Cycle through patterns
only in the main Chart Options dialog box, the rst two styles in the Grouped Charts list are used as the
bar ll patterns on the new chart.
To Change the Order in Which Fill Styles Are Used
1. Select Simple Charts and then select a ll pattern that is used for charts without categories.
2. Select Grouped Charts to change the pattern cycle for charts with categories. To change a category's
ll pattern, select a category and then select a ll pattern for that category from the palette.
Optionally, you can:
• Insert a new category above the selected category.
• Move a selected category.
• Remove a selected category.
• Reset the sequence to the default sequence.
Pivot Tables options
Pivot Tables options set various options for the display of pivot tables.
TableLook
Select a TableLook from the list of les and click OK or Apply. You can use one of the TableLooks
provided with IBM SPSS Statistics, or you can create your own in the Pivot Table Editor (choose
TableLooks from the Format menu).
Browse
Allows you to select a TableLook from another directory.
Set TableLook Directory
Allows you to change the default TableLook directory. Use Browse to navigate to the directory you
want to use, select a TableLook in that directory, and then select Set TableLook Directory.
Note: TableLooks created in earlier versions of IBM SPSS Statistics cannot be used in version 16.0 or
later.
Column Widths
These options control the automatic adjustment of column widths in pivot tables.
Adjust for labels only
Adjusts column width to the width of the column label. This produces more compact tables, but data
values wider than the label may be truncated.
Adjust for labels and data for all tables
Adjusts column width to whichever is larger: the column label or the largest data value. This produces
wider tables, but it ensures that all values will be displayed.
Table Comment
You can automatically include comments for each table.
• Comment text is displayed in a tooltip when you hover over a table in the Viewer.
• Screen readers read the comment text when the table has focus.
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187
• The tooltip in the Viewer displays only the rst 200 characters of the comment, but screen readers read
the entire text.
• When you export output to HTML, the comment text is used as alt text.
Title
Include the table title in the comment.
Procedure
Include the name of the procedure that created the table.
Date
Includes the date the table was created.
Dataset
Includes the name of the dataset that was used to create the table.
Sample
The Sample section provides a visual representation of the selected TableLook.
Copying wide tables to the clipboard in rich text format
When pivot tables are pasted in Word/RTF format, tables that are too wide for the document width will
either be wrapped, scaled down to t the document width, or left unchanged.
Display "<.001" when signicance value is less than .001 (the observed value is observed)
When this setting is selected, small signicance values are presented as "<.001" in table output.
Show footnotes and captions in tables
Use this setting to displays or hide footnotes and captions in tables.
File Locations options
Options on the File Locations tab control the default location that the application will use for opening and
saving les at the start of each session, the location of the journal le, the location of the temporary
folder, the number of les that appear in the recently used le list, and the installation of Python 3.8 that
is used by the IBM SPSS Statistics - Integration Plug-in for Python.
Startup Folders for the Open and Save Dialogs
Specied folder
The specied folder is used as the default location at the start of each session. You can specify
different default locations for data and other (non-data) les.
Last folder used
The last folder used to either open or save les in the previous session is used as the default at the
start of the next session. This applies to both data and other (non-data) les.
These settings apply only to dialog boxes for opening and saving les—and the "last folder used" is
determined by the last dialog box used to open or save a le. Files opened or saved via command syntax
have no effect on—and are not affected by—these settings. These settings are only available in local
analysis mode. In distributed analysis mode connected to a remote server (requires IBM SPSS Statistics
Server), you cannot control the startup folder locations.
Session Journal
You can use the session journal to automatically record commands run in a session. This includes
commands entered and run in syntax windows and commands generated by dialog box choices. You can
edit the journal le and use the commands again in other sessions. You can turn journaling off and on,
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append or overwrite the journal le, and select the journal lename and location. You can copy command
syntax from the journal le and save it in a syntax le.
Temporary folder
This species the location of temporary les created during a session. In distributed mode (available with
the server version), this does not affect the location of temporary data les. In distributed mode, the
location of temporary data les is controlled by the environment variable SPSSTMPDIR, which can be set
only on the computer running the server version of the software. If you need to change the location of the
temporary directory, contact your system administrator.
Number of Recently Used Files to List
This controls the number of recently used les that appear on the File menu.
Python 2 Location - deprecated
These settings specify the installation of Python 2.7, which is no longer installed with IBM SPSS Statistics.
Python 3 is the recommended distribution.
If you choose to use Python 2, specify the path to the root directory of that Python installation. The
setting takes effect in the current session unless Python was already started by running a Python
program, a Python script, or an extension command that is implemented in Python. In that case, the
setting will be in effect in the next session. This setting is only available in local analysis mode. In
distributed analysis mode (requires IBM SPSS Statistics Server), the Python location on the remote server
is set from the IBM SPSS Statistics Administration Console. Contact your system administrator for
assistance.
Python 3 Location
These settings specify the installation of Python 3.8, which is used by the IBM SPSS Statistics -
Integration Plug-in for Python when you are running Python from SPSS Statistics. By default, the Python
distribution 3.8 that is installed with SPSS Statistics (as part of IBM SPSS Statistics - Essentials for
Python) is used. The distribution is in the Python3 directory under the directory where SPSS Statistics is
installed. To use a different installation of Python on your computer, specify the path to the root directory
of that installation of Python. The setting takes effect in the current session unless Python was already
started by running a Python program, a Python script, or an extension command that is implemented in
Python. In that case, the setting will be in effect in the next session. This setting is only available in local
analysis mode. In distributed analysis mode (requires IBM SPSS Statistics Server), the Python location on
the remote server is set from the IBM SPSS Statistics Administration Console. Contact your system
administrator for assistance.
Script options
Use the Scripts tab to specify the default script language and any autoscripts you want to use. You can
use scripts to automate many functions, including customizing pivot tables.
Note: Legacy Sax Basic users must manually convert any custom autoscripts. The autoscripts installed
with pre-16.0 versions are available as a set of separate script les located in the Samples subdirectory of
the directory where IBM SPSS Statistics is installed. By default, no output items are associated with
autoscripts. You must manually associate all autoscripts with the output items, as described below. For
information on converting legacy autoscripts, see “Compatibility with Versions Prior to 16.0” on page 259.
Default script language
The default script language determines the script editor that is launched when new scripts are
created. It also species the default language whose executable will be used to run autoscripts. The
available scripting languages depend on your platform. For Windows, the available scripting
languages are Basic, which is installed with the Core system, and the Python programming language.
For all other platforms, scripting is available with the Python programming language. You can choose
Python 3 as the default script language for the Python programming.
Chapter 18. Options
189
To use scripting with the Python programming language, you need IBM SPSS Statistics - Essentials for
Python, which is installed by default with your IBM SPSS Statistics product.
Enable Autoscripting
This check box allows you to enable or disable autoscripting. By default, autoscripting is enabled.
Base Autoscript
An optional script that is applied to all new Viewer objects before any other autoscripts are applied.
Specify the script le to be used as the base autoscript as well as the language whose executable will
be used to run the script.
Applying autoscripts to output items
1. In the Command Identiers grid, select a command that generates output items to which autoscripts
will be applied.
The Objects column, in the Objects and Scripts grid, displays a list of the objects associated with the
selected command. The Script column displays any existing script for the selected command.
2. Specify a script for any of the items shown in the Objects column. click the corresponding Script cell.
Enter the path to the script or click the ellipsis (...) button to browse for the script.
3. Specify the language whose executable will be used to run the script.
Note: The selected language is not affected by changing the default script language.
4. Click Apply or OK.
Removing autoscript associations
1. In the Objects and Scripts grid, click the cell in the Script column corresponding to the script to
dissociate.
2. Delete the path to the script and then click any other cell in the Objects and Scripts grid.
3. Click Apply or OK.
Multiple imputations options
The Multiple Imputations tab controls two kinds of preferences related to Multiple Imputations:
Marking of Imputed Data. By default, cells containing imputed data will have a different background
color than cells containing nonimputed data. The distinctive appearance of the imputed data should make
it easy for you to scroll through a dataset and locate those cells. You can change the default cell
background color, the font, and make the imputed data display in bold type.
Analysis Output. This group controls the type of Viewer output produced whenever a multiply imputed
dataset is analyzed. By default, output will be produced for the original (pre-imputation) dataset and for
each of the imputed datasets. In addition, for those procedures that support pooling of imputed data,
nal pooled results will be generated. When univariate pooling is performed, pooling diagnostics will also
display. However, you can suppress any output you do not want to see.
To Set Multiple Imputation Options
From the menus, choose:
Edit > Options
Click the Multiple Imputation tab.
Syntax editor options
Syntax Color Coding
You can turn color coding of commands, subcommands, keywords, keyword values, and comments off or
on and you can specify the font style and color for each.
Error Color Coding
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You can turn color coding of certain syntactical errors off or on and you can specify the font style and
color used. Both the command name and the text (within the command) containing the error are color
coded, and you can choose different styles for each. See the topic “Color Coding” on page 159 for more
information.
Auto-Complete Settings
You can turn automatic display of the auto-complete control off or on. The auto-complete control can
always be displayed by pressing Ctrl+Spacebar. See the topic “Auto-Completion” on page 159 for more
information.
Indent size
Species the number of spaces in an indent. The setting applies to indenting selected lines of syntax as
well as to automatic indentation.
Gutter
These options specify the default behavior for showing or hiding line numbers and command spans within
the Syntax Editor's gutter--the region to the left of the text pane that is reserved for line numbers,
bookmarks, breakpoints, and command spans. Command spans are icons that provide visual indicators of
the start and end of a command.
Panes
Display the navigation pane. This species the default for showing or hiding the navigation pane. The
navigation pane contains a list of all recognized commands in the syntax window, displayed in the order in
which they occur. Clicking on a command in the navigation pane positions the cursor at the start of the
command.
Automatically open Error Tracking pane when errors are found. This species the default for showing
or hiding the error tracking pane when run-time errors are found.
Optimize for right to left languages. Check this box for the best user experience when working with right
to left languages.
Paste syntax from dialogs. Species the position at which syntax is inserted into the designated syntax
window when pasting syntax from a dialog. After last command inserts pasted syntax after the last
command. At cursor or selection inserts pasted syntax at the position of the cursor; or, if a block of
syntax is selected, then the selection will be replaced by the pasted syntax.
Privacy options
The Privacy tab provides options for:
Allow SPSS Statistics to share your information with IBM
When enabled, SPSS Statistics shares your usage and performance data with IBM.
The setting helps improve SPSS Statistics. All collected data is transmitted securely.
Disable SPSS Statistics from retrieving Welcome dialog content updates
When enabled, SPSS Statistics will not automatically retrieve Welcome dialog content updates. The
updates may include features enhancement information, and other product specic information.
Disable SPSS Statistics from sending error reports to IBM
When enabled, SPSS Statistics does not automatically send error reports to IBM.
Setting Privacy options
1. From the menus, choose: Edit > Options...
2. Click the Privacy tab.
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Chapter 19. Customizing Menus and Toolbars
Customizing Menus and Toolbars
Menu Editor
You can use the Menu Editor to customize your menus. With the Menu Editor you can:
• Add menu items that run customized scripts.
• Add menu items that run command syntax les.
• Add menu items that launch other applications and automatically send data to other applications.
You can send data to other applications in the following formats: IBM SPSS Statistics, Excel, Lotus 1-2-3,
tab-delimited, and dBASE IV.
To Add Items to Menus
1. From the menus choose:
View > Menu Editor...
2. In the Menu Editor dialog box, double-click the menu (or click the plus sign icon) to which you want to
add a new item.
3. Select the menu item above which you want the new item to appear.
4. Click Insert Item to insert a new menu item.
5. Enter the text for the new item. On Windows operating systems, an ampersand (&) before a letter
species that letter should be used as the underlined mnemonic key.
6. Select the le type for the new item (script le, command syntax le, or external application).
7. Click Browse to select a le to attach to the menu item.
You can also add entirely new menus and separators between menu items. Optionally, you can
automatically send the contents of the Data Editor to another application when you select that application
on the menu.
Customizing Toolbars
You can customize toolbars and create new toolbars. Toolbars can contain any of the available tools,
including tools for all menu actions. They can also contain custom tools that launch other applications,
run command syntax les, or run script les.
Show Toolbars
Use Show Toolbars to show or hide toolbars, customize toolbars, and create new toolbars. Toolbars can
contain any of the available tools, including tools for all menu actions. They can also contain custom tools
that launch other applications, run command syntax les, or run script les.
To Customize Toolbars
1. From the menus choose:
View > Toolbars > Customize
2. Select the toolbar you want to customize and click Edit, or click New to create a new toolbar.
3. For new toolbars, enter a name for the toolbar, select the windows in which you want the toolbar to
appear, and click Edit.
4. Select an item in the Categories list to display available tools in that category.
5. Drag and drop the tools you want onto the toolbar displayed in the dialog box.
6. To remove a tool from the toolbar, drag it anywhere off the toolbar displayed in the dialog box.
To create a custom tool to open a le, to run a command syntax le, or to run a script:
7. Click New Tool in the Edit Toolbar dialog box.
8. Enter a descriptive label for the tool.
9. Select the action you want for the tool (open a le, run a command syntax le, or run a script).
10. Click Browse to select a le or application to associate with the tool.
New tools are displayed in the User-Dened category, which also contains user-dened menu items.
Toolbar Properties
Use Toolbar Properties to select the window types in which you want the selected toolbar to appear. This
dialog box is also used for creating names for new toolbars.
To Set Toolbar Properties
1. From the menus choose:
View > Toolbars > Customize
2. For existing toolbars, click Edit, and then click Properties in the Edit Toolbar dialog box.
3. For new toolbars, click New Tool.
4. Select the window types in which you want the toolbar to appear. For new toolbars, also enter a
toolbar name.
Edit Toolbar
Use the Edit Toolbar dialog box to customize existing toolbars and create new toolbars. Toolbars can
contain any of the available tools, including tools for all menu actions. They can also contain custom tools
that launch other applications, run command syntax les, or run script les.
To Change Toolbar Images
1. Select the tool for which you want to change the image on the toolbar display.
2. Click Change Image.
3. Select the image le that you want to use for the tool. The following image formats are supported:
BMP, PNG, GIF, JPG.
• Images should be square. Images that are not square are clipped to a square area.
• Images are automatically scaled to t. For optimal display, use 16x16 pixel images for small toolbar
images or 32x32 pixel images for large toolbar images.
Create New Tool
Use the Create New Tool dialog box to create custom tools to launch other applications, run command
syntax les, and run script les.
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Chapter 20. Extensions
Extensions are custom components that extend the capabilities of IBM SPSS Statistics. Extensions are
packaged in extension bundles (.spe les) and are installed to IBM SPSS Statistics. Extensions can be
created by any user and shared with other users by sharing the associated extension bundle.
The following utilities are provided for working with extensions:
• The “Extension Hub” on page 195, which is accessed from Extensions > Extension Hub, is an interface
for searching for, downloading, and installing extensions from the IBM SPSS Predictive Analytics
collection on GitHub. From the Extension Hub dialog, you can also view details of the extensions that
are installed on your computer, get updates for installed extensions, and remove extensions.
• You can install an extension bundle that is stored on your local computer from Extensions > Install
Local Extension Bundle.
• You can use the Custom Dialog Builder for Extensions to create an extension that includes a user
interface, which is referred to as a custom dialog. Custom dialogs generate SPSS Statistics command
syntax that carries out the tasks that are associated with the extension. You design the generated
syntax as part of designing the custom dialog.
• You can use the Create Extension Bundle and Edit Extension Bundle dialogs for cases where you can't
use the Custom Dialog Builder for Extensions. For more information, see the topic “Creating and editing
extension bundles” on page 233.
Extension Hub
From the Extension Hub dialog, you can do the following tasks:
• Explore extensions that are available from the IBM SPSS Predictive Analytics collection on GitHub. You
can select extensions to install now or you can download selected extensions and install them later.
• Get updated versions of extensions that are already installed on your computer.
• View details about the extensions that are already installed on your computer.
• Remove extensions that are installed on your computer.
To download or remove extensions:
1. From the menus, choose: Extensions > Extension Hub
2. Select the extensions that you want to download or remove and click OK. All selections that are made
on the Explore and Installed tabs are processed when you click OK.
By default, the extensions that are selected for download are downloaded and installed on your
computer. From the Settings tab, you can choose to download the selected extensions to a specied
location without installing them. You can then install them later by choosing Extensions > Install Local
Extension Bundle. For Windows and Mac, you can install an extension by double-clicking the extension
bundle le.
Important:
• Extensions are always installed, or downloaded, to your local computer. If you work in distributed
analysis mode, then see the topic “Installing local extension bundles” on page 197 for further details.
• For Windows 7 and later, installing an updated version of an existing extension bundle might require
running IBM SPSS Statistics with administrator privileges. You can start IBM SPSS Statistics with
administrator privileges by right-clicking the icon for IBM SPSS Statistics and choosing Run as
administrator. In particular, if you receive an error message that states that one or more extension
bundles could not be installed, then try running with administrator privileges.
Note: The license that you agree to when you install an extension can be viewed at any later time by
clicking More info... for the extension on the Installed tab.
Explore tab
The Explore tab displays all of the extensions that are available from the IBM SPSS Predictive Analytics
collection on GitHub (https://ibmpredictiveanalytics.github.io/). From the Explore tab, you can select new
extensions to download and install, and you can select updates for extensions that are already installed
on your computer. The Explore tab requires an internet connection.
• For each extension, the number of the latest version and the associated date of that version are
displayed. A brief summary of the extension is also provided. For extensions that are already installed
on your computer, the installed version number is also displayed.
• You can view detailed information about an extension by clicking More info. When an update is
available, More info displays information about the update.
• You can view the prerequisites for running an extension, such as whether the IBM SPSS Statistics -
Integration Plug-in for R is required, by clicking Prerequisites. When an update is available,
Prerequisites displays information about the update.
Rene by
You can rene the set of extensions that are displayed. You can rene by general categories of
extensions, the language in which the extension is implemented, the type of organization that provided
the extension, or the state of the extension. For each group, such as Category, you can select multiple
items by which to rene the displayed list of extensions. You can also rene by search terms. Searches
are not case-sensitive, and the asterisk (*) is treated as any other character and does not indicate a
wildcard search.
• To rene the displayed list of extensions, click Apply. Pressing the enter key when the cursor is in the
Search box has the same effect as clicking Apply.
• To reset the list to display all available extensions, delete any text in the Search box, deselect all items,
and click Apply.
Installed tab
The Installed tab displays all of the extensions that are installed on your computer. From the Installed
tab, you can select updates for installed extensions that are available from the IBM SPSS Predictive
Analytics collection on GitHub and you can remove extensions. To get updates for installed extensions,
you must have an internet connection.
• For each extension, the installed version number is displayed. When an internet connection is available,
the number of the latest version and the associated date of that version are displayed. A brief summary
of the extension is also provided.
• You can view detailed information about an extension by clicking More info. When an update is
available, More info displays information about the update.
• You can view the prerequisites for running an extension, such as whether the IBM SPSS Statistics -
Integration Plug-in for R is required, by clicking Prerequisites. When an update is available,
Prerequisites displays information about the update.
Rene by
You can rene the set of extensions that are displayed. You can rene by general categories of
extensions, the language in which the extension is implemented, the type of organization that provided
the extension, or the state of the extension. For each group, such as Category, you can select multiple
items by which to rene the displayed list of extensions. You can also rene by search terms. Searches
are not case-sensitive, and the asterisk (*) is treated as any other character and does not indicate a
wildcard search.
• To rene the displayed list of extensions, click Apply. Pressing the enter key when the cursor is in the
Search box has the same effect as clicking Apply.
• To reset the list to display all available extensions, delete any text in the Search box, deselect all items,
and click Apply.
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Private extensions
Private extensions are extensions that are installed on your computer but are not available from the IBM
SPSS Predictive Analytics collection on GitHub. The features for rening the set of displayed extensions
and for viewing the prerequisites to run an extension are not available for private extensions.
Note: When using the Extension Hub without an internet connection, some of the features of the Installed
tab might not be available.
Settings
The Settings tab species whether extensions that are selected for download are downloaded and then
installed or downloaded but not installed. This setting applies to new extensions and updates to existing
extensions. You might choose to download extensions without installing them if you are downloading
extensions to distribute to other users within your organization. You might also choose to download, but
not install, extensions if you don't have the prerequisites for running the extensions but plan to get the
prerequisites.
If you choose to download extensions without installing them, you can install them later by choosing
Extensions > Install Local Extension Bundle. For Windows and Mac, you can install an extension by
double-clicking the extension bundle le.
Extension Details
The Extension Details dialog box displays the information that was provided by the author of the
extension. In addition to required information, such as Summary, and Version, the author might have
included URLs to locations of relevance, such as the author's home page. If the extension was
downloaded from the Extension Hub, then it includes a license that can be viewed by clicking View
license.
Components. The Components group lists the custom dialogs, if any, and the names of any extension
commands that are included in the extension. Extension commands can be run from the syntax editor in
the same manner as built-in IBM SPSS Statistics commands. Help for an extension command might be
available by positioning the cursor within the command (in a syntax window) and pressing the F1 key.
Help might also be available by running CommandName /HELP in the syntax editor.
Note: Installing an extension that contains a custom dialog might require a restart of IBM SPSS Statistics
to see the entry for the dialog in the Components table.
Dependencies. The Dependencies group lists add-ons that are required to run the components included
in the extension.
• Integration Plug-Ins for Python and R. The components for an extension may require the Integration
Plug-in for Python, or the Integration Plug-in for R, or both. The Integration Plug-in for Java
™
is installed
with the Core system and does not require separate installation.
• R packages. Lists any R packages that are required by the extension. During installation of the
extension, the installer attempts to download and install the necessary packages on your machine. If
this process fails, you will be alerted and you will then need to manually install the packages. See the
topic “Required R packages” on page 199
for more information.
• Python modules. Lists any Python modules that are required by the extension. Any such modules may
be available from the IBM SPSS Predictive Analytics community at https://www.ibm.com/community/
spss-statistics . Copy the modules to a location specied for extension commands as shown in the
output from the SHOW EXTPATHS command. Alternatively, you can copy the modules to a location on
the Python search path, such as the Python site-packages directory.
• Extensions. Lists the names of any extensions that are required by the current extension. Any such
extensions might be available for download from the Extension Hub.
Installing local extension bundles
To install an extension bundle that is stored on your local computer:
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197
1. From the menus choose:
Extensions > Install Local Extension Bundle...
2. Select the extension bundle. Extension bundles have a le type of spe.
You can also install extension bundles with a command line utility that allows you to install multiple
bundles at once. See the topic “Batch installation of extension bundles” on page 199 for more
information.
Installing extension bundles in distributed mode
If you work in distributed mode, then you must install the extension bundle on the associated IBM SPSS
Statistics Server, using the command line utility. If the extension bundle contains a custom dialog, then
you must also install the extension bundle on your local machine (from the menus, as described
previously). If you don't know whether the extension bundle contains a custom dialog, then it is best to
install the extension bundle on your local machine and on the IBM SPSS Statistics Server machine. For
information on using the command line utility, see “Batch installation of extension bundles” on page 199.
Important: For users of Windows 7 and later versions of Windows, installing an updated version of an
existing extension bundle might require running IBM SPSS Statistics with administrator privileges. You
can start IBM SPSS Statistics with administrator privileges by right-clicking the icon for IBM SPSS
Statistics and choosing Run as administrator. In particular, if you receive an error message that states
that one or more extension bundles could not be installed, then try running with administrator privileges.
Installation locations for extensions
By default, extensions are installed to a general user-writable location for your operating system. To view
the location, run the SHOW EXTPATHS syntax command. The output displays a list of locations, under the
heading "Locations for extension commands," for installing extensions. Extensions are installed to the
rst writable location in the list.
You can override the default location by dening a path with the SPSS_EXTENSIONS_PATH environment
variable. For multiple locations, separate each with a semicolon on Windows and a colon on Linux and
Mac. The specied location must exist on the target computer. After you set SPSS_EXTENSIONS_PATH,
you must restart IBM SPSS Statistics for the changes to take effect.
Custom dialogs, contained in extension bundles, are installed to the rst writable location in the list under
the heading "Locations for custom dialogs" in the output from the SHOW EXTPATHS syntax command. You
can override the default location by dening a path with the SPSS_CDIALOGS_PATH environment
variable, with the same specications as for the SPSS_EXTENSIONS_PATH environment variable.
Note: For an extension that is implemented in Python 3, you can specify alternative installation locations
with the SPSSEX_EXTENSIONS_PATH and SPSSEX_CDIALOGS_PATH environment variables. The
SPSSEX_EXTENSIONS_PATH and SPSSEX_CDIALOGS_PATH variables have the same specications as
SPSS_EXTENSIONS_PATH and SPSS_CDIALOGS_PATH and take precedence over them and over the
default installation location for extensions. The SPSSEX_EXTENSIONS_PATH and
SPSSEX_CDIALOGS_PATH environment variables apply only in the case that Python 3 is specied as the
Python Version for the extension. You can view the Python Version from the Extension Details dialog,
which is accessed by clicking More info for the associated extension in the Extension Hub dialog.
To create an environment variable on Windows, from the Control Panel:
Windows 7
1. Select User Accounts.
2. Select Change my environment variables.
3. Click New, enter the name of the environment variable (for instance, SPSS_EXTENSIONS_PATH) in the
Variable name eld and enter the path or paths in the Variable value eld.
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Windows 8
1. Select System.
2. Select the Advanced tab and click Environment Variables. The Advanced tab is accessed from
Advanced system settings.
3. In the User variables section, click New, enter the name of the environment variable (for instance,
SPSS_EXTENSIONS_PATH) in the Variable name eld and enter the path or paths in the Variable
value eld.
Windows 10
1. Enter envrionment variable in the Windows search eld and click the Edit the system
environment variables result that is provided. The System Properties dialog opens to the Advanced
tab, which provides the Environment Variables... control.
2. Click Environment Variables... to open the Environment Variables dialog.
3. In the User variables for <username> section, click New, enter the name of the environment variable
(for instance, SPSS_EXTENSIONS_PATH) in the Variable name eld and enter the path or paths in the
Variable value eld.
Important: For users of Windows 7 and later versions of Windows, installing an updated version of an
existing extension bundle might require running IBM SPSS Statistics with administrator privileges. You
can start IBM SPSS Statistics with administrator privileges by right-clicking the icon for IBM SPSS
Statistics and choosing Run as administrator. In particular, if you receive an error message that states
that one or more extension bundles could not be installed, then try running with administrator privileges.
Required R packages
The extension installer attempts to download and install any R packages that are required by the
extension and not found on your computer. If you do not have internet access, you will need to obtain the
necessary packages from someone who does. If installation of the packages fails, you will be alerted with
the list of required packages. You can also view the list from the Extension Details dialog box, once the
extension is installed. See the topic “Extension Details” on page 197
for more information. Packages can
be downloaded from http://www.r-project.org/ and then installed from within R. For details, see the R
Installation and Administration guide, distributed with R.
Note: For UNIX (including Linux) users, packages are downloaded in source form and then compiled. This
requires that you have the appropriate tools installed on your machine. See the R Installation and
Administration guide for details. In particular, Debian users should install the r-base-dev package from
apt-get install r-base-dev.
Permissions
By default, required R packages are installed to the library folder under the location where R is
installed (for example, C:\Program Files\R\R-3.6.x\library on Windows). If you do not have write
permission to this location or would like to store R packages--installed for extensions--elsewhere, you
can specify one or more alternate locations by dening the SPSS_RPACKAGES_PATH environment
variable. When present, the paths specied in SPSS_RPACKAGES_PATH are added to the R library search
path and take precedence over the default location. R packages will be installed to the rst writable
location. For multiple locations, separate each with a semicolon on Windows and a colon on Linux and
Mac. The specied locations must exist on the target machine. After setting SPSS_RPACKAGES_PATH,
you will need to restart IBM SPSS Statistics for the changes to take effect. For information on how to set
an environment variable on Windows, see “Installation locations for extensions” on page 198.
Batch installation of extension bundles
You can install multiple extension bundles at once using the batch utility installextbundles.bat
(installextbundles.sh for Mac and UNIX systems) located in the IBM SPSS Statistics installation
directory. For Windows and Mac, the utility is located at the root of the installation directory. For Linux and
IBM SPSS Statistics Server for UNIX, the utility is located in the bin subdirectory of the installation
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199
directory. The utility is designed to run from a command prompt and must be run from its installed
location. The form of the command line is:
installextbundles [–statssrv] [–download no|yes ] –source <folder> | <filename>...
-statssrv. Species that you are running the utility on a IBM SPSS Statistics Server. You should also install
the same extension bundles on client machines that connect to the server.
-download no|yes. Species whether the utility has permission to access the internet in order to
download any R packages required by the specied extension bundles. The default is no. If you keep the
default or do not have internet access then you will need to manually install any required R packages. See
the topic “Required R packages” on page 199 for more information.
–source <folder> | <lename>... Species the extension bundles to install. You can specify the path to a
folder containing extension bundles or you can specify a list of lenames of extension bundles. If you
specify a folder, all extension bundles (les of type .spe) found in the folder will be installed. Separate
multiple lenames with one or more spaces. Enclose paths with double-quotes if they contain spaces.
Note: When running installextbundles.sh on IBM SPSS Statistics Server for UNIX, the Bash shell
must be present on the server machine.
Creating and managing custom dialogs
The Custom Dialog Builder creates custom dialogs for generating command syntax.
Using the Custom Dialog Builder you can:
• Create your own version of a dialog for a built-in IBM SPSS Statistics procedure. For example, you can
create a dialog for the Frequencies procedure that only allows the user to select the set of variables and
then generates command syntax with pre-set options that standardize the output.
• Create a user interface that generates command syntax for an extension command. Extension
commands are user-dened IBM SPSS Statistics commands that are implemented in the Python
programming language, R or Java. See the topic “Custom Dialogs for Extension Commands” on page
231 for more information.
• Open a le containing the specication for a custom dialog--perhaps created by another user--and add
the dialog to your installation of IBM SPSS Statistics, optionally making your own modications.
• Save the specication for a custom dialog so that other users can add it to their installations of IBM
SPSS Statistics.
The Custom Dialog Builder supports two modes of operation:
Custom Dialog Builder for Extensions
This mode creates and modies custom dialogs within new or existing extensions. When you open the
Custom Dialog Builder in this mode, a new extension that contains an empty custom dialog is created.
When you save or install custom dialogs in this mode, they are saved or installed as part of an
extension.
Dialogs that you create in this mode are referred to as enhanced custom dialogs. Enhanced custom
dialogs have many new features that were not available in releases of IBM SPSS Statistics before
release 24. In that regard, enhanced dialogs are incompatible with pre-24 releases.
To open the Custom Dialog Builder in this mode, from the menus choose:
Extensions > Custom Dialog Builder for Extensions
Custom Dialog Builder - Compatibility mode
This mode creates and modies custom dialogs that are compatible with all releases of IBM SPSS
Statistics and are referred to as compatible custom dialogs. Compatible custom dialogs do not have
the added features that are available with enhanced dialogs.
• The controls and control properties that are supported in compatibility mode are the same controls
and properties that are supported in the Custom Dialog Builder in pre-24 releases.
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• When you save a dialog in compatibility mode, it is saved as a compatible custom dialog package
(.spd) le, which you can then add to an extension.
• You can convert a dialog that is open in compatibility mode to an enhanced dialog that is then part
of a new extension.
To open the Custom Dialog Builder in compatibility mode, from the menus choose:
Extensions > Utilities > Custom Dialog Builder (Compatibility mode)...
Custom Dialog Builder layout
Canvas
The canvas is the area of the Custom Dialog Builder where you design the layout of your dialog.
Properties Pane
The properties pane is the area of the Custom Dialog Builder where you specify properties of the controls
that make up the dialog as well as properties of the dialog itself, such as the menu location.
Tools Palette
The tools palette provides the set of controls that can be included in a custom dialog. You can show or
hide the Tools Palette by choosing Tools Palette from the View menu.
Syntax Template
The Syntax Template species the command syntax that is generated by the custom dialog. You can
move the Syntax Template pane to a separate window by clicking Move to New Window. To move a
separate Syntax Template window back into the Custom Dialog Builder, click Restore to Main Window.
Building a custom dialog
The basic steps involved in building a custom dialog are:
Note: If you are working in compatibility mode, then some special considerations apply as noted in what
follows.
1. Specify the properties of the dialog itself, such as the title that appears when the dialog is launched
and the location of the new menu item for the dialog within the IBM SPSS Statistics menus. See the
topic “Dialog Properties” on page 202
for more information.
2. Specify the controls, such as source and target variable lists, that make up the dialog and any sub-
dialogs. See the topic “Control types” on page 206 for more information.
3. Create the syntax template that species the command syntax to be generated by the dialog. See the
topic “Building the Syntax Template” on page 204 for more information.
4. Specify properties of the extension that contains your dialog. See the topic “Extension Properties” on
page 225 for more information.
Note: This step does not apply in Compatibility mode.
5. Install the extension that contains the dialog to IBM SPSS Statistics and/or save the extension to an
extension bundle (.spe) le. See the topic “Managing custom dialogs” on page 228 for more
information.
Note: In Compatibility mode, you install the dialog to IBM SPSS Statistics and/or save the specication
for the dialog to a compatible custom dialog package (.spd) le. See the topic “Managing custom
dialogs in compatibility mode” on page 229 for more information.
You can preview your dialog as you're building it. See the topic “Previewing a custom dialog” on page 205
for more information.
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Dialog Properties
To view and set Dialog Properties:
1. Click on the canvas in an area outside of any controls. With no controls on the canvas, Dialog
Properties are always visible.
Dialog Name. The Dialog Name property is required and species a unique name to associate with the
dialog. To minimize the possibility of name conflicts, you may want to prex the dialog name with an
identier for your organization, such as a URL.
Menu Location. Click the ellipsis (...) button to open the Menu Location dialog box, which allows you to
specify the name and location of the menu item for the custom dialog.
Title. The Title property species the text to be displayed in the title bar of the dialog box.
Help File. The Help File property is optional and species the path to a help le for the dialog. This is the
le that will be launched when the user clicks the Help button on the dialog. Help les must be in HTML
format. A copy of the specied help le is included with the specications for the dialog when the dialog is
installed or saved. The Help button on the run-time dialog is hidden if there is no associated help le.
• Localized versions of the help le that exist in the same directory as the help le are automatically
added to the dialog when you add the help le. Localized versions of the help le are named <Help
File>_<language identifier>.htm. For more information, see the topic “Creating Localized
Versions of Custom Dialogs” on page 231.
• Supporting les, such as image les and style sheets, can be added to the dialog by rst saving the
dialog. You then manually add the supporting les to the dialog le (.cfe or .spd). For information
about accessing and manually modifying custom dialog les, see the section that is titled "To localize
dialog strings" in the topic “Creating Localized Versions of Custom Dialogs” on page 231.
Web Deployment Properties. Allows you to associate a properties le with this dialog for use in building
thin client applications that are deployed over the web.
Modeless. Species whether the dialog is modal or modeless. When a dialog is modal, it must be closed
before the user can interact with the main application windows (Data, Output, and Syntax) or with other
open dialogs. Modeless dialogs do not have that constraint. The default is modeless.
Data Source. Species the source of the elds that are displayed in Source List, Target List, and Field
Chooser controls. By default, the active dataset is the data source. You can specify a Dataset Selector
control as the data source. At run time, the dataset that is selected in the control is the data source. Click
the ellipsis (...) button to open the dialog box and specify the data source.
Required Add-Ons. Species one or more add-ons--such as the Integration Plug-in for Python or the
Integration Plug-in for R--that are required in order to run the command syntax generated by the dialog.
For example, if the dialog generates command syntax for an extension command implemented in R, then
check the box for the Integration Plug-in for R. Users will be warned about required add-ons that are
missing when they try to install or run the dialog.
Note: The Required Add-Ons property applies only in Compatibility mode. When you are working with the
Custom Dialog Builder for Extensions, any required add-ons are specied as part of the extension
properties.
Specifying the Data Source for a Dialog
The Data Source dialog box species the source of the elds that are displayed in Source List, Target List,
and Field Chooser controls. By default, the active dataset is the data source. You can specify a Dataset
Selector control as the data source. At run time, the dataset that is selected in the control is the data
source.
Specifying the Menu Location for a Custom Dialog
The Menu Location dialog box is used to specify the name and location of the menu item for a custom
dialog. Menu items for custom dialogs do not appear in the Menu Editor within IBM SPSS Statistics. If you
are working in compatibility mode, then see the Compatibility Mode section for instructions.
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1. Double-click the menu (or click the plus sign icon) to which you want to add the item for the new
dialog. By default, the dialog is installed to all window types (Data Editor, Syntax, and Viewer) and the
menus that are common to all window types are displayed. You can choose to install the dialog to a
particular window type, and display the menus for that window type, by selecting the window type
from the Install to list.
2. Select the menu item above which you want the item for the new dialog to appear and click Add. After
the item is added, you can use Move Up and Move Down to reposition it. You can also move the item
under a new submenu by clicking Move Under New Menu. When the dialog is installed, the submenu
is added to the IBM SPSS Statistics menu system if it is not already present.
3. Enter the name of the menu item. Names within a particular menu or submenu must be unique.
Compatibility Mode
1. Double-click the menu (or click the plus sign icon) to which you want to add the item for the new
dialog.
If you want to create custom menus or submenus, use the Menu Editor. For more information, see the
topic “Menu Editor” on page 193, and also see the associated note in the Note section.
2. Select the menu item above which you want the item for the new dialog to appear. After the item is
added, you can use the Move Up and Move Down buttons to reposition it.
3. Enter a title for the menu item. Titles within a particular menu or submenu must be unique.
4. Click Add.
Options
• Add a separator above or below the new menu item.
• Specify the path to an image that appears next to the menu item for the custom dialog. The supported
image types are gif and png. The image cannot be larger than 16 x 16 pixels.
Note:
• The Menu Location dialog box displays menus for all add-on modules. Be sure to add the menu item for
your custom dialog to a menu that is available to you or other users of your dialog.
• If you add your dialog to a menu that was created from the Menu Editor (View>Menu Editor), then
users of your dialog must manually create the same menu from their Menu Editor. Otherwise, the dialog
is added to their Extensions menu.
Laying out controls on the canvas
You add controls to a custom dialog by dragging them from the tools palette onto the canvas. The canvas
is divided into four functional columns in which you can place controls. The following considerations
apply:
• The rst (leftmost) column is primarily intended for a Source List control. Source List controls must in
fact be in the rst column.
• Target List controls must be in the second column.
• Sub-dialog buttons must be in the rightmost column (for example, the third column if only three
columns are used) and no other controls can be in the same column as Sub-dialog buttons. In that
regard, the fourth column can contain only Sub-dialog buttons.
Note: In compatibility mode, only three columns are available for laying out controls.
Although not shown on the canvas, each custom dialog contains OK, Paste, Cancel, and Help buttons
positioned across the bottom of the dialog. The presence and locations of these buttons is automatic,
however, the Help button is hidden if there is no help le associated with the dialog (as specied by the
Help File property in Dialog Properties).
You can change the vertical order of the controls within a column by dragging them up or down, but the
exact position of the controls is determined automatically for you. At run-time, controls resize in
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appropriate ways when the dialog itself is resized. Controls such as source and target lists automatically
expand to ll the available space below them.
Building the Syntax Template
The syntax template species the command syntax that will be generated by the custom dialog. A single
custom dialog can generate command syntax for any number of built-in IBM SPSS Statistics commands or
extension commands.
The syntax template can consist of static text that is always generated and control identiers that are
replaced at run time with the values of the associated custom dialog controls. For example, command
names and subcommand specications that don't depend on user input would be static text. The set of
variables that is specied in a target list, however, would be represented with the control identier for the
target list control.
To Build the Syntax Template
1. For static command syntax that does not depend on user-specied values, enter the syntax as you
would in the Syntax Editor. The Syntax Template supports the auto-completion and color coding
features of the Syntax Editor. See the topic “Using the Syntax Editor” on page 157 for more
information.
2. Add control identiers of the form %%Identifier%% at the locations where you want to insert
command syntax that is generated by controls, where Identifier is the value of the Identier
property for the control.
• You can insert a control identier by selecting a row in the table of identiers, right-clicking and
selecting Add to syntax template. You can also insert a control identier by right-clicking a control
on the canvas and selecting Add to syntax template.
• You can also select from a list of available control identiers by pressing Ctrl+Spacebar. The list
contains the control identiers followed by the items available with the syntax auto-completion
feature.
If you manually enter identiers, retain any spaces, since all spaces in identiers are signicant.
At run time, and for all controls other than check boxes and check box groups, each identier is
replaced with the current value of the Syntax property of the associated control. For check boxes and
check box groups, the identier is replaced by the current value of the Checked Syntax or Unchecked
Syntax property of the associated control, depending on the current state of the control--checked or
unchecked. See the topic “Control types” on page 206 for more information.
Note: The syntax that is generated at run-time automatically includes a command terminator (period) as
the very last character if one is not present.
Example: Including Run-time Values in the Syntax Template
Consider a simplied version of the Frequencies dialog that contains only a source list control and a target
list control, and generates command syntax of the following form:
FREQUENCIES VARIABLES=var1 var2...
/FORMAT = NOTABLE
/BARCHART.
The syntax template to generate this syntax might look like:
FREQUENCIES VARIABLES=%%target_list%%
/FORMAT = NOTABLE
/BARCHART.
• %%target_list%% is the value of the Identier property for the target list control. At run time it will be
replaced by the current value of the Syntax property of the control.
• Dening the Syntax property of the target list control to be %%ThisValue%% species that at run time,
the current value of the property will be the value of the control, which is the set of variables in the
target list.
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Example: Including Command Syntax from Container Controls
Building on the previous example, consider adding a Statistics sub-dialog that contains a single group of
check boxes that allow a user to specify mean, standard deviation, minimum, and maximum. Assume that
the check boxes are contained in an item group control.
An example of the generated command syntax would be:
FREQUENCIES VARIABLES=var1 var2...
/FORMAT = NOTABLE
/STATISTICS MEAN STDDEV
/BARCHART.
The syntax template to generate this syntax might look like:
FREQUENCIES VARIABLES=%%target_list%%
/FORMAT = NOTABLE
%%stats_group%%
/BARCHART.
• %%target_list%% is the value of the Identier property for the target list control and %
%stats_group%% is the value of the Identier property for the item group control.
The following denitions illustrate one way to specify the Syntax properties of the item group and the
check boxes that are contained within it to generate the correct result. The Syntax property of the target
list would be set to %%ThisValue%%, as described in the previous example.
Syntax property of item group: /STATISTICS %%ThisValue%%
Checked Syntax property of mean check box: MEAN
Checked Syntax property of stddev check box: STDDEV
Checked Syntax property of min check box: MINIMUM
Checked Syntax property of max check box: MAXIMUM
At run time, %%stats_group%% will be replaced by the current value of the Syntax property for the item
group control. Specically, %%ThisValue%% will be replaced by a blank-separated list of the values of the
Checked or Unchecked Syntax property of each check box, depending on its state--checked or
unchecked. Since we only specied values for the Checked Syntax property, only checked boxes will
contribute to %%ThisValue%%. For example, if the user checks the mean and standard deviation boxes,
the run time value of the Syntax property for the item group will be /STATISTICS MEAN STDDEV.
If no boxes are checked, then the Syntax property for the item group control will be empty, and the
generated command syntax will not contain any reference to %%stats_group%%. This might or might not
be desirable. For example, even with no boxes checked you might still want to generate the STATISTICS
subcommand. This can be accomplished by referencing the identiers for the check boxes directly in the
syntax template, as in:
FREQUENCIES VARIABLES=%%target_list%%
/FORMAT = NOTABLE
/STATISTICS %%stats_mean%% %%stats_stddev%% %%stats_min%% %%stats_max%%
/BARCHART.
Previewing a custom dialog
You can preview the dialog that is currently open in the Custom Dialog Builder. The dialog appears and
functions as it would when run from the menus within IBM SPSS Statistics.
• Source variable lists are populated with dummy variables that can be moved to target lists.
• The Paste button pastes command syntax into the designated syntax window.
• The OK button closes the preview.
• If a help le is specied, the Help button is enabled and will open the specied le. If no help le is
specied, the help button is disabled when previewing, and hidden when the actual dialog is run.
To preview a custom dialog:
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1. From the menus in the Custom Dialog Builder choose:
File > Preview Dialog
Control types
The tools palette provides the controls that can be added to a custom dialog.
• Source List: A list of source variables from the active dataset. See the topic “Source List” on page 206
for more information.
• Target List: A target for variables transferred from the source list. See the topic “Target List” on page
207 for more information.
• Field Chooser: A list of all the elds from the active dataset. See the topic “Field Chooser” on page 208
for more information.
• Dataset Selector: A list of the datasets that are currently open. See the topic “Dataset Selector” on
page 209 for more information.
• Check Box: A single check box. See the topic “Check Box” on page 210 for more information.
• Combo Box: A combo box for creating drop-down lists. See the topic “Combo Box” on page 210 for
more information.
• List Box: A list box for creating single selection or multiple selection lists. See the topic “List Box” on
page 212 for more information.
• Text control: A text box that accepts arbitrary text as input. See the topic “Text control” on page 213
for more information.
• Number control: A text box that is restricted to numeric values as input. See the topic “Number
Control” on page 214 for more information.
• Date control: A spinner control for specifying date/time values, which include dates, times, and
datetimes. See the topic “Date control” on page 215 for more information.
• Secured Text: A text box that masks user entry with asterisks. See the topic “Secured Text” on page
216 for more information.
• Static Text control: A control for displaying static text. See the topic “Static Text Control” on page 217
for more information.
• Color Picker: A control for specifying a color and generating the associated RGB value. See the topic
“Color Picker” on page 217 for more information.
• Table control: A table with a xed number of columns and a variable number of rows that are added at
run time. See the topic “Table Control” on page 218 for more information.
• Item Group: A container for grouping a set of controls, such as a set of check boxes. See the topic
“Item Group” on page 220 for more information.
• Radio Group: A group of radio buttons. See the topic “Radio Group” on page 220 for more information.
• Check Box Group: A container for a set of controls that are enabled or disabled as a group, by a single
check box. See the topic “Check Box Group” on page 221 for more information.
• File Browser: A control for browsing the le system to open or save a le. See the topic “File Browser”
on page 222 for more information.
• Tab: A single tab. See the topic “Tab” on page 223 for more information.
• Sub-dialog Button: A button for launching a sub-dialog. See the topic “Sub-dialog button” on page 223
for more information.
Source List
The Source Variable List control displays the list of variables from the active dataset that are available to
the end user of the dialog. You can display all variables from the active dataset (the default) or you can
lter the list based on type and measurement level--for instance, numeric variables that have a
measurement level of scale. Use of a Source List control implies the use of one or more Target List
controls. The Source List control has the following properties:
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Identier. The unique identier for the control.
Title. An optional title that appears with the control. For multi-line titles or long titles, click the ellipsis (...)
button and enter your title in the Title Property dialog.
ToolTip. Optional ToolTip text that appears when the user hovers over the control. The specied text only
appears when hovering over the title area of the control. Hovering over one of the listed variables will
display the variable name and label.
Mnemonic Key. An optional character in the title to use as a keyboard shortcut to the control. The
character appears underlined in the title. The shortcut is activated by pressing Alt+[mnemonic key]. The
Mnemonic Key property is not supported on Mac.
Variable Transfers. Species whether variables transferred from the source list to a target list remain in
the source list (Copy Variables), or are removed from the source list (Move Variables).
Variable Filter. Allows you to lter the set of variables displayed in the control. You can lter on variable
type and measurement level, and you can specify that multiple response sets are included in the variable
list. Click the ellipsis (...) button to open the Filter dialog. You can also open the Filter dialog by double-
clicking the Source List control on the canvas. See the topic “Filtering Variable Lists” on page 209 for
more information.
Note: The Source List control cannot be added to a sub-dialog.
Target List
The Target List control provides a target for variables that are transferred from the source list. Use of the
Target List control assumes the presence of a Source List control. You can specify that only a single
variable can be transferred to the control or that multiple variables can be transferred to it, and you can
constrain which types of variables can be transferred to the control--for instance, only numeric variables
with a measurement level of nominal or ordinal. The Target List control has the following properties:
Identier. The unique identier for the control. This is the identier to use when referencing the control
in the syntax template.
Title. An optional title that appears with the control. For multi-line titles or long titles, click the ellipsis (...)
button and enter your title in the Title Property dialog.
ToolTip. Optional ToolTip text that appears when the user hovers over the control. The specied text only
appears when hovering over the title area of the control. Hovering over one of the listed variables will
display the variable name and label.
Target list type. Species whether multiple variables or only a single variable can be transferred to the
control.
Mnemonic Key. An optional character in the title to use as a keyboard shortcut to the control. The
character appears underlined in the title. The shortcut is activated by pressing Alt+[mnemonic key]. The
Mnemonic Key property is not supported on Mac.
Separator Type. Species the delimiter between the selected elds in the generated syntax. The allowed
separators are a blank, a comma, and a plus sign (+). You can also enter an arbitrary single character to
be used as the separator.
Minimum Fields. The minimum number of elds that must be specied for the control, if any.
Maximum Fields. The maximum number of elds that can be specied for the control, if any.
Required for execution. Species whether a value is required in this control in order for execution to
proceed. If True is specied, the OK and Paste buttons will be disabled until a value is specied for this
control. If False is specied, the absence of a value in this control has no effect on the state of the OK and
Paste buttons. The default is True.
Variable Filter. Allows you to constrain the types of variables that can be transferred to the control. You
can constrain by variable type and measurement level, and you can specify whether multiple response
sets can be transferred to the control. Click the ellipsis (...) button to open the Filter dialog. You can also
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open the Filter dialog by double-clicking the Target List control on the canvas. See the topic “Filtering
Variable Lists” on page 209 for more information.
Syntax. Species command syntax that is generated by this control at run time and can be inserted in the
syntax template.
• You can specify any valid command syntax. For multi-line syntax or long syntax, click the ellipsis (...)
button and enter your syntax in the Syntax Property dialog.
• The value %%ThisValue%% species the run time value of the control, which is the list of variables
transferred to the control. This is the default.
Enabling Rule. Species a rule that determines when the current control is enabled. Click the ellipsis (...)
button to open the dialog box and specify the rule. The Enabling Rule property is visible only when other
controls that can be used to specify an enabling rule exist on the canvas.
Note: The Target List control cannot be added to a sub-dialog.
Field Chooser
The Field Chooser control displays the list of elds that are available to the end user of the dialog. You can
lter the list based on type and measurement level--for instance, numeric elds that have a measurement
level of scale. You can also specify any other Field Chooser or Target List control as the source of elds for
the current Field Chooser. The Field Chooser control has the following properties:
Identier. The unique identier for the control.
Title. An optional title that appears with the control. For multi-line titles or long titles, click the ellipsis (...)
button and enter your title in the Title Property dialog.
Title Position. Species the position of the title relative to the control. Values are Top and Left where Top
is the default. This property only applies when the chooser type is set to select a single eld.
ToolTip. Optional ToolTip text that appears when the user hovers over the control. The specied text only
appears when hovering over the title area of the control. Hovering over one of the listed elds displays the
eld name and label.
Mnemonic Key. An optional character in the title to use as a keyboard shortcut to the control. The
character appears underlined in the title. The shortcut is activated by pressing Alt+[mnemonic key].
Chooser Type. Species whether the Field Chooser in the custom dialog can be used to select a single
eld or multiple elds from the eld list.
Separator Type. Species the delimiter between the selected elds in the generated syntax. The allowed
separators are a blank, a comma, and a plus sign (+). You can also enter an arbitrary single character to
be used as the separator.
Minimum Fields. The minimum number of elds that must be specied for the control, if any.
Maximum Fields. The maximum number of elds that can be specied for the control, if any.
Required for Execution. Species whether a value is required in this control in order for execution to
proceed. If True is specied, the OK and Paste buttons will be disabled until a value is specied for this
control. If False is specied, the absence of a value in this control has no effect on the state of the OK and
Paste buttons.
Variable Filter. Allows you to lter the set of elds that are displayed in the control. You can lter on eld
type and measurement level, and you can specify that multiple response sets are included in the eld list.
Click the ellipsis (...) button to open the Filter dialog. You can also open the Filter dialog by double-
clicking the Field Chooser control on the canvas. See the topic “Filtering Variable Lists” on page 209
for
more information.
Field Source. Species that another Field Chooser or Target List control is the source of elds for the
current Field Chooser. When the Field Source property is not set, the source of elds is the current data
source as determined by the Data Source property of the dialog. Click the ellipsis (...) button to open the
dialog box and specify the eld source.
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Syntax. Species the command syntax that is generated and run by this control at run-time and can be
inserted in the syntax template.
• You can specify any valid command syntax. For multi-line syntax or long syntax, click the ellipsis (...)
button and enter your syntax in the Syntax Property dialog.
• The value %%ThisValue%% species the run-time value of the control, which is the list of elds. This is
the default.
Enabling Rule. Species a rule that determines when the current control is enabled. Click the ellipsis (...)
button to open the dialog box and specify the rule. The Enabling Rule property is visible only when other
controls that can be used to specify an enabling rule exist on the canvas.
Note: The Field Chooser control is not available in compatibility mode.
Specifying the Field Source for a Field Chooser
The Field Source dialog box species the source of the elds that are displayed in the Field Chooser, and
overrides the setting of the Data Source property for the dialog. The source can be any other Field
Chooser or Target List control. You can choose to display the elds that are in the selected control or the
elds, from the current data source, that are not in the selected control. The data source is determined by
the Data Source property of the dialog.
Filtering Variable Lists
The Filter dialog box, associated with source list, target list, and eld chooser controls, allows you to lter
the types of variables from the active dataset that can appear in the lists. You can also specify whether
multiple response sets associated with the active dataset are included. Numeric variables include all
numeric formats except date and time formats.
Dataset Selector
The Dataset Selector control displays a list of the datasets that are currently open. You can use the
Dataset Selector control to capture the name of a selected dataset. You can also use it with the Data
Source property of the dialog to set the data source that is used by Source List and Field Chooser
controls.
Identier. The unique identier for the control. This is the identier to use when referencing the control
in the syntax template.
Title. An optional title that appears with the control. For multi-line titles or long titles, click the ellipsis (...)
button and enter your title in the Title Property dialog.
ToolTip. Optional ToolTip text that appears when the user hovers over the control.
Mnemonic Key. An optional character in the title to use as a keyboard shortcut to the control. The
character appears underlined in the title. The shortcut is activated by pressing Alt+[mnemonic key]. The
Mnemonic Key property is not supported on Mac.
Required for execution. Species whether a value is required in this control in order for execution to
proceed. If True is specied, the OK and Paste buttons will be disabled until a value is specied for this
control. If False is specied, the absence of a value in this control has no effect on the state of the OK and
Paste buttons. The default is False.
Syntax. Species the command syntax that is generated by this control at run time and can be inserted in
the syntax template.
• You can specify any valid command syntax. For multi-line syntax or long syntax, click the ellipsis (...)
button and enter your syntax in the Syntax Property dialog.
• The value %%ThisValue%% species the run time value of the control, which is the name of the
selected dataset. This is the default.
Enabling Rule. Species a rule that determines when the current control is enabled. Click the ellipsis (...)
button to open the dialog box and specify the rule. The Enabling Rule property is visible only when other
controls that can be used to specify an enabling rule exist on the canvas.
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Note: Dataset Selector control is not available in compatibility mode.
Check Box
The Check Box control is a simple check box that can generate different command syntax for the checked
versus the unchecked state. The Check Box control has the following properties:
Identier. The unique identier for the control. This is the identier to use when referencing the control
in the syntax template.
Title. An optional title that appears with the control. For multi-line titles or long titles, click the ellipsis (...)
button and enter your title in the Title Property dialog.
ToolTip. Optional ToolTip text that appears when the user hovers over the control.
Mnemonic Key. An optional character in the title to use as a keyboard shortcut to the control. The
character appears underlined in the title. The shortcut is activated by pressing Alt+[mnemonic key]. The
Mnemonic Key property is not supported on Mac.
Default Value. The default state of the check box--checked or unchecked.
Checked/Unchecked Syntax. Species the command syntax that is generated when the control is
checked and when it is unchecked. To include the command syntax in the syntax template, use the value
of the Identier property. The generated syntax, whether from the Checked Syntax or Unchecked Syntax
property, will be inserted at the specied position(s) of the identier. For example, if the identier is
checkbox1, then at run time, instances of %%checkbox1%% in the syntax template will be replaced by the
value of the Checked Syntax property when the box is checked and the Unchecked Syntax property when
the box is unchecked.
• You can specify any valid command syntax. For multi-line syntax or long syntax, click the ellipsis (...)
button and enter your syntax in the Syntax Property dialog.
Enabling Rule. Species a rule that determines when the current control is enabled. Click the ellipsis (...)
button to open the dialog box and specify the rule. The Enabling Rule property is visible only when other
controls that can be used to specify an enabling rule exist on the canvas.
Combo Box
The Combo Box control allows you to create a drop-down list that can generate command syntax specic
to the selected list item. It is limited to single selection. The Combo Box control has the following
properties:
Identier. The unique identier for the control. This is the identier to use when referencing the control
in the syntax template.
Title. An optional title that appears with the control. For multi-line titles or long titles, click the ellipsis (...)
button and enter your title in the Title Property dialog.
Title Position. Species the position of the title relative to the control. Values are Top and Left where Top
is the default.
ToolTip. Optional ToolTip text that appears when the user hovers over the control.
List Items. Click the ellipsis (...) button to open the List Item Properties dialog box, which allows you to
specify the list items of the control. You can also open the List Item Properties dialog by double-clicking
the Combo Box control on the canvas.
Mnemonic Key. An optional character in the title to use as a keyboard shortcut to the control. The
character appears underlined in the title. The shortcut is activated by pressing Alt+[mnemonic key].The
Mnemonic Key property is not supported on Mac.
Editable. Species whether the Combo Box control is editable. When the control is editable, a custom
value can be entered at run time.
Syntax. Species the command syntax that is generated by this control at run time and can be inserted in
the syntax template.
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• The value %%ThisValue%% species the run time value of the control and is the default. If the list items
are manually dened, the run time value is the value of the Syntax property for the selected list item. If
the list items are based on a target list control, the run time value is the value of the selected list item.
For multiple selection list box controls, the run time value is a blank-separated list of the selected
items. See the topic “Specifying list items for combo boxes and list boxes” on page 211 for more
information.
• You can specify any valid command syntax. For multi-line syntax or long syntax, click the ellipsis (...)
button and enter your syntax in the Syntax Property dialog.
Quote Handling. Species handling of quotation marks in the run time value of %%ThisValue%% when
the Syntax property contains %%ThisValue%% as part of a quoted string. In this context, a quoted string
is a string that is enclosed in single quotation marks or double quotation marks. Quote handling applies
only to quotation marks that are the same type as the quotation marks that enclose %%ThisValue%%.
The following types of quote handling are available.
Syntax
Quotation marks in the run time value of %%ThisValue%% that match the enclosing quotation
marks are doubled. For example, if the Syntax property is '%%ThisValue%%' and the run time
value of the combo box is Combo box's value, then the generated syntax is 'Combo box''s
value'.
Python
Quotation marks in the run time value of %%ThisValue%% that match the enclosing quotation
marks are escaped with the backslash character (\). For example, if the Syntax property is '%
%ThisValue%%' and the run time value of the combo box is Combo box's value, then the
generated syntax is 'Combo box\'s value'. Note that quote handling is not done when %
%ThisValue%% is enclosed in triple quotation marks.
R
Quotation marks in the run time value of %%ThisValue%% that match the enclosing quotation
marks are escaped with the backslash character (\). For example, if the Syntax property is '%
%ThisValue%%' and the run time value of the combo box is Combo box's value, then the
generated syntax is 'Combo box\'s value'.
None
Quotation marks in the run time value of %%ThisValue%% that match the enclosing quotation
marks are retained with no modication.
Enabling Rule. Species a rule that determines when the current control is enabled. Click the ellipsis (...)
button to open the dialog box and specify the rule. The Enabling Rule property is visible only when other
controls that can be used to specify an enabling rule exist on the canvas.
Specifying list items for combo boxes and list boxes
The List Item Properties dialog box allows you to specify the list items of a combo box or list box control.
Manually dened values. Allows you to explicitly specify each of the list items.
• Identier. A unique identier for the list item.
• Name. The name that appears in the list for this item. The name is a required eld.
• Default. For a combo box, species whether the list item is the default item displayed in the combo
box. For a list box, species whether the list item is selected by default.
• Syntax. Species the command syntax that is generated when the list item is selected.
• You can specify any valid command syntax. For multi-line syntax or long syntax, click the ellipsis (...)
button and enter your syntax in the Syntax Property dialog.
Note: You can add a new list item in the blank line at the bottom of the existing list. Entering any of the
properties other than the identier will generate a unique identier, which you can keep or modify. You
can delete a list item by clicking on the Identier cell for the item and pressing delete.
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Values based on the contents of a target list or eld chooser control. Species that the list items are
dynamically populated with values associated with the variables in a selected target list or eld chooser
control. Select an existing target list or eld chooser control as the source of the list items, or enter the
value of the Identier property for a target list or eld chooser control into the text area of the Target List
or Field Chooser combo box. The latter approach allows you to enter the Identier for a target list or eld
chooser control that you plan to add later.
• Variable Names. Populate the list items with the names of the variables in the specied target list or
eld chooser control.
• Value Labels. Populate the list items with the union of the value labels associated with the variables in
the specied target list control. You can choose whether the command syntax generated by the
associated combo box or list box control contains the selected value label or its associated value. The
Value Labels option is not available for eld choosers.
• Custom Attribute. Populate the list items with the union of the attribute values associated with
variables in the target list control that contain the specied custom attribute. The Custom Attribute
option is not available for eld choosers.
• Syntax. Displays the Syntax property of the associated combo box or list box control, allowing you to
make changes to the property. See the topic “Combo Box” on page 210 for more information.
List Box
The List Box control allows you to display a list of items that support single or multiple selection and
generate command syntax specic to the selected item(s). The List Box control has the following
properties:
Identier. The unique identier for the control. This is the identier to use when referencing the control
in the syntax template.
Title. An optional title that appears with the control. For multi-line titles or long titles, click the ellipsis (...)
button and enter your title in the Title Property dialog.
ToolTip. Optional ToolTip text that appears when the user hovers over the control.
List Items. Click the ellipsis (...) button to open the List Item Properties dialog box, which allows you to
specify the list items of the control. You can also open the List Item Properties dialog by double-clicking
the List Box control on the canvas.
Mnemonic Key. An optional character in the title to use as a keyboard shortcut to the control. The
character appears underlined in the title. The shortcut is activated by pressing Alt+[mnemonic key].The
Mnemonic Key property is not supported on Mac.
List Box Type. Species whether the list box supports single selection only or multiple selection. You can
also specify that items are displayed as a list of check boxes.
Separator Type. Species the delimiter between the selected list items in the generated syntax. The
allowed separators are a blank, a comma, and a plus sign (+). You can also enter an arbitrary single
character to be used as the separator.
Minimum Selected. The minimum number of items that must be selected in the control, if any.
Maximum Selected. The maximum number of items that can be selected in the control, if any.
Syntax. Species the command syntax that is generated by this control at run time and can be inserted in
the syntax template.
• The value %%ThisValue%% species the run time value of the control and is the default. If the list items
are manually dened, the run time value is the value of the Syntax property for the selected list item. If
the list items are based on a target list control, the run time value is the value of the selected list item.
For multiple selection list box controls, the run time value is a list of the selected items, delimited by the
specied Separator Type (default is blank separated). See the topic “Specifying list items for combo
boxes and list boxes” on page 211 for more information.
• You can specify any valid command syntax. For multi-line syntax or long syntax, click the ellipsis (...)
button and enter your syntax in the Syntax Property dialog.
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Quote Handling. Species handling of quotation marks in the run time value of %%ThisValue%% when
the Syntax property contains %%ThisValue%% as part of a quoted string. In this context, a quoted string
is a string that is enclosed in single quotation marks or double quotation marks. Quote handling applies
only to quotation marks that are the same type as the quotation marks that enclose %%ThisValue%%.
The following types of quote handling are available.
Syntax
Quotation marks in the run time value of %%ThisValue%% that match the enclosing quotation
marks are doubled. For example, if the Syntax property is '%%ThisValue%%' and the selected list
item is List item's value, then the generated syntax is 'List item''s value'.
Python
Quotation marks in the run time value of %%ThisValue%% that match the enclosing quotation
marks are escaped with the backslash character (\). For example, if the Syntax property is '%
%ThisValue%%' and the selected list item is List item's value, then the generated syntax is
'List item\'s value'. Note that quote handling is not done when %%ThisValue%% is
enclosed in triple quotation marks.
R
Quotation marks in the run time value of %%ThisValue%% that match the enclosing quotation
marks are escaped with the backslash character (\). For example, if the Syntax property is '%
%ThisValue%%' and the selected list item is List item's value, then the generated syntax is
'List item\'s value'.
None
Quotation marks in the run time value of %%ThisValue%% that match the enclosing quotation
marks are retained with no modication.
Enabling Rule. Species a rule that determines when the current control is enabled. Click the ellipsis (...)
button to open the dialog box and specify the rule. The Enabling Rule property is visible only when other
controls that can be used to specify an enabling rule exist on the canvas.
Text control
The Text control is a simple text box that can accept arbitrary input, and has the following properties:
Identier. The unique identier for the control. This is the identier to use when referencing the control
in the syntax template.
Title. An optional title that appears with the control. For multi-line titles or long titles, click the ellipsis (...)
button and enter your title in the Title Property dialog.
Title Position. Species the position of the title relative to the control. Values are Top and Left where Top
is the default.
ToolTip. Optional ToolTip text that appears when the user hovers over the control.
Mnemonic Key. An optional character in the title to use as a keyboard shortcut to the control. The
character appears underlined in the title. The shortcut is activated by pressing Alt+[mnemonic key]. The
Mnemonic Key property is not supported on Mac.
Text Content. Species the allowed contents. The value Any species that the contents are arbitrary. The
value Variable Name species that the text box must contain a string that adheres to rules for IBM SPSS
Statistics variable names. See the topic “Variable names” on page 46
for more information. The value
New dataset name species that the text box must contain a valid IBM SPSS Statistics dataset name and
cannot be the name of a currently open dataset.
Default Value. The default contents of the text box.
Width. Species the width of the text area of the control in characters. The allowed values are positive
integers. An empty value means that the width is automatically determined.
Required for execution. Species whether a value is required in this control in order for execution to
proceed. If True is specied, the OK and Paste buttons will be disabled until a value is specied for this
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control. If False is specied, the absence of a value in this control has no effect on the state of the OK and
Paste buttons. The default is False.
Syntax. Species the command syntax that is generated by this control at run time and can be inserted in
the syntax template.
• You can specify any valid command syntax. For multi-line syntax or long syntax, click the ellipsis (...)
button and enter your syntax in the Syntax Property dialog.
• The value %%ThisValue%% species the run time value of the control, which is the content of the text
box. This is the default.
• If the Syntax property includes %%ThisValue%% and the run time value of the text box is empty, then
the text box control does not generate any command syntax.
Quote Handling. Species handling of quotation marks in the run time value of %%ThisValue%% when
the Syntax property contains %%ThisValue%% as part of a quoted string. In this context, a quoted string
is a string that is enclosed in single quotation marks or double quotation marks. Quote handling applies
only to quotation marks that are the same type as the quotation marks that enclose %%ThisValue%%.
The following types of quote handling are available.
Syntax
Quotation marks in the run time value of %%ThisValue%% that match the enclosing quotation
marks are doubled. For example, if the Syntax property is'%%ThisValue%%' and the run time
value of the text control is Text box's value, then the generated syntax is 'Text box''s
value'.
Python
Quotation marks in the run time value of %%ThisValue%% that match the enclosing quotation
marks are escaped with the backslash character (\). For example, if the Syntax property is '%
%ThisValue%%' and the run time value of the text control is Text box's value, then the
generated syntax is 'Text box\'s value'. Quote handling is not done when %%ThisValue%%
is enclosed in triple quotation marks.
R
Quotation marks in the run time value of %%ThisValue%% that match the enclosing quotation
marks are escaped with the backslash character (\). For example, if the Syntax property is '%
%ThisValue%%' and the run time value of the text control is Text box's value, then the
generated syntax is 'Text box\'s value'.
None
Quotation marks in the run time value of %%ThisValue%% that match the enclosing quotation
marks are retained with no modication.
Enabling Rule. Species a rule that determines when the current control is enabled. Click the ellipsis (...)
button to open the dialog box and specify the rule. The Enabling Rule property is visible only when other
controls that can be used to specify an enabling rule exist on the canvas.
Number Control
The Number control is a text box for entering a numeric value, and has the following properties:
Identier. The unique identier for the control. This is the identier to use when referencing the control
in the syntax template.
Title. An optional title that appears with the control. For multi-line titles or long titles, click the ellipsis (...)
button and enter your title in the Title Property dialog.
Title Position. Species the position of the title relative to the control. Values are Top and Left where Top
is the default.
ToolTip. Optional ToolTip text that appears when the user hovers over the control.
Mnemonic Key. An optional character in the title to use as a keyboard shortcut to the control. The
character appears underlined in the title. The shortcut is activated by pressing Alt+[mnemonic key]. The
Mnemonic Key property is not supported on Mac.
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Numeric Type. Species any limitations on what can be entered. A value of Real species that there are
no restrictions on the entered value, other than it be numeric. A value of Integer species that the value
must be an integer.
Spin Input. Species whether the control is displayed as a spinner. The default is False.
Increment. The increment when the control is displayed as a spinner.
Default Value. The default value, if any.
Minimum Value. The minimum allowed value, if any.
Maximum Value. The maximum allowed value, if any.
Width. Species the width of the text area of the control in characters. The allowed values are positive
integers. An empty value means that the width is automatically determined.
Required for execution. Species whether a value is required in this control in order for execution to
proceed. If True is specied, the OK and Paste buttons will be disabled until a value is specied for this
control. If False is specied, the absence of a value in this control has no effect on the state of the OK and
Paste buttons. The default is False.
Syntax. Species the command syntax that is generated by this control at run time and can be inserted in
the syntax template.
• You can specify any valid command syntax. For multi-line syntax or long syntax, click the ellipsis (...)
button and enter your syntax in the Syntax Property dialog.
• The value %%ThisValue%% species the run time value of the control, which is the numeric value. This
is the default.
• If the Syntax property includes %%ThisValue%% and the run time value of the number control is empty,
then the number control does not generate any command syntax.
Enabling Rule. Species a rule that determines when the current control is enabled. Click the ellipsis (...)
button to open the dialog box and specify the rule. The Enabling Rule property is visible only when other
controls that can be used to specify an enabling rule exist on the canvas.
Date control
The Date control is a spinner control for specifying date/time values, which include dates, times, and
datetimes. The Date control has the following properties:
Identier. The unique identier for the control. This is the identier to use when referencing the control
in the syntax template.
Title. An optional title that appears with the control. For multi-line titles or long titles, click the ellipsis (...)
button and enter your title in the Title Property dialog.
Title Position. Species the position of the title relative to the control. Values are Top and Left where Top
is the default.
ToolTip. Optional ToolTip text that appears when the user hovers over the control.
Mnemonic Key. An optional character in the title to use as a keyboard shortcut to the control. The
character appears underlined in the title. The shortcut is activated by pressing Alt+[mnemonic key]. The
Mnemonic Key property is not supported on Mac.
Type. Species whether the control is for dates, times, or datetime values.
Date
The control species a calendar date of the form yyyy-mm-dd. The default run time value is
specied by the Default Value property.
Time
The control species the time of day in the form hh:mm:ss. The default run time value is the
current time of day.
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Datetime
The control species a date and time of the form yyyy-mm-dd hh:mm:ss. The default run time
value is the current date and time of day.
Default Value. The default run time value of the control when the type is Date. You can specify to display
the current date or a particular date.
Syntax. Species the command syntax that is generated by this control at run time and can be inserted in
the syntax template.
• You can specify any valid command syntax. For multi-line syntax or long syntax, click the ellipsis (...)
button and enter your syntax in the Syntax Property dialog.
• The value %%ThisValue%% species the run time value of the control. This is the default.
Enabling Rule. Species a rule that determines when the current control is enabled. Click the ellipsis (...)
button to open the dialog box and specify the rule. The Enabling Rule property is visible only when other
controls that can be used to specify an enabling rule exist on the canvas.
Note: The Date control is not available in compatibility mode.
Secured Text
The Secured Text control is a text box that masks user entry with asterisks.
Identier. The unique identier for the control. This is the identier to use when referencing the control
in the syntax template.
Title. An optional title that appears with the control. For multi-line titles or long titles, click the ellipsis (...)
button and enter your title in the Title Property dialog.
Title Position. Species the position of the title relative to the control. Values are Top and Left where Top
is the default.
ToolTip. Optional ToolTip text that appears when the user hovers over the control.
Mnemonic Key. An optional character in the title to use as a keyboard shortcut to the control. The
character appears underlined in the title. The shortcut is activated by pressing Alt+[mnemonic key]. The
Mnemonic Key property is not supported on Mac.
Encrypt passed value. Species whether the value in the generated command syntax is encrypted. True
species that the value is encrypted. The default is False, which species that the value is not encrypted.
Encrypted values can be decrypted only by IBM SPSS Statistics commands that can process encrypted
passwords, such as the GET and SAVE commands.
Width. Species the width of the text area of the control in characters. The allowed values are positive
integers. An empty value means that the width is automatically determined.
Required for execution. Species whether a value is required in this control in order for execution to
proceed. If True is specied, the OK and Paste buttons will be disabled until a value is specied for this
control. If False is specied, the absence of a value in this control has no effect on the state of the OK and
Paste buttons. The default is False.
Syntax. Species the command syntax that is generated by this control at run time and can be inserted in
the syntax template.
• You can specify any valid command syntax. For multi-line syntax or long syntax, click the ellipsis (...)
button and enter your syntax in the Syntax Property dialog.
• The value %%ThisValue%% species the run time value of the control, which is the content of the text
box. This is the default.
• If the Syntax property includes %%ThisValue%% and the run time value of the secured text control is
empty, then the secured text control does not generate any command syntax.
Quote Handling. Species handling of quotation marks in the run time value of %%ThisValue%% when
the Syntax property contains %%ThisValue%% as part of a quoted string. In this context, a quoted string
is a string that is enclosed in single quotation marks or double quotation marks. Quote handling applies
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only to quotation marks that are the same type as the quotation marks that enclose %%ThisValue%% and
only when Encrypt passed value=False. The following types of quote handling are available.
Syntax
Quotation marks in the run time value of %%ThisValue%% that match the enclosing quotation
marks are doubled. For example, if the Syntax property is '%%ThisValue%%' and the run time
value of the control is Secured Text's value, then the generated syntax is 'Secured
Text''s value'.
Python
Quotation marks in the run time value of %%ThisValue%% that match the enclosing quotation
marks are escaped with the backslash character (\). For example, if the Syntax property is '%
%ThisValue%%' and the run time value of the control is Secured Text's value, then the
generated syntax is 'Secured Text\'s value'. Quote handling is not done when %
%ThisValue%% is enclosed in triple quotation marks.
R
Quotation marks in the run time value of %%ThisValue%% that match the enclosing quotation
marks are escaped with the backslash character (\). For example, if the Syntax property is '%
%ThisValue%%' and the run time value of the control is Secured Text's value, then the
generated syntax is 'Secured Text\'s value'.
None
Quotation marks in the run time value of %%ThisValue%% that match the enclosing quotation
marks are retained with no modication.
Enabling Rule. Species a rule that determines when the current control is enabled. Click the ellipsis (...)
button to open the dialog box and specify the rule. The Enabling Rule property is visible only when other
controls that can be used to specify an enabling rule exist on the canvas.
Note: The Secured Text control is not available in compatibility mode.
Static Text Control
The Static Text control allows you to add a block of text to your dialog, and has the following properties:
Identier. The unique identier for the control.
Title. The content of the text block. For multiple lines or long lines of text, click the ellipsis (...) button and
enter your text in the Title Property dialog.
Enabling Rule. Species a rule that determines when the current control is enabled. Click the ellipsis (...)
button to open the dialog box and specify the rule. The Enabling Rule property is visible only when other
controls that can be used to specify an enabling rule exist on the canvas.
Color Picker
The Color Picker control is a user interface for specifying a color and generating the associated RGB value.
The Color Picker control has the following properties:
Identier. The unique identier for the control. This is the identier to use when referencing the control
in the syntax template.
Title. An optional title that appears with the control. For multi-line titles or long titles, click the ellipsis (...)
button and enter your title in the Title Property dialog.
Title Position. Species the position of the title relative to the control. Values are Top and Left where Top
is the default.
ToolTip. Optional ToolTip text that appears when the user hovers over the control.
Mnemonic Key. An optional character in the title to use as a keyboard shortcut to the control. The
character appears underlined in the title. The shortcut is activated by pressing Alt+[mnemonic key]. The
Mnemonic Key property is not supported on Mac.
Syntax. Species the command syntax that is generated by this control at run time and can be inserted in
the syntax template.
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• You can specify any valid command syntax. For multi-line syntax or long syntax, click the ellipsis (...)
button and enter your syntax in the Syntax Property dialog.
• The value %%ThisValue%% species the run time value of the control, which is the RGB value of the
selected color. The RGB value is represented as a blank separated list of integers in the following order:
R value, G value, B value.
Enabling Rule. Species a rule that determines when the current control is enabled. Click the ellipsis (...)
button to open the dialog box and specify the rule. The Enabling Rule property is visible only when other
controls that can be used to specify an enabling rule exist on the canvas.
Note: The Color Picker control is not available in compatibility mode.
Table Control
The Table control creates a table with a xed number of columns and a variable number of rows that are
added at run time. The Table control has the following properties:
Identier. The unique identier for the control. This is the identier to use when referencing the control
in the syntax template.
Title. An optional title that appears with the control. For multi-line titles or long titles, click the ellipsis (...)
button and enter your title in the Title Property dialog.
ToolTip. Optional ToolTip text that appears when the user hovers over the control.
Mnemonic Key. An optional character in the title to use as a keyboard shortcut to the control. The
character appears underlined in the title. The shortcut is activated by pressing Alt+[mnemonic key].The
Mnemonic Key property is not supported on Mac.
Reorder Buttons. Species whether move up and move down buttons are added to the table. These
buttons are used at run time to reorder the rows of the table.
Table Columns. Click the ellipsis (...) button to open the Table Columns dialog box, where you specify the
columns of the table.
Minimum Rows. The minimum number of rows that must be in the table.
Maximum Rows. The maximum number of rows that can be in the table.
Required for Execution. Species whether a value is required in this control in order for execution to
proceed. If True is specied, the OK and Paste buttons will be disabled until a value is specied for this
control. If False is specied, the absence of a value in this control has no effect on the state of the OK and
Paste buttons.
Syntax. Species the command syntax that is generated by this control at run time and can be inserted in
the syntax template.
• The value %%ThisValue%% species the run time value of the control and is the default. The run time
value is a blank-separated list of the syntax that is generated by each column in the table, starting with
the leftmost column. If the Syntax property includes %%ThisValue%% and none of the columns
generate syntax, then the table as a whole does not generate any syntax.
• You can specify any valid command syntax. For multi-line syntax or long syntax, click the ellipsis (...)
button and enter your syntax in the Syntax Property dialog.
Enabling Rule. Species a rule that determines when the current control is enabled. Click the ellipsis (...)
button to open the dialog box and specify the rule. The Enabling Rule property is visible only when other
controls that can be used to specify an enabling rule exist on the canvas.
Note: The Table control is not available in compatibility mode.
Specifying columns for table controls
The Table Columns dialog box species the properties of the columns of the Table control.
Identier. A unique identier for the column.
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Column Name. The name of the column as it appears in the table.
Contents. Species the type of data for the column. The value Real species that there are no restrictions
on the entered value, other than it is numeric. The value Integer species that the value must be an
integer. The value Any species that there are no restrictions on the entered value. The value Variable
Name species that the value must meet the requirements for a valid variable name in IBM SPSS
Statistics.
Default Value. The default value for this column, if any, when new rows are added to the table at run
time.
Separator Type. Species the delimiter between the values of the column, in the generated syntax. The
allowed separators are a blank, a comma, and a plus sign (+). You can also enter an arbitrary single
character to be used as the separator.
Quoted. Species whether each value in the column is enclosed in double quotation marks in the
generated syntax.
Quote Handling. Species handling of quotation marks in cell entries for the column when the Quoted
property is true. Quote handling applies only to double quotation marks in cell values. The following types
of quote handling are available.
Syntax
Double quotation marks in cell values are doubled. For example, if the cell value is This
"quoted" value then the generated syntax is "This ""quoted"" value".
Python
Double quotation marks in cell values are escaped with the backslash character (\). For example,
if the cell value is This "quoted" value then the generated syntax is "This \"quoted\"
value".
R
Double quotation marks in cell values are escaped with the backslash character (\). For example,
if the cell value is This "quoted" value then the generated syntax is "This \"quoted\"
value".
None
Double quotation marks in cell values are retained with no modication.
Width(chars). Species the width of the column in characters. The allowed values are positive integers.
Syntax. Species the command syntax that is generated by this column at run time. The generated
syntax for the table as a whole is a blank-separated list of the syntax that is generated by each column in
the table, starting with the leftmost column.
• You can specify any valid command syntax. For multi-line syntax or long syntax, click the ellipsis (...)
button and enter your syntax in the Syntax Property dialog.
• The value %%ThisValue%% species the run time value of the column, which is a list of the values in the
column, delimited by the specied separator.
• If the Syntax property for the column includes %%ThisValue%% and the run time value of the column is
empty, then the column does not generate any syntax.
Note: You can add a row for a new Table column in the blank line at the bottom of the existing list in the
Table Columns dialog. Entering any of the properties other than the identier generates a unique
identier, which you can keep or modify. You can delete a Table column by clicking the identier cell for
the Table column and pressing delete.
Link to Control
You can link a Table control to a Field Chooser control. When a Table control is linked to a Field Chooser,
there is a row in the table for each eld in the Field Chooser. Rows are added to the table by adding elds
to the Field Chooser. Rows are deleted from the table by removing elds from the Field Chooser. A linked
Table control can be used, for example, to specify properties of elds that are selected in a Field Chooser.
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To enable linking, the table must have a column with Variable Name for the Contents property and there
must be at least one Field Chooser control on the canvas.
To link a Table control to a Field Chooser, specify the Field Chooser from the list of Available controls in
the Link to Control group on the Table Columns dialog box. Then, select the table column, referred to as
the Linked column, that denes the link. When the table is rendered, the linked column displays the
current elds in the Field Chooser. You can link only to multi-eld Field Choosers.
Item Group
The Item Group control is a container for other controls, allowing you to group and control the syntax
generated from multiple controls. For example, you have a set of check boxes that specify optional
settings for a subcommand, but only want to generate the syntax for the subcommand if at least one box
is checked. This is accomplished by using an Item Group control as a container for the check box controls.
The following types of controls can be contained in an Item Group: eld chooser, dataset selector, check
box, combo box, list box, text control, number control, date control, secured text, static text, color picker,
table control, radio group, and le browser. The Item Group control has the following properties:
Identier. The unique identier for the control. This is the identier to use when referencing the control
in the syntax template.
Title. An optional title for the group. For multi-line titles or long titles, click the ellipsis (...) button and
enter your title in the Title Property dialog.
Syntax. Species the command syntax that is generated by this control at run time and can be inserted in
the syntax template.
• You can specify any valid command syntax. For multi-line syntax or long syntax, click the ellipsis (...)
button and enter your syntax in the Syntax Property dialog.
• You can include identiers for any controls contained in the item group. At run time the identiers are
replaced with the syntax generated by the controls.
• The value %%ThisValue%% generates a blank-separated list of the syntax generated by each control in
the item group, in the order in which they appear in the group (top to bottom). This is the default. If the
Syntax property includes %%ThisValue%% and no syntax is generated by any of the controls in the item
group, then the item group as a whole does not generate any command syntax.
Enabling Rule. Species a rule that determines when the current control is enabled. Click the ellipsis (...)
button to open the dialog box and specify the rule. The Enabling Rule property is visible only when other
controls that can be used to specify an enabling rule exist on the canvas.
Radio Group
The Radio Group control is a container for a set of radio buttons, each of which can contain a set of nested
controls. The Radio Group control has the following properties:
Identier. The unique identier for the control. This is the identier to use when referencing the control
in the syntax template.
Title. An optional title for the group. For multi-line titles or long titles, click the ellipsis (...) button and
enter your title in the Title Property dialog.
ToolTip. Optional ToolTip text that appears when the user hovers over the control.
Radio Buttons. Click the ellipsis (...) button to open the Radio Group Properties dialog box, which allows
you to specify the properties of the radio buttons as well as to add or remove buttons from the group. The
ability to nest controls under a given radio button is a property of the radio button and is set in the Radio
Group Properties dialog box. Note that you can also open the Radio Group Properties dialog by double-
clicking the Radio Group control on the canvas.
Syntax. Species the command syntax that is generated by this control at run time and can be inserted in
the syntax template.
• You can specify any valid command syntax. For multi-line syntax or long syntax, click the ellipsis (...)
button and enter your syntax in the Syntax Property dialog.
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• The value %%ThisValue%% species the run time value of the radio button group, which is the value of
the Syntax property for the selected radio button. This is the default. If the Syntax property includes %
%ThisValue%% and no syntax is generated by the selected radio button, then the radio button group
does not generate any command syntax.
Enabling Rule. Species a rule that determines when the current control is enabled. Click the ellipsis (...)
button to open the dialog box and specify the rule. The Enabling Rule property is visible only when other
controls that can be used to specify an enabling rule exist on the canvas.
Dening radio buttons
The Radio Button Group Properties dialog box allows you to specify a group of radio buttons.
Identier. A unique identier for the radio button.
Column Name. The name that appears next to the radio button. The name is a required eld.
ToolTip. Optional ToolTip text that appears when the user hovers over the control.
Mnemonic Key. An optional character in the name to use as a mnemonic. The specied character must
exist in the name.
Nested Group. Species whether other controls can be nested under this radio button. The default is
false. When the nested group property is set to true, a rectangular drop zone is displayed, nested and
indented, under the associated radio button. The following controls can be nested under a radio button:
eld chooser, dataset selector, check box, combo box, list box, text control, number control, date control,
secured text, static text, color picker, table control, and le browser.
Default. Species whether the radio button is the default selection.
Enabling Rule. Species a rule that determines when the current control is enabled. Click the ellipsis (...)
button to open the dialog box and specify the rule. The Enabling Rule property is visible only when other
controls that can be used to specify an enabling rule exist on the canvas.
Syntax. Species the command syntax that is generated when the radio button is selected.
• You can specify any valid command syntax. For multi-line syntax or long syntax, click the ellipsis (...)
button and enter your syntax in the Syntax Property dialog.
• For radio buttons containing nested controls, the value %%ThisValue%% generates a blank-separated
list of the syntax generated by each nested control, in the order in which they appear under the radio
button (top to bottom).
You can add a new radio button in the blank line at the bottom of the existing list. Entering any of the
properties other than the identier will generate a unique identier, which you can keep or modify. You
can delete a radio button by clicking on the Identier cell for the button and pressing delete.
Check Box Group
The Check Box Group control is a container for a set of controls that are enabled or disabled as a group,
by a single check box. The following types of controls can be contained in a Check Box Group: eld
chooser, dataset selector, check box, combo box, list box, text control, number control, date control,
secured text, static text, color picker, table control, radio group, and le browser. The Check Box Group
control has the following properties:
Identier. The unique identier for the control. This is the identier to use when referencing the control
in the syntax template.
Title. An optional title for the group. For multi-line titles or long titles, click the ellipsis (...) button and
enter your title in the Title Property dialog.
Checkbox Title. An optional label that is displayed with the controlling check box. Supports \n to specify
line breaks.
ToolTip. Optional ToolTip text that appears when the user hovers over the control.
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Mnemonic Key. An optional character in the title to use as a keyboard shortcut to the control. The
character appears underlined in the title. The shortcut is activated by pressing Alt+[mnemonic key]. The
Mnemonic Key property is not supported on Mac.
Default Value. The default state of the controlling check box--checked or unchecked.
Checked/Unchecked Syntax. Species the command syntax that is generated when the control is
checked and when it is unchecked. To include the command syntax in the syntax template, use the value
of the Identier property. The generated syntax, whether from the Checked Syntax or Unchecked Syntax
property, will be inserted at the specied position(s) of the identier. For example, if the identier is
checkboxgroup1, then at run time, instances of %%checkboxgroup1%% in the syntax template will be
replaced by the value of the Checked Syntax property when the box is checked and the Unchecked Syntax
property when the box is unchecked.
• You can specify any valid command syntax. For multi-line syntax or long syntax, click the ellipsis (...)
button and enter your syntax in the Syntax Property dialog.
• You can include identiers for any controls contained in the check box group. At run time the identiers
are replaced with the syntax generated by the controls.
• The value %%ThisValue%% can be used in either the Checked Syntax or Unchecked Syntax property. It
generates a blank-separated list of the syntax generated by each control in the check box group, in the
order in which they appear in the group (top to bottom).
• By default, the Checked Syntax property has a value of %%ThisValue%% and the Unchecked Syntax
property is blank.
Enabling Rule. Species a rule that determines when the current control is enabled. Click the ellipsis (...)
button to open the dialog box and specify the rule. The Enabling Rule property is visible only when other
controls that can be used to specify an enabling rule exist on the canvas.
File Browser
The File Browser control consists of a text box for a le path and a browse button that opens a standard
IBM SPSS Statistics dialog to open or save a le. The File Browser control has the following properties:
Identier. The unique identier for the control. This is the identier to use when referencing the control
in the syntax template.
Title. An optional title that appears with the control. For multi-line titles or long titles, click the ellipsis (...)
button and enter your title in the Title Property dialog.
Title Position. Species the position of the title relative to the control. Values are Top and Left where Top
is the default.
ToolTip. Optional ToolTip text that appears when the user hovers over the control.
Mnemonic Key. An optional character in the title to use as a keyboard shortcut to the control. The
character appears underlined in the title. The shortcut is activated by pressing Alt+[mnemonic key]. The
Mnemonic Key property is not supported on Mac.
File System Operation. Species whether the dialog launched by the browse button is appropriate for
opening les or for saving les. A value of Open indicates that the browse dialog validates the existence of
the specied le. A value of Save indicates that the browse dialog does not validate the existence of the
specied le.
Browser Type. Species whether the browse dialog is used to select a le (Locate File) or to select a
folder (Locate Folder).
File Filter. Click the ellipsis (...) button to open the File Filter dialog box, which allows you to specify the
available le types for the open or save dialog. By default, all le types are allowed. Note that you can also
open the File Filter dialog by double-clicking the File Browser control on the canvas.
File System Type. In distributed analysis mode, this species whether the open or save dialog browses
the le system on which IBM SPSS Statistics Server is running or the le system of your local computer.
Select Server to browse the le system of the server or Client to browse the le system of your local
computer. The property has no effect in local analysis mode.
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Required for execution. Species whether a value is required in this control in order for execution to
proceed. If True is specied, the OK and Paste buttons will be disabled until a value is specied for this
control. If False is specied, the absence of a value in this control has no effect on the state of the OK and
Paste buttons. The default is False.
Default. The default value of the control.
Syntax. Species the command syntax that is generated by this control at run time and can be inserted in
the syntax template.
• You can specify any valid command syntax. For multi-line syntax or long syntax, click the ellipsis (...)
button and enter your syntax in the Syntax Property dialog.
• The value %%ThisValue%% species the run time value of the text box, which is the le path, specied
manually or populated by the browse dialog. This is the default.
• If the Syntax property includes %%ThisValue%% and the run time value of the text box is empty, then
the le browser control does not generate any command syntax.
Enabling Rule. Species a rule that determines when the current control is enabled. Click the ellipsis (...)
button to open the dialog box and specify the rule. The Enabling Rule property is visible only when other
controls that can be used to specify an enabling rule exist on the canvas.
File type lter
The File Filter dialog box allows you to specify the le types displayed in the Files of type and Save as type
drop-down lists for open and save dialogs accessed from a File System Browser control. By default, all le
types are allowed.
To specify le types not explicitly listed in the dialog box:
1. Select Other.
2. Enter a name for the le type.
3. Enter a le type using the form *.suffix--for example, *.xls. You can specify multiple le types,
each separated by a semicolon.
Tab
The Tab control adds a tab to the dialog. Any of the other controls can be added to the new tab. The Tab
control has the following properties:
Identier. The unique identier for the control.
Title. The title of the tab.
Position. Species the position of the tab on the dialog, relative to the other tabs on the dialog.
Enabling Rule. Species a rule that determines when the current control is enabled. Click the ellipsis (...)
button to open the dialog box and specify the rule. The Enabling Rule property is visible only when other
controls that can be used to specify an enabling rule exist on the canvas.
Note: The Tab control is not available in compatibility mode.
Sub-dialog button
The Sub-dialog Button control species a button for launching a sub-dialog and provides access to the
Dialog Builder for the sub-dialog. The Sub-dialog Button has the following properties:
Identier. The unique identier for the control.
Title. The text that is displayed in the button.
ToolTip. Optional ToolTip text that appears when the user hovers over the control.
Sub-dialog. Click the ellipsis (...) button to open the Custom Dialog Builder for the sub-dialog. You can
also open the builder by double-clicking on the Sub-dialog button.
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Mnemonic Key. An optional character in the title to use as a keyboard shortcut to the control. The
character appears underlined in the title. The shortcut is activated by pressing Alt+[mnemonic key]. The
Mnemonic Key property is not supported on Mac.
Enabling Rule. Species a rule that determines when the current control is enabled. Click the ellipsis (...)
button to open the dialog box and specify the rule. The Enabling Rule property is visible only when other
controls that can be used to specify an enabling rule exist on the canvas.
Note: The Sub-dialog Button control cannot be added to a sub-dialog.
Dialog properties for a sub-dialog
To view and set properties for a sub-dialog:
1. Open the sub-dialog by double-clicking on the button for the sub-dialog in the main dialog, or single-
click the sub-dialog button and click the ellipsis (...) button for the Sub-dialog property.
2. In the sub-dialog, click on the canvas in an area outside of any controls. With no controls on the
canvas, the properties for a sub-dialog are always visible.
Sub-dialog Name. The unique identier for the sub-dialog. The Sub-dialog Name property is required.
Note: If you specify the Sub-dialog Name as an identier in the Syntax Template--as in %%My Sub-
dialog Name%%--it will be replaced at run-time with a blank-separated list of the syntax generated by
each control in the sub-dialog, in the order in which they appear (top to bottom and left to right).
Title. Species the text to be displayed in the title bar of the sub-dialog box. The Title property is optional
but recommended.
Help File. Species the path to an optional help le for the sub-dialog. This is the le that will be
launched when the user clicks the Help button on the sub-dialog, and may be the same help le specied
for the main dialog. Help les must be in HTML format. See the description of the Help File property for
Dialog Properties
for more information.
Specifying an Enabling Rule for a Control
You can specify a rule that determines when a control is enabled. For example, you can specify that a
radio group is enabled when a target list is populated. The available options for specifying the enabling
rule depend on the type of control that denes the rule.
Target List or Field Chooser
You can specify that the current control is enabled when a Target List or Field Chooser is populated
with at least one eld (Non-empty). You can alternately specify that the current control is enabled
when a Target List or Field Chooser is not populated (Empty).
Check Box or Check Box Group
You can specify that the current control is enabled when a Check Box or Check Box Group is checked.
You can alternately specify that the current control is enabled when a Check Box or Check Box Group
is not checked.
Combo Box or Single-Select List Box
You can specify that the current control is enabled when a particular value is selected in a Combo Box
or Single-Select List Box. You can alternately specify that the current control is enabled when a
particular value is not selected in a Combo Box or Single-Select List Box.
Multi-Select List Box
You can specify that the current control is enabled when a particular value is among the selected
values in a Multi-Select List Box. You can alternately specify that the current control is enabled when
a particular value is not among the selected values in a Multi-Select List Box.
Radio Group
You can specify that the current control is enabled when a particular radio button is selected. You can
alternately specify that the current control is enabled when a particular radio button is not selected.
Controls for which an enabling rule can be specied have an associated Enabling Rule property.
Note:
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• Enabling rules apply whether the control that denes the rule is enabled or not. For example, consider a
rule that species that a radio group is enabled when a target list is populated. The radio group is then
enabled whenever the target list is populated, regardless of whether the target list is enabled.
• When a Tab control is disabled, all controls on the tab are disabled regardless of whether any of those
controls have an enabling rule that is satised.
• When a Check Box Group is disabled, all controls in the group are disabled regardless of whether the
controlling check box is checked.
Extension Properties
The Extension Properties dialog species information about the current extension within the Custom
Dialog Builder for Extensions, such as the name of the extension and the les in the extension.
Note: The Extension Properties dialog does not apply in Compatibility mode.
• All custom dialogs that are created in the Custom Dialog Builder for Extensions are part of an extension.
• Fields on the Required tab of the Extension Properties dialog must be specied before you can install an
extension and the custom dialogs that are contained in it.
To specify the properties for an extension, from the menus in the Custom Dialog Builder for Extensions
choose:
Extension > Properties
Required properties of extensions
Name
A unique name to associate with the extension. It can consist of up to three words and is not case
sensitive. Characters are restricted to seven-bit ASCII. To minimize the possibility of name conflicts,
you may want to use a multi-word name, where the rst word is an identier for your organization,
such as a URL.
Summary
A short description of the extension that is intended to be displayed as a single line.
Version
A version identier of the form x.x.x, where each component of the identier must be an integer, as in
1.0.0. Zeros are implied if not provided. For example, a version identier of 3.1 implies 3.1.0. The
version identier is independent of the IBM SPSS Statistics version.
Minimum SPSS Statistics Version
The minimum version of SPSS Statistics required to run the extension.
Files
The Files list displays the les that are currently included in the extension. Click Add to add les to
the extension. You can also remove les from the extension and you can extract les to a specied
folder.
• Enhanced custom dialogs have a letype of .cfe and compatible custom dialogs have a letype
of .spd. An extension can contain multiple .cfe les but it can contain only one .spd le.
• An extension must at least include a custom dialog specication (.cfe or .spd) le, or an XML
specication le for an extension command. If an XML specication le is included, then the
extension must include at least one Python, R, or Java code le--specically, a le of
type .py, .pyc, .pyo, .R, .class, or .jar.
• Translation les for components of the extension are added from the Localization settings on the
Optional tab.
• You can add a readme le to the extension. Specify the lename as ReadMe.txt. Users can access
the readme le from the dialog that displays the details for the extension. You can include localized
versions of the readme le, specied as ReadMe_<language identifier>.txt, as in
ReadMe_fr.txt for a French version.
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Optional properties of extensions
General properties
Description
A more detailed description of the extension than that provided for the Summary eld. For example,
you might list the major features available with the extension.
Date
An optional date for the current version of the extension. No formatting is provided.
Author
The author of the extension. You might want to include an email address.
Links
A set of URLs to associate with the extension; for example, the author's home page. The format of this
eld is arbitrary so be sure to delimit multiple URLs with spaces, commas, or some other reasonable
delimiter.
Keywords
A set of keywords with which to associate the extension.
Platform
Information about any restrictions that apply to using the extension on particular operating system
platforms.
Dependencies
Maximum SPSS Statistics Version
The maximum version of IBM SPSS Statistics on which the extension can be run.
Integration Plug-in for Python required
Species whether the Integration Plug-in for Python is required.
• If the Python implementation code is specied to run in Python 3, then select Python 3 for the
Python Version.
• If the extension requires Python modules that are not explicitly included in the extension, then
enter the names in the Required Python Modules control. Any such modules should be contributed
to the IBM SPSS Predictive Analytics community ( https://www.ibm.com/community/spss-
statistics ). To add the rst module, click anywhere in the Required Python Modules control to
highlight the entry eld. Pressing Enter, with the cursor in a given row, will create a new row. You
delete a row by selecting it and pressing Delete.
The user of the extension is responsible for downloading any required Python modules and copying
them to a location that is specied for extension commands, as shown in the output from the SHOW
EXTPATHS command. Alternatively, the modules can be copied to a location on the Python search
path, such as the Python site-packages directory.
Integration Plug-in for R required
Species whether the Integration Plug-in for R is required.
If the extension requires any R packages from the CRAN package repository, then enter the names of
those packages in the Required R Packages control. Names are case sensitive. To add the rst
package, click anywhere in the Required R Packages control to highlight the entry eld. Pressing
Enter, with the cursor in a given row, will create a new row. You delete a row by selecting it and
pressing Delete. When the extension is installed, IBM SPSS Statistics will check if the required R
packages are installed and attempt to download and install any that are missing.
Required Extensions
Enter the names of any extensions that are required by the current extension. To add the rst
extension, click anywhere in the Required Extensions control to highlight the entry eld. Pressing
Enter, with the cursor in a particular row, creates a new row. You delete a row by selecting it and
pressing Delete. The user of the extensions is responsible for installing any required extensions.
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Note: There is no option for specifying the Integration Plug-in for Java because it is always installed with
IBM SPSS Statistics.
Localization
Custom Dialogs
You can add translated versions of the properties le (species all strings that appear in the dialog)
for a custom dialog within the extension. To add translations for a particular dialog, select the dialog,
click Add Translations, and select the folder that contains the translated versions. All translated les
for a particular dialog must be in the same folder. For instructions on creating the translation les, see
the topic “Creating Localized Versions of Custom Dialogs” on page 231.
Translation Catalogues Folder
You can include a folder containing translation catalogues. This allows you to provide localized
messages and localized output from Python or R programs that implement an extension command
included in the extension. You can also provide localized versions of the Summary and Description
elds for the extension that are displayed when end users view the extension details from the
Extension Hub. The set of all localized les for an extension must be in a folder named lang. Browse
to the lang folder that contains the localized les and select that folder.
For information on localizing output from Python and R programs, see the topics on the Integration
Plug-in for Python and the Integration Plug-in for R, in the Help system.
To provide localized versions of the Summary and Description elds, create a le named
<extension name>_<language-identifier>.properties for each language for which a
translation is being provided. At run time, if the .properties le for the current user interface
language cannot be found, the values of the Summary and Description elds that are specied on the
Required and Optional tabs are used.
• <extension name> is the value of the Name eld for the extension, with any spaces replaced by
underscore characters.
• <language-identifier> is the identier for a particular language. Identiers for the languages
that are supported by IBM SPSS Statistics are shown in what follows.
For example, the French translations for an extension named MYORG MYSTAT are stored in the le
MYORG_MYSTAT_fr.properties.
The .properties le must contain the following two lines, which specify the localized text for the
two elds:
Summary=<localized text for Summary field>
Description=<localized text for Description field>
• The keywords Summary and Description must be in English and the localized text must be on the
same line as the keyword, and with no line breaks.
• The le must be in ISO 8859-1 encoding. Characters that cannot be directly represented in this
encoding must be written with Unicode escapes ("\u").
The lang folder that contains the localized les must have a subfolder named <language-
identifier> that contains the localized .properties le for a particular language. For example,
the French .properties le must be in the lang/fr folder.
Language Identiers
de. German
en. English
es. Spanish
fr. French
it. Italian
ja. Japanese
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ko. Korean
pl. Polish
pt_BR. Brazilian Portuguese
ru. Russian
zh_CN. Simplied Chinese
zh_TW. Traditional Chinese
Managing custom dialogs
The Custom Dialog Builder for Extensions allows you to manage custom dialogs, within extensions that
are created by you or by other users. Custom dialogs must be installed before they can be used.
Note: If you are working in compatibility mode, then see the topic “Managing custom dialogs in
compatibility mode” on page 229.
Opening an extension that contains custom dialogs
You can open an extension bundle le (.spe) that contains the specications for one or more custom
dialogs or you can open an installed extension. You can modify any of the enhanced dialogs in the
extension and save or install the extension. Installing the extension installs the dialogs that are contained
in the extension. Saving the extension saves changes that were made to any of the dialogs in the
extension.
To open an extension bundle le, from the menus in the Custom Dialog Builder for Extensions choose:
File > Open
To open an installed extension, from the menus in the Custom Dialog Builder for Extensions choose:
File > Open Installed
Note: If you are opening an installed extension to modify it, choosing File > Install reinstalls it, replacing
the existing version.
Saving to an extension bundle le
Saving the extension that is open in the Custom Dialog Builder for Extensions also saves the custom
dialogs that are contained in the extension. Extensions are saved to an extension bundle le (.spe).
From the menus in the Custom Dialog Builder for Extensions, choose:
File > Save
Installing an extension
Installing the extension that is open in the Custom Dialog Builder for Extensions also installs the custom
dialogs that are contained in the extension. Installing an existing extension replaces the existing version,
which includes replacing all custom dialogs in the extension that were already installed.
To install the currently open extension, from the menus in the Custom Dialog Builder for Extensions
choose:
File > Install
By default, extensions are installed to a general user-writable location for your operating system. For
more information, see the topic “Installation locations for extensions” on page 198.
Uninstalling an extension
From the menus in the Custom Dialog Builder for Extensions, choose:
File > Uninstall
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Uninstalling an extension uninstalls all custom dialogs that are contained in the extension. You can also
uninstall extensions from the Extension Hub.
Converting a compatible custom dialog to an enhanced custom dialog
If the currently open extension contains a compatible custom dialog (.spd) le, you can convert the
compatible dialog to an enhanced dialog. The original compatible version of the custom dialog is retained
in the extension.
From the menus in the Custom Dialog Builder for Extensions, choose:
Extension > Convert Compatible Dialog
Adding a custom dialog to an extension
You can add a new enhanced custom dialog to an extension.
From the menus in the Custom Dialog Builder for Extensions, choose:
Extension > New Dialog
Switching between multiple custom dialogs in an extension
If the current extension contains multiple custom dialogs, you can switch between them.
From the menus in the Custom Dialog Builder for Extensions, choose:
Extension > Edit Dialog and select the custom dialog that you want to work with.
Note: You cannot edit compatible custom dialog (.spd) les in the Custom Dialog Builder for Extensions.
To modify a compatible custom dialog, you must use the Custom Dialog Builder in Compatibility mode. If
you do not have a separate copy of the compatible custom dialog, you can extract it using the Extension
Properties dialog, which is accessed from Extension>Properties within the Custom Dialog Builder for
Extensions.
Creating a new extension
When you create a new extension in the Custom Dialog Builder for Extensions, a new empty custom
dialog is added to the extension.
To create a new extension, from the menus in the Custom Dialog Builder for Extensions choose:
File > New
Managing custom dialogs in compatibility mode
In compatibility mode, you create and modify custom dialogs that are compatible with all releases of IBM
SPSS Statistics and are referred to as compatible custom dialogs.
To open the Custom Dialog Builder in compatibility mode, from the menus choose:
Extensions > Utilities > Custom Dialog Builder (Compatibility mode)...
Opening a compatible custom dialog
You can open a compatible custom dialog package (.spd) le containing the specications for a
compatible custom dialog or you can open an installed compatible custom dialog.
To open a compatible custom dialog package le, from the menus in the Custom Dialog Builder choose:
File > Open
To open an installed compatible custom dialog, from the menus in the Custom Dialog Builder choose:
File > Open Installed
Note: If you open an installed dialog and modify it, choosing File > Install reinstalls it, replacing the
existing version.
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Saving to a compatible custom dialog package le
You can save the specications for a compatible custom dialog to an external le. Specications are
saved to a compatible custom dialog package (.spd) le.
From the menus in the Custom Dialog Builder, choose:
File > Save
Converting a compatible custom dialog to an enhanced custom dialog
You can convert a dialog that is open in compatibility mode to an enhanced dialog to take advantage of
the features that are available for enhanced dialogs. The enhanced version of the dialog is then part of a
new extension.
From the menus in the Custom Dialog Builder, choose:
File > Convert to enhanced
Note: The conversion to an enhanced dialog cannot be undone.
Installing a compatible custom dialog
You can install the dialog that is open in the Custom Dialog Builder or you can install a dialog from a
compatible custom dialog package (.spd) le. Reinstalling an existing dialog replaces the existing
version.
To install the currently open dialog, from the menus in the Custom Dialog Builder choose:
File > Install
To install from a compatible custom dialog package le, from the IBM SPSS Statistics menus choose:
Extensions > Utilities > Install Custom Dialog (Compatibility mode)...
For Windows 7 and later, and Mac, dialogs are installed to a general user-writable location. To view the
current installation locations for custom dialogs, run the following command syntax: SHOW EXTPATHS.
For Linux, and by default, installing a dialog requires write permission to the IBM SPSS Statistics
installation directory.
If you do not have write permissions to the required location or would like to store installed dialogs
elsewhere, you can specify one or more alternate locations by dening the SPSS_CDIALOGS_PATH
environment variable. When present, the paths specied in SPSS_CDIALOGS_PATH take precedence over
the default location. Custom dialogs will be installed to the rst writable location. Note that Mac users
may also utilize the SPSS_CDIALOGS_PATH environment variable. For multiple locations, separate each
with a semicolon on Windows and a colon on Linux and Mac. The specied locations must exist on the
target machine. After setting SPSS_CDIALOGS_PATH, you must restart IBM SPSS Statistics for the
changes to take effect.
To create the SPSS_CDIALOGS_PATH environment variable on Windows, from the Control Panel:
Windows 7
1. Select User Accounts.
2. Select Change my environment variables.
3. Click New, enter SPSS_CDIALOGS_PATH in the Variable name eld and the path(s) in the Variable
value eld.
Windows 8 and Later
1. Select System.
2. Select the Advanced tab, which is accessed from Advanced system settings, and click Environment
Variables.
3. In the User variables section, click New, enter SPSS_CDIALOGS_PATH in the Variable name eld and
the path(s) in the Variable value eld.
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Sharing a compatible custom dialog as an extension
You can create an extension that includes a compatible custom dialog so that you can share the dialog
with other users. See the topic “Creating and editing extension bundles” on page 233 for more
information.
Uninstalling a compatible custom dialog
From the menus in the Custom Dialog Builder, choose:
File > Uninstall
Creating a new compatible custom dialog
To create a new compatible custom dialog, from the menus in the Custom Dialog Builder choose:
File > New
Custom Dialogs for Extension Commands
Extension commands are user-dened IBM SPSS Statistics commands that are implemented in the
Python programming language, R or Java. Once deployed to an instance of IBM SPSS Statistics, an
extension command is run in the same manner as any built-in IBM SPSS Statistics command. You can use
the Custom Dialog Builder to create a dialog for an extension command by specifying the dialog's syntax
template so that it generates the command syntax for the extension command.
When you build your custom dialog in the Custom Dialog Builder for Extensions, you add the les for the
extension command (the XML le that species the syntax of the extension command and the
implementation les that are written in Python, R, or Java) to the extension that contains your dialog. In
the Custom Dialog Builder for Extensions, you add les to an extension from the Extension Properties
dialog, which is accessed from Extension > Properties. You can then install the extension or save it to an
extension bundle (.spe) le so that you can share it with other users.
If you are working in Compatibility mode, you rst save the custom dialog to a compatible custom dialog
package (.spd) le. You then create a new extension bundle and add the .spd le and the les for the
extension command (the XML le that species the syntax of the extension command and the
implementation les that are written in Python, R, or Java) to the extension bundle. You can then install
the extension bundle or share it with other users. See the topic “Creating and editing extension bundles”
on page 233 for more information.
Creating Localized Versions of Custom Dialogs
You can create localized versions of custom dialogs for any of the languages supported by IBM SPSS
Statistics. You can localize any string that appears in a custom dialog and you can localize the optional
help le.
To localize dialog strings
You must create a copy of the properties le associated with the custom dialog for each language that you
plan to deploy. The properties le contains all of the localizable strings associated with the dialog.
Extract the custom dialog le (.cfe) from the extension by selecting the le in the Extension Properties
dialog (within the Custom Dialog Builder for Extensions) and clicking Extract. Then, extract the contents
of the .cfe le. A .cfe le is simply a .zip le. The extracted contents of a .cfe le includes a
properties le for each supported language, where the name of the le for a particular language is given
by <Dialog Name>_<language identifier>.properties (see language identiers in the table
that follows).
Note: If you are working in Compatibility mode, then save the custom dialog to an external .spd le and
extract the contents of the .spd le. An .spd le is simply a .zip le. Make a copy of the <Dialog
Name>.properties le for each language that you plan to deploy and rename it to <Dialog
Name>_<language identifier>.properties. Use the language identiers in the table that follows.
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For example, if the dialog name is mydialog and you want to create a Japanese version of the dialog, then
the localized properties le must be named mydialog_ja.properties.
1. Open each properties le, that you plan to translate, with a text editor that supports UTF-8, such as
Notepad on Windows, or the TextEdit application on Mac. Modify the values associated with any
properties that need to be localized, but do not modify the names of the properties. Properties
associated with a specic control are prexed with the identier for the control. For example, the
ToolTip property for a control with the identier options_button is options_button_tooltip_LABEL. Title
properties are simply named <identier>_LABEL, as in options_button_LABEL.
2. Add the localized versions of the properties les back to the custom dialog le (.cfe) from the
Localization settings on the Optional tab of the Extension Properties dialog. For more information, see
the topic “Optional properties of extensions” on page 226. If you are working with an .spd le, then
the localized properties les must be manually added back to the .spd le.
When the dialog is launched, IBM SPSS Statistics searches for a properties le whose language identier
matches the current language, as specied by the Language drop-down on the General tab in the Options
dialog box. If no such properties le is found, the default le <Dialog Name>.properties is used.
To localize the help le
1. Make a copy of the help le associated with the custom dialog and localize the text for the language
you want.
2. Rename the copy to <Help File>_<language identifier>.htm, using the language identiers
in the table below. For example, if the help le is myhelp.htm and you want to create a German
version of the le, then the localized help le should be named myhelp_de.htm.
Store all localized versions of the help le in the same directory as the non-localized version. When you
add the non-localized help le from the Help File property of Dialog Properties, the localized versions are
automatically added to the dialog.
If there are supplementary les such as image les that also need to be localized, then you must
manually modify the appropriate paths in the main help le to point to the localized versions.
Supplementary les, including localized versions, must be manually added to the custom dialog (.cfe
or .spd) le. See the previous section titled "To localize dialog strings" for information about accessing
and manually modifying custom dialog les.
When the dialog is launched, IBM SPSS Statistics searches for a help le whose language identier
matches the current language, as specied by the Language drop-down on the General tab in the Options
dialog box. If no such help le is found, the help le specied for the dialog (the le specied in the Help
File property of Dialog Properties) is used.
Language Identiers
de. German
en. English
es. Spanish
fr. French
it. Italian
ja. Japanese
ko. Korean
pl. Polish
pt_BR. Brazilian Portuguese
ru. Russian
zh_CN. Simplied Chinese
zh_TW. Traditional Chinese
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Note: Text in custom dialogs and associated help les is not limited to the languages supported by IBM
SPSS Statistics. You are free to write the dialog and help text in any language without creating language-
specic properties and help les. All users of your dialog will then see the text in that language.
Creating and editing extension bundles
You can create or edit any extension bundle from the Create Extension Bundle or Edit Extension Bundle
dialog.
• If you are creating or editing an extension bundle that contains an enhanced custom dialog, then you
might prefer to use the Custom Dialog Builder for Extensions. With the Custom Dialog Builder for
Extensions, you can create or modify an enhanced custom dialog at the same time as you create or edit
the extension that contains the dialog. And you can edit installed extensions from within the Custom
Dialog Builder for Extensions.
• If your extension bundle does not contain an enhanced custom dialog, then you must use the Create
Extension Bundle or Edit Extension Bundle dialog to create or edit the extension bundle. For example, if
you are creating an extension that includes a compatible custom dialog package (.spd) le and no
enhanced dialogs, or an extension that consists only of an extension command, then you must use the
Create Extension Bundle dialog.
Creating an extension bundle
1. From the menus, choose:
Extensions > Utilities > Create Extension Bundle...
2. Enter values for all elds on the Required tab.
3. Enter values for any elds on the Optional tab that are needed for your extension.
4. Specify a target le for the extension bundle.
5. Click Save to save the extension bundle to the specied location. This action closes the Create
Extension Bundle dialog box.
Editing an extension bundle
1. From the menus, choose:
Extensions > Utilities > Edit Extension Bundles...
2. Open the extension bundle.
3. Modify values for any elds on the Required tab.
4. Modify values for any elds on the Optional tab.
5. Specify a target le for the extension bundle.
6. Click Save to save the extension bundle to the specied location. This action closes the Edit Extension
Bundle dialog box.
For detailed information about elds on the Required tab and Optional tab, see the topics “Required
properties of extensions” on page 225 and “Optional properties of extensions” on page 226.
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Chapter 21. Production jobs
Production jobs run IBM SPSS Statistics in an automated fashion. The program runs unattended and ends
after the last command runs. You can also schedule the production job to run automatically at scheduled
times. Production jobs are useful if you often run the same set of time-consuming analyses, such as
weekly reports.
You can run production jobs in two different ways:
Interactively. The program runs unattended in a separate session on either your local computer or a
remote server. Your local computer must remain on (and connected to the remote server, if applicable)
until the job is complete.
In the background on a server. The program runs in a separate session on a remote server. Your local
computer does not have to remain on and does not have to remain connected to the remote server. You
can disconnect and retrieve the results later.
Note: Running a production job on a remote server requires access to a server that is running IBM SPSS
Statistics Server.
Creating and running production jobs
To create and run a production job:
1. From the menus, choose:
Utilities > Production Job
2. Click New to create a new production job.
or
3. Select a production job to run or modify from the list. Click Browse to change the directory location for
the les that appears in the list.
Note: Production Facility job les (.spp) created in releases before release 16.0 do not run in release
16.0 or later. A conversion utility is available to convert Windows and Macintosh Production Facility job
les to production jobs (.spj). For more information, see the topic “Converting Production Facility les”
on page 241.
4. Specify one or more command syntax les to include in the job. Click the plus sign (+) icon to select
command syntax les.
5. Select the output le name, location, and format.
6. Click Run to run the production job interactively or in the background on a server.
Default encoding
By default, IBM SPSS Statistics runs in Unicode mode. You can run production jobs in Unicode mode or
the current locale encoding. The encoding affects how data and syntax les are read. For more
information, see the topic “General options” on page 179.
• Unicode (UTF-8). The production job runs in Unicode mode. By default, text data les and command
syntax les are read as Unicode UTF-8. You can specify a code page encoding for text data les with the
ENCODING subcommand on the GET DATA command. You can specify a code page encoding for syntax
les with the ENCODING subcommand on the INCLUDE or INSERT command.
– Local encoding for syntax les. If a syntax le does not contain a UTF-8 byte order mark, read
syntax les as the current locale encoding. This setting overrides any ENCODING specication on
INCLUDE or INSERT. It also ignores any code page identier in the le.
• Local encoding. The production job runs in the current locale encoding. Unless a different encoding is
explicitly specied on a command that reads text data (for example, GET DATA), text data les are read
in the current locale encoding. Syntax le with a Unicode UTF-8 byte order mark are read as Unicode
UTF-8. All other syntax les are read in the current locale encoding.
Syntax les
Production jobs use command syntax les to tell IBM SPSS Statistics what to do. A command syntax le
is a simple text le containing command syntax. You can use the syntax editor or any text editor to create
the le. You can also generate command syntax by pasting dialog box selections into a syntax window.
See the topic Chapter 14, “Working with Command Syntax,” on page 155 for more information.
If you include multiple command syntax les, the les are concatenated together in the order they appear
in the list and run as a single job.
Syntax format. Controls the form of the syntax rules used for the job.
• Interactive. Each command must end with a period. Periods can appear anywhere within the
command, and commands can continue on multiple lines, but a period as the last nonblank character
on a line is interpreted as the end of the command. Continuation lines and new commands can start
anywhere on a new line. These are the "interactive" rules in effect when you select and run commands
in a syntax window.
• Batch. Each command must start at the beginning of a new line (no blank spaces before the start of the
command), and continuation lines must be indented at least one space. If you want to indent new
commands, you can use a plus sign, dash, or period as the rst character at the start of the line and then
indent the actual command. The period at the end of the command is optional. This setting is
compatible with the syntax rules for command les included with the INCLUDE command.
Note: Do not use the Batch option if your syntax les contain GGRAPH command syntax that includes
GPL statements. GPL statements will only run under interactive rules.
Error Processing. Controls the treatment of error conditions in the job.
• Continue processing after errors. Errors in the job do not automatically stop command processing. The
commands in the production job les are treated as part of the normal command stream, and command
processing continues in the normal fashion.
• Stop processing immediately. Command processing stops when the rst error in a production job le
is encountered. This is compatible with the behavior of command les included with the INCLUDE
command.
Output
These options control the name, location, and format of the production job results. The following format
options are available:
• Viewer le (.spv). Results are saved in IBM SPSS Statistics Viewer format in the specied le location.
You can store to disk or to an IBM SPSS Collaboration and Deployment Services Repository. Storing to
an IBM SPSS Collaboration and Deployment Services Repository requires the Statistics Adapter.
• Word/RTF. Pivot tables are exported as Word tables with all formatting attributes intact (for example,
cell borders, font styles, and background colors). Text output is exported as formatted RTF. Charts, tree
diagrams, and model views are included in PNG format. Note that Microsoft Word might not display
extremely wide tables properly.
• Excel. Pivot table rows, columns, and cells are exported as Excel rows, columns, and cells, with all
formatting attributes intact (for example, cell borders, font styles, and background colors). Text output
is exported with all font attributes intact. Each line in the text output is a row in the Excel le, with the
entire contents of the line in a single cell. Charts, tree diagrams, and model views are included in PNG
format. Output can be exported as Excel 97-2004 or Excel 2007 and higher.
• HTML. Pivot tables are exported as HTML tables. Text output is exported as preformatted HTML. Charts,
tree diagrams, and model views are embedded in the document in the selected graphic format. A
browser compatible with HTML 5 is required for viewing output that is exported in HTML format.
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• Portable Document Format. All output is exported as it appears in Print Preview, with all formatting
attributes intact.
• PowerPoint le. Pivot tables are exported as Word tables and are embedded on separate slides in the
PowerPoint le, with one slide for each pivot table. All formatting attributes of the pivot table are
retained (for example, cell borders, font styles, and background colors). Charts, tree diagrams, and
model views are exported in TIFF format. Text output is not included.
Export to PowerPoint is available only on Windows operating systems.
• Text. Text output formats include plain text, UTF-8, and UTF-16. Pivot tables can be exported in tab-
separated or space-separated format. All text output is exported in space-separated format. For charts,
tree diagrams, and model views, a line is inserted in the text le for each graphic, indicating the image
le name.
Print Viewer le on completion. Sends the nal Viewer output le to the printer on completion of the
production job. This option is not available when running a production job in the background on a remote
server.
HTML options
Table options
No table options are available for HTML format. All pivot tables are converted to HTML tables.
Image options
The available image types are: JPEG, PNG, and BMP. You can also scale the image size from 1% to
200%.
PowerPoint options
Table Options. You can use the Viewer outline entries as slide titles. Each slide contains a single output
item. The title is formed from the outline entry for the item in the outline pane of the Viewer.
Image Options. You can scale the image size from 1% to 200%. (All images are exported to PowerPoint
in TIFF format.)
Note: PowerPoint format is only available on Windows operating systems and requires PowerPoint 97 or
later.
PDF options
Embed bookmarks. This option includes bookmarks in the PDF document that correspond to the Viewer
outline entries. Like the Viewer outline pane, bookmarks can make it much easier to navigate documents
with a large number of output objects.
Embed fonts. Embedding fonts ensures that the PDF document will look the same on all computers.
Otherwise, if some fonts used in the document are not available on the computer being used to view (or
print) the PDF document, font substitution may yield suboptimal results.
Text options
Table Options. Pivot tables can be exported in tab-separated or space-separated format. For space-
separated format, you can also control:
• Column Width. Autot does not wrap any column contents, and each column is as wide as the widest
label or value in that column. Custom sets a maximum column width that is applied to all columns in
the table, and values that exceed that width wrap onto the next line in that column.
• Row/Column Border Character. Controls the characters used to create row and column borders. To
suppress display of row and column borders, enter blank spaces for the values.
Image Options. The available image types are: EPS, JPEG, TIFF, PNG, and BMP. On Windows operating
systems, EMF (enhanced metale) format is also available. You can also scale the image size from 1% to
200%.
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Production jobs with OUTPUT commands
Production jobs honor OUTPUT commands, such as OUTPUT SAVE, OUTPUT ACTIVATE, and OUTPUT
NEW. OUTPUT SAVE commands executed during the course of a production job will write the contents of
the specied output documents to the specied locations. This is in addition to the output le created by
the production job. When using OUTPUT NEW to create a new output document, it is recommended that
you explicitly save it with the OUTPUT SAVE command.
A production job output le consists of the contents of the active output document as of the end of the
job. For jobs containing OUTPUT commands, the output le may not contain all output created in the
session. For example, suppose the production job consists of a number of procedures followed by an
OUTPUT NEW command, followed by more procedures but no more OUTPUT commands. The OUTPUT
NEW command denes a new active output document. At the end of the production job, it will contain
output from only the procedures executed after the OUTPUT NEW command.
Runtime values
Runtime values dened in a production job le and used in a command syntax le simplify tasks such as
running the same analysis for different data les or running the same set of commands for different sets
of variables. For example, you could dene the runtime value @datale to prompt you for a data le name
each time you run a production job that uses the string @datale in place of a le name in the command
syntax le.
• Runtime value substitution uses the macro facility (DEFINE-!ENDDEFINE) to create string substitution
values.
• Runtime values in command syntax les are ignored if they are enclosed in quotation marks. If the
runtime value needs to be quoted, select Quote Value. If the runtime value is only part of a quoted
string, you can include the runtime value in a macro with the !UNQUOTE and !EVAL parameters.
Symbol. The string in the command syntax le that triggers the production job to prompt the user for a
value. The symbol name must begin with an @ sign and must conform to variable naming rules. See the
topic “Variable names” on page 46 for more information.
Default Value. The value that the production job supplies by default if you don't enter a different value.
This value is displayed when the production job prompts you for information. You can replace or modify
the value at runtime. If you don't provide a default value, don't use the silent keyword when running the
production job with command line switches, unless you also use the -symbol switch to specify runtime
values. See the topic “Running production jobs from a command line” on page 240 for more information.
User Prompt. The descriptive label that is displayed when the production job prompts you to enter
information. For example, you could use the phrase "What data le do you want to use?" to identify a eld
that requires a data lename.
Quote Value. Encloses the default value or the value entered by the user in quotes. For example, le
specications should be enclosed in quotes.
Command syntax le with user prompt symbols
GET FILE @datafile. /*check the Quote value option to quote file specifications.
FREQUENCIES VARIABLES=@varlist. /*do not check the Quote value option
Using a macro to replace part of a string value
If the entire replacement string is enclosed in quotes, you can use the Quote Value option. If the
replacement string is only part of a quoted string, you can include the runtime value in a macro, using
the !UNQUOTE and !EVAL functions.
DEFINE !LabelSub()
VARIABLE LABELS Var1
!QUOTE(!concat(!UNQUOTE('First part of label - '), !UNQUOTE(!EVAL(@replace)), !UNQUOTE(' -
rest of label'))).
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!ENDDEFINE.
!LabelSub.
Run options
You can run production jobs in two different ways:
Interactively. The program runs unattended in a separate session on either your local computer or a
remote server. Your local computer must remain on (and connected to the remote server, if applicable)
until the job is complete.
In the background on a server. The program runs in a separate session on a remote server. Your local
computer does not have to remain on and does not have to remain connected to the remote server. You
can disconnect and retrieve the results later.
Note: Running a production job on a remote server requires access to a server that is running IBM SPSS
Statistics Server.
Statistics server. If you select to run the production job in the background on a remote server, you must
specify the server on which it will run. Click Select Server to specify the server. This applies only to jobs
run in the background on a remote server, not jobs run interactively on a remote server.
Server login
Use the Server login dialog to add and modify remote servers and to select the server to use to run the
current production job. Remote servers usually require a user ID and password, and a domain name may
also be necessary. Contact your system administrator for information about available servers, a user ID
and password, domain names, and other connection information.
If your site is running IBM SPSS Collaboration and Deployment Services 3.5 or later, you can click
Search... to view a list of servers that are available on your network. If you are not logged on to a IBM
SPSS Collaboration and Deployment Services Repository, you will be prompted to enter connection
information before you can view the list of servers.
Adding and Editing Server Login Settings
Use the Server Login Settings dialog box to add or edit connection information for remote servers for use
in distributed analysis mode.
Contact your system administrator for a list of available servers, port numbers for the servers, and
additional connection information. Do not use the Secure Socket Layer unless instructed to do so by your
administrator.
Server Name. A server "name" can be an alphanumeric name that is assigned to a computer (for
example, NetworkServer) or a unique IP address that is assigned to a computer (for example,
202.123.456.78).
Port Number. The port number is the port that the server software uses for communications.
Description. You can enter an optional description to display in the servers list.
Connect with Secure Socket Layer. Secure Socket Layer (SSL) encrypts requests for distributed analysis
when they are sent to the remote server. Before you use SSL, check with your administrator. For this
option to be enabled, SSL must be congured on your desktop computer and the server.
User prompts
A production job prompts you for values whenever you run a production job that contains dened runtime
symbols. You can replace or modify the default values that are displayed. Those values are then
substituted for the runtime symbols in all command syntax les associated with the production job.
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Background job status
The background job status tab displays the status of production jobs that have been submitted to run in
the background on a remote server.
Server name. Displays the name of the currently selected remote server. Only jobs submitted to that
server are displayed in the list. To display jobs submitted to a different server, click Select Server.
Job status information. Includes production job name, current job status, and start and end time.
Refresh. Updates the job status information.
Get job output. Retrieves the output from the selected production job. The output for each job resides on
the server the job was run on; so you must switch to the status for that server to select the job and
retrieve the output. This button is disabled if the job status is Running.
Cancel job. Cancels the selected production job. This button is only enabled if the job status is Running.
Remove job. Removes the selected production job. This removes the job from the list and removes the
associated les from the remote server. This button is disabled if the job status is Running.
Note: Background job status does not reflect the status of any jobs run interactively on a remote server.
Running production jobs from a command line
Command line switches enable you to schedule production jobs to run automatically at certain times,
using scheduling utilities available on your operating system. The basic form of the command line
argument is:
Windows:
stats --production filename.spj
MacOS:
SPSSStatistics --production filename.spj
Depending on how you invoke the production job, you may need to include directory paths for the
application's executable le (located in the directory in which the application is installed) and/or the
production job le.
Note: You cannot run command line production jobs while the IBM SPSS Statistics Subscription
application is running.
You can run production jobs from a command line with the following switches:
-production [prompt|silent]. Start the application in production mode. The prompt and silent
keywords specify whether to display the dialog box that prompts for runtime values if they are specied in
the job. The prompt keyword is the default and shows the dialog box. The silent keyword suppresses the
dialog box. If you use the silent keyword, you can dene the runtime symbols with the -symbol
switch. Otherwise, the default value is used. The -switchserver and -singleseat switches are
ignored when using the -production switch.
-symbol <values>. List of symbol-value pairs used in the production job. Each symbol name starts with
@. Values that contain spaces should be enclosed in quotes. Rules for including quotes or apostrophes in
string literals may vary across operating systems, but enclosing a string that includes single quotes or
apostrophes in double quotes usually works (for example, “'a quoted value'”). The symbols must be
dened in the production job using the Runtime Values tab. See the topic “Runtime values” on page 238
for more information.
-background. Run the production job in the background on a remote server. Your local computer does
not have to remain on and does not have to remain connected to the remote server. You can disconnect
and retrieve the results later. You must also include the -production switch and specify the server
using the -server switch.
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To run production jobs on a remote server, you also need to specify the server login information:
-server <inet:hostname:port> or -server <ssl:hostname:port>. The name or IP address and port
number of the server. Windows only.
-user <name>. A valid user name. If a domain name is required, precede the user name with the domain
name and a backslash (\). Windows only.
-password <password>. The user's password.
Example
Windows:
statssub --production /Users/Simon/job.spj silent --symbol @sex male
MacOS:
IBMSPSSStatistics --production /Users/Simon/job.spj silent --symbol @sex male
• This example assumes that you are running the command line from the installation directory, so no path
is required for the IBM SPSS Statistics Subscription executable le. The default installation path is as
follows:
Windows: $InstalledPath$
MacOS: $InstalledPath$/IBMSPSSStatistics.app/Contents/MacOS/
• The directory path for the location of the production job uses the Windows back slash convention. On
Macintosh and Linux, use forward slashes. The forward slashes in the quoted data le specication will
work on all operating systems since this quoted string is inserted into the command syntax le and
forward slashes are acceptable in commands that include le specications (for example, GET FILE,
GET DATA, SAVE) on all operating systems.
• The silent keyword suppresses any user prompts in the production job, and the --symbol switch
inserts the quoted data le name and location wherever the runtime symbol @sex male appears in the
command syntax les included in the production job.
Converting Production Facility les
Production Facility job les (.spp) created in releases prior to 16.0 will not run in release 16.0 or later. For
Windows and Macintosh Production Facility job les created in earlier releases, you can use prodconvert,
located in the installation directory, to convert those les to new production job les (.spj). Run
prodconvert from a command window using the following specications:
[installpath]\prodconvert [filepath]\filename.spp
where [installpath] is the location of the folder in which IBM SPSS Statistics is installed and [lepath] is
the folder t the original production job le is located. A new le with the same name but with the
extension .spj is created in the same folder as the original le. (Note: If the path contains spaces, enclose
each path and le specication in double quotes. On Macintosh operating systems, use forward slashes
instead of back slashes.)
Limitations
• WMF and EMF chart formats are not supported. PNG format is used in place of these formats.
• The export options Output Document (No Charts), Charts Only, and Nothing are not supported. All
output objects supported by the selected format are included.
• Remote server settings are ignored. To specify remote server settings for distributed analysis, you need
to run the production job from a command line, using command line switches to specify the server
settings. See the topic “Running production jobs from a command line” on page 240 for more
information.
• Publish to Web settings are ignored.
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Chapter 22. Output Management System
The Output Management System (OMS) provides the ability to automatically write selected categories of
output to different output les in different formats. Formats include: Word, Excel, PDF, IBM SPSS
Statistics data le format (.sav), Viewer le format (.spv), XML, HTML, and text. See the topic “OMS
options” on page 246 for more information.
To use the Output Management System Control Panel
1. From the menus choose:
Utilities > OMS Control Panel...
You can use the control panel to start and stop the routing of output to various destinations.
• Each OMS request remains active until explicitly ended or until the end of the session.
• A destination le that is specied on an OMS request is unavailable to other procedures and other
applications until the OMS request is ended.
• While an OMS request is active, the specied destination les are stored in memory (RAM), so active
OMS requests that write a large amount of output to external les may consume a large amount of
memory.
• Multiple OMS requests are independent of each other. The same output can be routed to different
locations in different formats, based on the specications in different OMS requests.
• The order of the output objects in any particular destination is the order in which they were created,
which is determined by the order and operation of the procedures that generate the output.
Limitations
• For Output XML format, the specication for the Headings output type has no effect. If any output from
a procedure is included, the procedure title output is included.
• If the OMS specication results in nothing other than Headings objects or a Notes tables being included
for a procedure, then nothing is included for that procedure.
Adding new OMS requests
1. Select the output types (tables, charts, etc.) that you want to include. See the topic “Output object
types” on page 244 for more information.
2. Select the commands to include. If you want to include all output, select all items in the list. See the
topic “Command identiers and table subtypes” on page 245 for more information.
3. For commands that produce pivot table output, select the specic table types to include.
The list displays only the tables that are available in the selected commands; any table type that is
available in one or more of the selected commands is displayed in the list. If no commands are
selected, all table types are displayed. See the topic “Command identiers and table subtypes” on
page 245 for more information.
4. To select tables based on text labels instead of subtypes, click Labels. See the topic “Labels” on page
245 for more information.
5. Click Options to specify the output format (for example, IBM SPSS Statistics data le, XML, or HTML).
By default, Output XML format is used. See the topic “OMS options” on page 246 for more information.
6. Specify an output destination:
• File. All selected output is routed to a single le.
• Based on object names. Output is routed to multiple destination les based on object names. A
separate le is created for each output object, with a lename based on either table subtype names
or table labels. Enter the destination folder name.
• New dataset. For IBM SPSS Statistics data le format output, you can route the output to a dataset.
The dataset is available for subsequent use in the same session but is not saved unless you explicitly
save it as a le prior to the end of the session. This option is available only for IBM SPSS Statistics
data le format output. Dataset names must conform to variable-naming rules. See the topic
“Variable names” on page 46 for more information.
7. Optionally:
• Exclude the selected output from the Viewer. If you select Exclude from Viewer, the output types in
the OMS request will not be displayed in the Viewer window. If multiple active OMS requests include
the same output types, the display of those output types in the Viewer is determined by the most recent
OMS request that contains those output types. See the topic “Excluding output display from the viewer”
on page 248 for more information.
• Assign an ID string to the request. All requests are automatically assigned an ID value, and you can
override the system default ID string with a descriptive ID, which can be useful if you have multiple
active requests that you want to identify easily. ID values that you assign cannot start with a dollar sign
($).
Tips for selecting multiple items in a list
The following tips are for selecting multiple items in a list:
• Press Ctrl+A to select all items in a list.
• Use Shift+click to select multiple contiguous items.
• Use Ctrl+click to select multiple noncontiguous items.
To end and delete OMS requests
Active and new OMS requests are displayed in the Requests list, with the most recent request at the top.
You can change the widths of the information columns by clicking and dragging the borders, and you can
scroll the list horizontally to see more information about a particular request.
An asterisk (*) after the word Active in the Status column indicates an OMS request that was created with
command syntax that includes features that are not available in the Control Panel.
To end a specic, active OMS request:
1. In the Requests list, click any cell in the row for the request.
2. Click End.
To end all active OMS requests:
1. Click End All.
To delete a new request (a request that has been added but is not yet active):
1. In the Requests list, click any cell in the row for the request.
2. Click Delete.
Note: Active OMS requests are not ended until you click OK.
Output object types
There are different types of output objects:
Charts. This includes charts created with the Chart Builder, charting procedures, and charts created by
statistical procedures (for example, a bar chart created by the Frequencies procedure).
Headings. Text objects that are labeled Title in the outline pane of the Viewer.
Logs. Log text objects. Log objects contain certain types of error and warning messages. Depending on
your Options settings (Edit menu, Options, Viewer tab), log objects may also contain the command syntax
that is executed during the session. Log objects are labeled Log in the outline pane of the Viewer.
Models. Output objects displayed in the Model Viewer. A single model object can contain multiple views
of the model, including both tables and charts.
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Tables. Output objects that are pivot tables in the Viewer (includes Notes tables). Tables are the only
output objects that can be routed to IBM SPSS Statistics data le (.sav) format.
Texts. Text objects that aren't logs or headings (includes objects labeled Text Output in the outline pane
of the Viewer).
Trees. Tree model diagrams that are produced by the Decision Tree option.
Warnings. Warning objects contain certain types of error and warning messages.
Command identiers and table subtypes
Command identiers
Command identiers are available for all statistical and charting procedures and any other commands
that produce blocks of output with their own identiable heading in the outline pane of the Viewer. These
identiers are usually (but not always) the same or similar to the procedure names on the menus and
dialog box titles, which are usually (but not always) similar to the underlying command names. For
example, the command identier for the Frequencies procedure is "Frequencies," and the underlying
command name is also the same.
There are, however, some cases where the procedure name and the command identier and/or the
command name are not all that similar. For example, all of the procedures on the Nonparametric Tests
submenu (from the Analyze menu) use the same underlying command, and the command identier is the
same as the underlying command name: Npar Tests.
Table subtypes
Table subtypes are the different types of pivot tables that can be produced. Some subtypes are produced
by only one command; other subtypes can be produced by multiple commands (although the tables may
not look similar). Although table subtype names are generally descriptive, there can be many names to
choose from (particularly if you have selected a large number of commands); also, two subtypes may
have very similar names.
To nd command identiers and table subtypes
When in doubt, you can nd command identiers and table subtype names in the Viewer window:
1. Run the procedure to generate some output in the Viewer.
2. Right-click the item in the outline pane of the Viewer.
3. Choose Copy OMS Command Identier or Copy OMS Table Subtype.
4. Paste the copied command identier or table subtype name into any text editor (such as a Syntax
Editor window).
Labels
As an alternative to table subtype names, you can select tables based on the text that is displayed in the
outline pane of the Viewer. You can also select other object types based on their labels. Labels are useful
for differentiating between multiple tables of the same type in which the outline text reflects some
attribute of the particular output object, such as the variable names or labels. There are, however, a
number of factors that can affect the label text:
• If split-le processing is on, split-le group identication may be appended to the label.
• Labels that include information about variables or values are affected by your current output label
options settings (Edit menu, Options, Output Labels tab).
• Labels are affected by the current output language setting (Edit menu, Options, General tab).
To specify labels to use to identify output objects
1. In the Output Management System Control Panel, select one or more output types and then select one
or more commands.
2. Click Labels.
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245
3. Enter the label exactly as it appears in the outline pane of the Viewer window. (You can also right-click
the item in the outline, choose Copy OMS Label, and paste the copied label into the Label text eld.)
4. Click Add.
5. Repeat the process for each label that you want to include.
6. Click Continue.
Wildcards
You can use an asterisk (*) as the last character of the label string as a wildcard character. All labels that
begin with the specied string (except for the asterisk) will be selected. This process works only when the
asterisk is the last character, because asterisks can appear as valid characters inside a label.
OMS options
You can use the OMS Options dialog box to:
• Specify the output format.
• Specify the image format (for HTML and Output XML output formats).
• Specify what table dimension elements should go into the row dimension.
• Include a variable that identies the sequential table number that is the source for each case (for IBM
SPSS Statistics data le format).
Specifying OMS options
1. Click Options in the Output Management System Control Panel.
Format
Excel
Excel 97-2004 and Excel 2007 and higher formats. Pivot table rows, columns, and cells are exported
as Excel rows, columns, and cells, with all formatting attributes intact -- for example, cell borders,
font styles, and background colors. Text output is exported with all font attributes intact. Each line in
the text output is a row in the Excel le, with the entire contents of the line contained in a single cell.
Charts, tree diagrams, and model views are included in PNG format.
HTML
Output objects that would be pivot tables in the Viewer are converted to HTML tables. Text output
objects are tagged <PRE> in the HTML. Charts, tree diagrams, and model views are embedded in the
document in the selected format.
Output XML
XML that conforms to the spss-output schema.
PDF
Output is exported as it would appear in Print Preview, with all formatting attributes intact. The PDF
le includes bookmarks that correspond to the entries in the Viewer outline pane.
IBM SPSS Statistics Data File
This format is a binary le format. All output object types other than tables are excluded. Each column
of a table becomes a variable in the data le. To use a data le that is created with OMS in the same
session, you must end the active OMS request before you can open the data le.See the topic
“Routing output to IBM SPSS Statistics data les” on page 249
for more information.
Text
Space-separated text. Output is written as text, with tabular output aligned with spaces for xed-
pitch fonts. Charts, tree diagrams, and model views are excluded.
Tabbed Text
Tab-delimited text. For output that is displayed as pivot tables in the Viewer, tabs delimit table
column elements. Text block lines are written as is; no attempt is made to divide them with tabs at
useful places. Charts, tree diagrams, and model views are excluded.
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Viewer File
This is the same format used when you save the contents of a Viewer window.
Word/RTF
Pivot tables are exported as Word tables with all formatting attributes intact--for example, cell
borders, font styles, and background colors. Text output is exported as formatted RTF. Charts, tree
diagrams, and model views are included in PNG format.
Graphics Images
For HTML and Output XML formats, you can include charts, tree diagrams, and model views as image les.
A separate image le is created for each chart and/or tree.
• For HTML document format, standard <IMG SRC='filename'> tags are included in the HTML
document for each image le.
• For Output XML document format, the XML le contains a chart element with an ImageFile attribute
of the general form <chart imageFile="filepath/filename"/> for each image le.
• Image les are saved in a separate subdirectory (folder). The subdirectory name is the name of the
destination le, without any extension and with _les appended to the end. For example, if the
destination le is julydata.htm, the images subdirectory will be named julydata_les.
Format
The available image formats are PNG, JPG, and BMP.
Size
You can scale the image size from 10% to 200%.
Include Imagemaps
For HTML document format, this option creates image map ToolTips that display information for some
chart elements, such as the value of the selected point on a line chart or bar on a bar chart.
Table Pivots
For pivot table output, you can specify the dimension element(s) that should appear in the columns. All
other dimension elements appear in the rows. For IBM SPSS Statistics data le format, table columns
become variables, and rows become cases.
• If you specify multiple dimension elements for the columns, they are nested in the columns in the order
in which they are listed. For IBM SPSS Statistics data le format, variable names are constructed by
nested column elements. See the topic “Variable names in OMS-generated data les” on page 249
for
more information.
• If a table doesn't contain any of the listed dimension elements, all dimension elements for that table
will appear in the rows.
• Table pivots that are specied here have no effect on tables that are displayed in the Viewer.
Each dimension of a table--row, column, layer--may contain zero or more elements. For example, a
simple two-dimensional crosstabulation contains a single row dimension element and a single column
dimension element, each of which contains one of the variables that are used in the table. You can use
either positional arguments or dimension element "names" to specify the dimension elements that you
want to put into the column dimension.
All dimensions in rows
Creates a single row for each table. For IBM SPSS Statistics format data les, this means each table is
a single case, and all the table elements are variables.
List of positions
The general form of a positional argument is a letter indicating the default position of the element--C
for column, R for row, or L for layer--followed by a positive integer indicating the default position
within that dimension. For example, R1 would indicate the outermost row dimension element.
• To specify multiple elements from multiple dimensions, separate each dimension with a space—for
example, R1 C2.
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• The dimension letter followed by ALL indicates all elements in that dimension in their default order.
For example, CALL is the same as the default behavior (using all column elements in their default
order to create columns).
• CALL RALL LALL (or RALL CALL LALL, and so on) will put all dimension elements into the columns.
For IBM SPSS Statistics data le format, this creates one row/case per table in the data le.
List of dimension names
As an alternative to positional arguments, you can use dimension element "names," which are the text
labels that appear in the table. For example, a simple two-dimensional crosstabulation contains a
single row dimension element and a single column dimension element, each with labels based on the
variables in those dimensions, plus a single layer dimension element labeled Statistics (if English is
the output language).
• Dimension element names may vary, based on the output language and/or settings that affect the
display of variable names and/or labels in tables.
• Each dimension element name must be enclosed in single or double quotation marks. To specify
multiple dimension element names, include a space between each quoted name.
The labels that are associated with the dimension elements may not always be obvious.
Viewing all dimension elements and their labels for a pivot table
1. Activate (double-click) the table in the Viewer.
2. From the menus choose:
View > Show All
or
3. If the pivoting trays aren't displayed, from the menus choose:
Pivot > Pivoting Trays
The element labels are dispalyed in the pivoting trays.
Logging
You can record OMS activity in a log in XML or text format.
• The log tracks all new OMS requests for the session but does not include OMS requests that were
already active before you requested a log.
• The current log le ends if you specify a new log le or if you deselect (clear) Log OMS activity.
How to specify OMS logging
To specify OMS logging:
1. Click Logging in the Output Management System Control Panel.
Excluding output display from the viewer
The Exclude from Viewer check box affects all output that is selected in the OMS request by suppressing
the display of that output in the Viewer window. This process is often useful for production jobs that
generate a lot of output and when you don't need the results in the form of a Viewer document (.spv le).
You can also use this functionality to suppress the display of particular output objects that you simply
never want to see, without routing any other output to some external le and format.
To suppress the display of certain output objects without routing other output to an external le:
1. Create an OMS request that identies the unwanted output.
2. Select Exclude from Viewer.
3. For the output destination, select File--but leave the File eld blank.
4. Click Add.
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The selected output will be excluded from the Viewer while all other output will be displayed in the
Viewer in the normal fashion.
Note: This setting has no effect on OMS output saved to external formats or les, including the Viewer
SPV format. It also has no effect on output saved to SPV format in a batch job executed with the Batch
Facility (available with IBM SPSS Statistics Server).
Routing output to IBM SPSS Statistics data les
A data le in IBM SPSS Statistics format consists of variables in the columns and cases in the rows, which
is essentially the format in which pivot tables are converted to data les:
• Columns in the table are variables in the data le. Valid variable names are constructed from the
column labels.
• Row labels in the table become variables with generic variable names (Var1, Var2, Var3, and so on) in
the data le. The values of these variables are the row labels in the table.
• Three table-identier variables are automatically included in the data le: Command_, Subtype_, and
Label_. All three are string variables. The rst two variables correspond to the command and subtype
identiers. See the topic “Command identiers and table subtypes” on page 245 for more information.
Label_ contains the table title text.
• Rows in the table become cases in the data le.
Data les created from multiple tables
When multiple tables are routed to the same data le, each table is added to the data le in a fashion that
is similar to merging data les by adding cases from one data le to another data le (Data menu, Merge
Files, Add Cases).
• Each subsequent table will always add cases to the data le.
• If column labels in the tables differ, each table may also add variables to the data le, with missing
values for cases from other tables that don't have an identically labeled column.
• If any tables do not have the same number of row elements as the other tables, no data le will be
created. The number of rows doesn't have to be the same; the number of row elements that become
variables in the data le must be the same. For example, a two-variable crosstabulation and a three-
variable crosstabulation contain different numbers of row elements, because the “layer” variable is
actually nested within the row variable in the default three-variable crosstabulation display.
Controlling column elements to control variables in the data le
In the Options dialog box of the Output Management System Control Panel, you can specify which
dimension elements should be in the columns and therefore will be used to create variables in the
generated data le. This process is equivalent to pivoting the table in the Viewer.
For example, the Frequencies procedure produces a descriptive statistics table with statistics in the rows,
while the Descriptives procedure produces a descriptive statistics table with statistics in the columns. To
include both table types in the same data le in a meaningful fashion, you need to change the column
dimension for one of the table types.
Because both table types use the element name "Statistics" for the statistics dimension, we can put the
statistics from the Frequencies statistics table in the columns simply by specifying "Statistics" (in
quotation marks) in the list of dimension names in the OMS Options dialog box.
Some of the variables will have missing values, because the table structures still aren't exactly the same
with statistics in the columns.
Variable names in OMS-generated data les
OMS constructs valid, unique variable names from column labels:
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• Row and layer elements are assigned generic variable names—the prex Var followed by a sequential
number.
• Characters that aren't allowed in variable names (spaces, parentheses, etc.) are removed. For example,
“This (Column) Label” would become a variable named ThisColumnLabel.
• If the label begins with a character that is allowed in variable names but not allowed as the rst
character (for example, a number), “@” is inserted as a prex. For example, “2nd” would become a
variable named @2nd.
• Column labels that would result in duplicate variable names are resolved by appending an underscore
and a sequential letter. For example, the second instance of "Count" would become a variable named
Count_A.
• Underscores or periods at the end of labels are removed from the resulting variable names. The
underscores at the end of the automatically generated variables Command_, Subtype_, and Label_ are
not removed.
• If more than one element is in the column dimension, variable names are constructed by combining
category labels with underscores between category labels. Group labels are not included. For example,
if VarB is nested under VarA in the columns, you would get variables like CatA1_CatB1, not
VarA_CatA1_VarB_CatB1.
OXML table structure
Output XML (OXML) is XML that conforms to the spss-output schema. For a detailed description of the
schema, see the Output Schema section of the Help system.
• OMS command and subtype identiers are used as values of the command and subType attributes in
OXML. An example is as follows:
<command text="Frequencies" command="Frequencies"...>
<pivotTable text="Gender" label="Gender" subType="Frequencies"...>
• OMS command and subType attribute values are not affected by output language or display settings for
variable names/labels or values/value labels.
• XML is case sensitive. A subType attribute value of "frequencies" is not the same as a subType
attribute value of "Frequencies."
• All information that is displayed in a table is contained in attribute values in OXML. At the individual cell
level, OXML consists of “empty” elements that contain attributes but no “content” other than the
content that is contained in attribute values.
• Table structure in OXML is represented row by row; elements that represent columns are nested within
the rows, and individual cells are nested within the column elements:
<pivotTable...>
<dimension axis='row'...>
<dimension axis='column'...>
<category...>
<cell text=’...' number='...' decimals='...'/>
</category>
<category...>
<cell text='...' number='...' decimals='...'/>
</category>
</dimension>
</dimension>
...
</pivotTable>
The preceding example is a simplied representation of the structure that shows the descendant/
ancestor relationships of these elements. However, the example does not necessarily show the parent/
child relationships, because there are typically intervening nested element levels.
The following example shows a simple frequency table and the complete output XML representation of
that table.
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Table 23. Simple frequency table
Gender Frequency Percent Valid Percent Cumulative
Percent
Valid Female 216 45.6 45.6 45.6
Male 258 54.4 54.4 100.0
Total 474 100.0 100.0
<?xml version="1.0" encoding="UTF-8" ?>
<outputTreeoutputTree xmlns="http://xml.spss.com/spss/oms"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://xml.spss.com/spss/oms
http://xml.spss.com/spss/oms/spss-output-1.0.xsd">
<command text="Frequencies" command="Frequencies"
displayTableValues="label" displayOutlineValues="label"
displayTableVariables="label" displayOutlineVariables="label">
<pivotTable text="Gender" label="Gender" subType="Frequencies"
varName="gender" variable="true">
<dimension axis="row" text="Gender" label="Gender"
varName="gender" variable="true">
<group text="Valid">
<group hide="true" text="Dummy">
<category text="Female" label="Female" string="f"
varName="gender">
<dimension axis="column" text="Statistics">
<category text="Frequency">
<cell text="216" number="216"/>
</category>
<category text="Percent">
<cell text="45.6" number="45.569620253165" decimals="1"/>
</category>
<category text="Valid Percent">
<cell text="45.6" number="45.569620253165" decimals="1"/>
</category>
<category text="Cumulative Percent">
<cell text="45.6" number="45.569620253165" decimals="1"/>
</category>
</dimension>
</category>
<category text="Male" label="Male" string="m" varName="gender">
<dimension axis="column" text="Statistics">
<category text="Frequency">
<cell text="258" number="258"/>
</category>
<category text="Percent">
<cell text="54.4" number="54.430379746835" decimals="1"/>
</category>
<category text="Valid Percent">
<cell text="54.4" number="54.430379746835" decimals="1"/>
</category>
<category text="Cumulative Percent">
<cell text="100.0" number="100" decimals="1"/>
</category>
</dimension>
</category>
</group>
<category text="Total">
<dimension axis="column" text="Statistics">
<category text="Frequency">
<cell text="474" number="474"/>
</category>
<category text="Percent">
<cell text="100.0" number="100" decimals="1"/>
</category>
<category text="Valid Percent">
<cell text="100.0" number="100" decimals="1"/>
</category>
</dimension>
</category>
</group>
</dimension>
</pivotTable>
</command>
</outputTree>
Figure 2. Output XML for the simple frequency table
As you may notice, a simple, small table produces a substantial amount of XML. That's partly because the
XML contains some information that is not readily apparent in the original table, some information that
might not even be available in the original table, and a certain amount of redundancy.
• The table contents as they are (or would be) displayed in a pivot table in the Viewer are contained in
text attributes. An example is as follows:
<command text="Frequencies" command="Frequencies"...>
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251
• Text attributes can be affected by both output language and settings that affect the display of variable
names/labels and values/value labels. In this example, the text attribute value will differ, depending
on the output language, whereas the command attribute value remains the same, regardless of output
language.
• Wherever variables or values of variables are used in row or column labels, the XML will contain a text
attribute and one or more additional attribute values. An example is as follows:
<dimension axis="row" text="Gender" label="Gender" varName="gender">
...<category text="Female" label="Female" string="f" varName="gender">
• For a numeric variable, there would be a number attribute instead of a string attribute. The label
attribute is present only if the variable or values have dened labels.
• The <cell> elements that contain cell values for numbers will contain the text attribute and one or
more additional attribute values. An example is as follows:
<cell text="45.6" number="45.569620253165" decimals="1"/>
The number attribute is the actual, unrounded numeric value, and the decimals attribute indicates the
number of decimal positions that are displayed in the table.
• Because columns are nested within rows, the category element that identies each column is repeated
for each row. For example, because the statistics are displayed in the columns, the element <category
text="Frequency"> appears three times in the XML: once for the male row, once for the female row,
and once for the total row.
OMS identiers
The OMS Identiers dialog box is designed to assist you in writing OMS command syntax. You can use this
dialog box to paste selected command and subtype identiers into a command syntax window.
To use the oms identiers dialog box
1. From the menus choose:
Utilities > OMS Identiers...
2. Select one or more command or subtype identiers. (Use Ctrl+click to select multiple identiers in
each list.)
3. Click Paste Commands and/or Paste Subtypes.
• The list of available subtypes is based on the currently selected command(s). If multiple commands are
selected, the list of available subtypes is the union of all subtypes that are available for any of the
selected commands. If no commands are selected, all subtypes are listed.
• The identiers are pasted into the designated command syntax window at the current cursor location. If
there are no open command syntax windows, a new syntax window is automatically opened.
• Each command and/or subtype identier is enclosed in quotation marks when pasted, because OMS
command syntax requires these quotation marks.
• Identier lists for the COMMANDS and SUBTYPES keywords must be enclosed in brackets, as in:
/IF COMMANDS=['Crosstabs' 'Descriptives']
SUBTYPES=['Crosstabulation' 'Descriptive Statistics']
Copying OMS identiers from the viewer outline
You can copy and paste OMS command and subtype identiers from the Viewer outline pane.
1. In the outline pane, right-click the outline entry for the item.
2. Choose Copy OMS Command Identier or Copy OMS Table Subtype.
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This method differs from the OMS Identiers dialog box method in one respect: The copied identier is
not automatically pasted into a command syntax window. The identier is simply copied to the clipboard,
and you can then paste it anywhere you want. Because command and subtype identier values are
identical to the corresponding command and subtype attribute values in Output XML format (OXML), you
might nd this copy/paste method useful if you write XSLT transformations.
Copying OMS labels
Instead of identiers, you can copy labels for use with the LABELS keyword. Labels can be used to
differentiate between multiple graphs or multiple tables of the same type in which the outline text
reflects some attribute of the particular output object, such as the variable names or labels. There are,
however, a number of factors that can affect the label text:
• If split-le processing is on, split-le group identication may be appended to the label.
• Labels that include information about variables or values are affected by the settings for the display of
variable names/labels and values/value labels in the outline pane (Edit menu, Options, Output Labels
tab).
• Labels are affected by the current output language setting (Edit menu, Options, General tab).
To copy OMS labels
1. In the outline pane, right-click the outline entry for the item.
2. Choose Copy OMS Label.
As with command and subtype identiers, the labels must be in quotation marks, and the entire list must
be enclosed in square brackets, as in:
/IF LABELS=['Employment Category' 'Education Level']
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Chapter 23. Scripting Facility
The scripting facility allows you to automate tasks, including:
• Opening and saving data les.
• Exporting charts as graphic les in a variety of formats.
• Customizing output in the Viewer.
The available scripting languages depend on your platform. For Windows, the available scripting
languages are Basic, which is installed with the Core system, and the Python programming language. For
all other platforms, scripting is available with the Python programming language.
To use scripting with the Python programming language, you need IBM SPSS Statistics - Essentials for
Python, which is installed by default with your IBM SPSS Statistics product.
Default Script Language
The default script language determines the script editor that is launched when new scripts are created. It
also species the default language whose executable will be used to run autoscripts. On Windows, the
default script language is Basic. You can change the default language from the Scripts tab in the Options
dialog. See the topic “Script options” on page 189
for more information.
Sample Scripts
A number of scripts are included with the software, in the Samples subdirectory of the directory where
IBM SPSS Statistics is installed. You can use these scripts as they are or you can customize them to your
needs.
To Create a New Script
1. From the menus choose:
File > New > Script
The editor associated with the default script language opens.
To Run a Script
1. From the menus choose:
Utilities > Run Script...
2. Select the script you want.
3. Click Run.
Python scripts can be run in a number of ways, other than from Utilities>Run Script. See the topic
“Scripting with the Python Programming Language” on page 257 for more information.
To Edit a Script
1. From the menus choose:
File > Open > Script...
2. Select the script you want.
3. Click Open.
The script is opened in the editor associated with the language in which the script is written.
Autoscripts
Autoscripts are scripts that run automatically when triggered by the creation of specic pieces of output
from selected procedures. For example, you can use an autoscript to automatically remove the upper
diagonal and highlight correlation coefcients below a certain signicance whenever a Correlations table
is produced by the Bivariate Correlations procedure.
Autoscripts can be specic to a given procedure and output type or apply to specic output types from
different procedures. For example, you might have an autoscript that formats the ANOVA tables produced
by One-Way ANOVA as well as ANOVA tables produced by other statistical procedures. On the other hand,
Frequencies produces both a frequency table and a table of statistics, and you might choose to have a
different autoscript for each.
Each output type for a given procedure can only be associated with a single autoscript. You can, however,
create a base autoscript that is applied to all new Viewer items prior to the application of any autoscripts
for specic output types. See the topic “Script options” on page 189 for more information.
The Scripts tab in the Options dialog box (accessed from the Edit menu) displays the autoscripts that have
been congured on your system and allows you to set up new autoscripts or modify the settings for
existing ones. Optionally, you can create and congure autoscripts for output items directly from the
Viewer.
Events that Trigger Autoscripts
The following events can trigger autoscripts:
• Creation of a pivot table
• Creation of a Notes object
• Creation of a Warnings object
You can also use a script to trigger an autoscript indirectly. For example, you could write a script that
invokes the Correlations procedure, which in turn triggers an autoscript registered to the resulting
Correlations table.
Creating Autoscripts
You can create an autoscript by starting with the output object that you want to serve as the trigger--for
instance, a frequency table.
1. In the Viewer, select the object that will trigger the autoscript.
2. From the menus choose:
Utilities > Create/Edit AutoScript…
If the selected object does not have an associated autoscript, an Open dialog prompts you for the
location and name of a new script.
3. Browse to the location where the new script will be stored, enter a le name and click Open. The
editor for the default script language opens. You can change the default script language from the
Scripts tab on the Options dialog. See the topic “Script options” on page 189
for more information.
4. Type the code.
For help with converting custom Sax Basic autoscripts used in pre-16.0 versions, see “Compatibility with
Versions Prior to 16.0” on page 259.
Note: By default, the executable associated with the default script language will be used to run the
autoscript. You can change the executable from the Scripts tab in the Options dialog.
If the selected object is already associated with an autoscript, the script is opened in the script editor
associated with the language in which the script is written.
Associating Existing Scripts with Viewer Objects
You can use existing scripts as autoscripts by associating them with a selected object in the Viewer--for
instance, a frequency table.
1. In the Viewer, select an object to associate with an autoscript (multiple Viewer objects can trigger the
same autoscript, but each object can only be associated with a single autoscript).
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2. From the menus choose:
Utilities > Associate AutoScript…
If the selected object does not have an associated autoscript, the Select Autoscript dialog opens.
3. Browse for the script you want and select it.
4. Click Apply.
If the selected object is already associated with an autoscript, you are prompted to verify that you want to
change the association. Clicking OK opens the Select Autoscript dialog.
Optionally, you can congure an existing script as an autoscript from the Scripts tab in the Options dialog
box. The autoscript can be applied to a selected set of output types or specied as the base autoscript
that is applied to all new Viewer items. See the topic “Script options” on page 189 for more information.
Scripting with the Python Programming Language
IBM SPSS Statistics provides two separate interfaces for programming with the Python language on
Windows, Linux, macOS, and for IBM SPSS Statistics Server. Use of these interfaces requires the IBM
SPSS Statistics - Integration Plug-in for Python, which is installed by default with your IBM SPSS Statistics
product. For help getting started with the Python programming language, see the Python tutorial,
available at http://docs.python.org/tut/tut.html .
Python Scripts
Python scripts make use of the interface exposed by the Python SpssClient module. They operate on
user interface and output objects and can also run command syntax. For instance, you would use a
Python script to customize a pivot table.
• Python scripts are run from Utilities>Run Script, from the Python editor launched from IBM SPSS
Statistics (accessed from File>Open>Script), or from an external Python process, such as a Python IDE
or the Python interpreter.
• Python scripts can be run as autoscripts.
• Python scripts run on the machine where the IBM SPSS Statistics client is running.
Complete documentation of the IBM SPSS Statistics classes and methods available for Python scripts can
be found in the Scripting Guide for IBM SPSS Statistics, available under Integration Plug-in for Python in
the Help system.
Python Programs
Python programs make use of the interface exposed by the Python spss module. They operate on the
IBM SPSS Statistics processor and are used to control the flow of a command syntax job, read from and
write to the active dataset, create new datasets, and create custom procedures that generate their own
pivot table output.
• Python programs are run from command syntax within BEGIN PROGRAM-END PROGRAM blocks, or
from an external Python process, such as a Python IDE or the Python interpreter.
• Python programs cannot be run as autoscripts.
• In distributed analysis mode (available with IBM SPSS Statistics Server), Python programs execute on
the computer where IBM SPSS Statistics Server is running.
More information about Python programs, including complete documentation of the IBM SPSS Statistics
functions and classes available for them, can be found in the documentation for the Python Integration
Package for IBM SPSS Statistics, available under Integration Plug-in for Python in the Help system.
Running Python Scripts and Python programs
Both Python scripts and Python programs can be run from within IBM SPSS Statistics or from an external
Python process, such as a Python IDE or the Python interpreter.
Python Scripts
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Python Script Run from IBM SPSS Statistics. You can run a Python script from Utilities>Run Script or
from the Python script editor which is launched when opening a Python le (.py) from File>Open>Script.
Scripts run from the Python editor that is launched from IBM SPSS Statistics operate on the IBM SPSS
Statistics client that launched the editor. This allows you to debug your Python code from a Python editor.
Python Script Run from an External Python Process. You can run a Python script from any external
Python process, such as a Python IDE that is not launched from IBM SPSS Statistics, or the Python
interpreter. The script will attempt to connect to an existing IBM SPSS Statistics client. If more than one
client is found, a connection is made to the most recently launched one. If an existing client is not found,
the Python script starts up a new instance of the IBM SPSS Statistics client. By default, the Data Editor
and Viewer are invisible for the new client. You can choose to make them visible or work in invisible mode
with datasets and output documents.
Python Programs
Python Program Run from Command Syntax. You can run a Python program by embedding Python code
within a BEGIN PROGRAM-END PROGRAM block in command syntax. The command syntax can be run
from the IBM SPSS Statistics client or from the IBM SPSS Statistics Batch Facility--a separate executable
provided with IBM SPSS Statistics Server.
Python Program Run from an External Python Process. You can run a Python program from any
external Python process, such as a Python IDE or the Python interpreter. In this mode, the Python
program starts up a new instance of the IBM SPSS Statistics processor without an associated instance of
the IBM SPSS Statistics client. You can use this mode to debug your Python programs using the Python
IDE of your choice.
Invoking Python Scripts from Python Programs and Vice Versa
Python Script Run from Python Program. You can run a Python script from a Python program by
importing the Python module containing the script and calling the function in the module that implements
the script. You can also call Python script methods directly from within a Python program. These features
are not available when running a Python program from an external Python process or when running a
Python program from the IBM SPSS Statistics Batch Facility (available with IBM SPSS Statistics Server).
Python Autoscript Triggered from Python Program. A Python script specied as an autoscript will be
triggered when a Python program executes the procedure containing the output item associated with the
autoscript. For example, you associate an autoscript with the Descriptive Statistics table generated by the
Descriptives procedure. You then run a Python program that executes the Descriptives procedure. The
Python autoscript will be executed.
Python Program Run from Python Script. Python scripts can run command syntax, which means they
can run command syntax containing Python programs.
Limitations and Warnings
• Running a Python program from the Python editor launched by IBM SPSS Statistics will start up a new
instance of the IBM SPSS Statistics processor and will not interact with the instance of IBM SPSS
Statistics that launched the editor.
• Python programs are not intended to be run from Utilities>Run Script.
• Python programs cannot be run as autoscripts.
• The interfaces exposed by the spss module cannot be used in a Python script.
Script Editor for the Python Programming Language
For the Python programming language, the default editor is IDLE, which is provided with Python. IDLE
provides an integrated development environment (IDE) with a limited set of features. Many IDE's are
available for the Python programming language. For instance, on Windows you might choose to use the
freely available PythonWin IDE.
To change the script editor for the Python programming language:
1. Open the le clientscriptingcfg.ini, located in the directory where IBM SPSS Statistics is installed.
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Note: clientscriptingcfg.ini must be edited with a UTF-16 aware editor, such as SciTE on Windows or
the TextEdit application on Mac.
2. Under the section that is labeled [Python3], change the value of EDITOR_PATH to point to the le
that starts the editor. The specications for Python 3 are independent.
3. In that same section, change the value of EDITOR_ARGS to handle any arguments that need to be
passed to the editor. If no arguments are required, remove any existing values.
Scripting in Basic
Scripting in Basic is available on Windows only and is installed with the Core system. Extensive online
help for scripting in Basic is available from the IBM SPSS Statistics Basic Script Editor. The editor can be
accessed from File>New>Script when the default script language (set from the Scripts tab on the Options
dialog) is set to Basic (the system default on Windows). It is also accessed from File>Open>Script, by
choosing Basic (wwd;sbs) in the Files of type list.
Note: For Windows 7 and higher, accessing the online help for Basic scripting requires the Windows Help
program (WinHlp32.exe), which may not be present on your system. If you cannot view the online help,
then contact Microsoft for instructions on how to obtain the Windows Help program (WinHlp32.exe).
Compatibility with Versions Prior to 16.0
Obsolete Methods and Properties
A number of automation methods and properties are obsolete for version 16.0 and above. In terms of
general features, this includes all objects associated with interactive graphs, the Draft Document object,
and methods and properties associated with maps. For additional information, see "Release Notes for
Version 16.0" in the help system provided with the IBM SPSS Statistics Basic Script Editor. The IBM SPSS
Statistics-specic help is accessed from Help>IBM SPSS Statistics Objects Help, in the script editor.
Global Procedures
Prior to version 16.0, the scripting facility included a global procedures le. For version 16.0 and above
the scripting facility does not use a global procedures le, although the pre-16.0 version of Global.sbs
(renamed Global.wwd) is installed for backwards compatibility.
To migrate a pre-16.0 version of a script that called functions in the global procedures le, add the
statement '#Uses "<install dir>\Samples\Global.wwd" to the declarations section of the
script, where <install dir> is the directory where IBM SPSS Statistics is installed. '#Uses is a special
comment recognized by the Basic script processor. If you're not sure if a script uses the global
procedures le, you should add the '#Uses statement. You can also use '$Include: instead of
'#Uses.
Legacy Autoscripts
Prior to version 16.0, the scripting facility included a single autoscript le containing all autoscripts. For
version 16.0 and above there is no single autoscript le. Each autoscript is now stored in a separate le
and can be applied to one or more output items, in contrast to pre-16.0 versions where each autoscript
was specic to a particular output item.
Some of the autoscripts installed with pre-16.0 versions are available as a set of separate script les
located in the Samples subdirectory of the directory where IBM SPSS Statistics is installed. They are
identied by a lename ending in Autoscript, with a le type of wwd. By default, they are not associated
with any output items. The association is done from the Scripts tab of the Options dialog. See the topic
“Script options” on page 189 for more information.
Any custom autoscripts used in pre-16.0 versions must be manually converted and associated with one
or more output items, from the Scripts tab of the Options dialog. The conversion process involves the
following steps:
1. Extract the subroutine specifying the autoscript from the legacy Autoscript.sbs le and save it as a new
le with an extension of wwd or sbs. The name of the le is arbitrary.
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2. Change the name of the subroutine to Main and remove the parameter specication, keeping track of
which parameters are required by the script, such as a pivot table that triggers the autoscript.
3. Use the scriptContext object (always available) to get the values required by the autoscript, such
as the output item that triggered the autoscript.
4. From the Scripts tab of the Options dialog, associate the script le with the output object.
To illustrate the converted code, consider the autoscript Descriptives_Table_DescriptiveStatistics_Create
from the legacy Autoscript.sbs le.
Sub Descriptives_Table_DescriptiveStatistics_Create _
(objPivotTable As Object,objOutputDoc As Object,lngIndex As Long)
'Autoscript
'Trigger Event: DescriptiveStatistics Table Creation after running
' Descriptives procedure.
'Purpose: Swaps the Rows and Columns in the currently active pivot table.
'Assumptions: Selected Pivot Table is already activated.
'Effects: Swaps the Rows and Columns in the output
'Inputs: Pivot Table, OutputDoc, Item Index
Dim objPivotManager As ISpssPivotMgr
Set objPivotManager=objPivotTable.PivotManager
objPivotManager.TransposeRowsWithColumns
End Sub
Following is the converted script:
Sub Main
'Purpose: Swaps the Rows and Columns in the currently active pivot table.
'Effects: Swaps the Rows and Columns in the output
Dim objOutputItem As ISpssItem
Dim objPivotTable as PivotTable
Set objOutputItem = scriptContext.GetOutputItem()
Set objPivotTable = objOutputItem.ActivateTable
Dim objPivotManager As ISpssPivotMgr
Set objPivotManager = objPivotTable.PivotManager
objPivotManager.TransposeRowsWithColumns
objOutputItem.Deactivate
End Sub
• Notice that nothing in the converted script indicates which object the script is to be applied to. The
association between an output item and an autoscript is set from the Scripts tab of the Options dialog
and maintained across sessions.
• scriptContext.GetOutputItem gets the output item (an ISpssItem object) that triggered the
autoscript.
• The object returned by scriptContext.GetOutputItem is not activated. If your script requires an
activated object, you'll need to activate it, as done in this example with the ActivateTable method.
When you're nished with any table manipulations, call the Deactivate method.
For version 16.0, there is no distinction between scripts that are run as autoscripts and scripts that aren't
run as autoscripts. Any script, appropriately coded, can be used in either context. See the topic “The
scriptContext Object” on page 261 for more information.
Note: To trigger a script from the application creation event, see “Startup Scripts” on page 261.
Script Editor
For version 16.0 and above the script editor for Basic no longer supports the following pre-16.0 features:
• The Script, Analyze, Graph, Utilities, and Add-Ons menus.
• The ability to paste command syntax into a script window.
The IBM SPSS Statistics Basic Script Editor is a standalone application that is launched from within IBM
SPSS Statistics via File>New>Script, File>Open>Script, or Utilities>Create/Edit AutoScript (from a Viewer
window). It allows you to run scripts against the instance of IBM SPSS Statistics from which it was
launched. Once opened, the editor will remain open after exiting IBM SPSS Statistics, but scripts that use
IBM SPSS Statistics objects will no longer run.
File Types
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For version 16.0 and above, the scripting facility will continue to support running and editing scripts with a
le type of sbs. By default, new Basic scripts created with the IBM SPSS Statistics Basic Script Editor have
a le type of wwd.
Using External COM Clients
For version 16.0 and above, the program identier for instantiating IBM SPSS Statistics from an external
COM client is SPSS.Application16. Application objects should be declared as
spsswinLib.Application16. For example:
Dim objSpssApp As spsswinLib.Application16
Set objSpssApp=CreateObject("SPSS.Application16")
To connect to a running instance of the IBM SPSS Statistics client from an external COM client, use:
Dim objSpssApp As spsswinLib.Application16
Set objSpssApp=GetObject("","SPSS.Application16")
If more than one client is running, GetObject will connect to the most recently launched one.
Note: For post-16.0 versions, the identier is still Application16.
The scriptContext Object
Detecting When a Script is Run as an Autoscript
Using the scriptContext object, you can detect when a script is being run as an autoscript. This allows
you to code a script so that it functions in either context (autoscript or not). This trivial script illustrates
the approach.
Sub Main
If scriptContext Is Nothing Then
MsgBox "I'm not an autoscript"
Else
MsgBox "I'm an autoscript"
End If
End Sub
• When a script is not run as an autoscript, the scriptContext object will have a value of Nothing.
• Given the If-Else logic in this example, you would include your autoscript-specic code in the Else
clause. Any code that is not to be run in the context of an autoscript would be included in the If clause.
Of course you can also include code that is to be run in either context.
Getting Values Required by Autoscripts
The scriptContext object provides access to values required by an autoscript, such as the output item
that triggered the current autoscript.
• The scriptContext.GetOutputItem method returns the output item (an ISpssItem object) that
triggered the current autoscript.
• The scriptContext.GetOutputDoc method returns the output document (an ISpssOutputDoc
object) associated with the current autoscript.
• The scriptContext.GetOutputItemIndex method returns the index, in the associated output
document, of the output item that triggered the current autoscript.
Note: The object returned by scriptContext.GetOutputItem is not activated. If your script requires
an activated object, you'll need to activate it--for instance, with the ActivateTable method. When
you're nished with any manipulations, call the Deactivate method.
Startup Scripts
You can create a script that runs at the start of each session and a separate script that runs each time you
switch servers. For Windows you can have versions of these scripts in both Python and Basic. For all other
platforms the scripts can only be in Python.
• The startup script must be named StartClient_.py for Python or StartClient_.wwd for Basic.
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261
• The script that runs when switching servers must be named StartServer_.py for Python or
StartServer_.wwd for Basic.
• The scripts must be located in the scripts directory of the installation directory--located at the root of
the installation directory for Windows and Linux, and under the Contents directory in the application
bundle for Mac. Note that regardless of whether you are working in distributed mode, all scripts
(including the StartServer_ scripts) must reside on the client machine.
• On Windows, if the scripts directory contains both a Python and a Basic version of StartClient_ or
StartServer_ then both versions are executed. The order of execution is the Python version followed by
the Basic version.
• If your system is congured to start up in distributed mode, then at the start of each session any
StartClient_ scripts are run followed by any StartServer_ scripts. Note: The StartServer_ scripts also run
each time you switch servers, but the StartClient_ scripts only run at the start of a session.
Example
This is an example of a StartServer_ script that maps a drive letter to a shared network resource specied
by a UNC identier. This allows users working in distributed mode to access data les on the network
resource from the Open Remote File dialog box.
#StartServer_.py
import SpssClient
SpssClient.StartClient()
SpssClient.RunSyntax(r""" HOST COMMAND=['net use y: \\myserver\data']. """)
SpssClient.StopClient()
The SpssClient.RunSyntax method is used to run a HOST command that calls the Windows net use
command to perform the mapping. When the StartServer_ script runs, IBM SPSS Statistics is in
distributed mode so the HOST command runs on the IBM SPSS Statistics Server machine.
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Chapter 24. TABLES and IGRAPH Command Syntax
Converter
If you have command syntax les that contain TABLES syntax that you want to convert to CTABLES
syntax and/or IGRAPH syntax that you want to convert to GGRAPH syntax, a simple utility program is
provided to help you get started with the conversion process. There are, however, signicant functionality
differences between TABLES and CTABLES and between IGRAPH and GGRAPH. It is likely that you will
nd that the utility program cannot convert some of your TABLES and IGRAPH syntax jobs or may
generate CTABLES and GGRAPH syntax that produces tables and graphs that do not closely resemble the
originals produced by the TABLES and IGRAPH commands. For most tables, you can edit the converted
syntax to produce a table closely resembling the original.
The utility program is designed to:
• Create a new syntax le from an existing syntax le. The original syntax le is not altered.
• Convert only TABLES and IGRAPH commands in the syntax le. Other commands in the le are not
altered.
• Retain the original TABLES and IGRAPH syntax in commented form.
• Identify the beginning and end of each conversion block with comments.
• Identify TABLES and IGRAPH syntax commands that could not be converted.
• Convert command syntax les that follow either interactive or production mode syntax rules.
This utility cannot convert commands that contain errors. The following other limitations also apply.
TABLES Limitations
The utility program may convert TABLES commands incorrectly under some circumstances, including
TABLES commands that contain:
• Parenthesized variable names with the initial letters "sta" or "lab" in the TABLES subcommand if the
variable is parenthesized by itself—for example, var1 by (statvar) by (labvar). These will be
interpreted as the (STATISTICS) and (LABELS) keywords.
• SORT subcommands that use the abbreviations A or D to indicate ascending or descending sort order.
These will be interpreted as variable names.
The utility program cannot convert TABLES commands that contain:
• Syntax errors.
• OBSERVATION subcommands that refer to a range of variables using the TO keyword (for example,
var01 TO var05).
• String literals broken into segments separated by plus signs (for example, TITLE "My" + "Title").
• Macro calls that, in the absence of macro expansion, would be invalid TABLES syntax. Since the
converter does not expand the macro calls, it treats them as if they were simply part of the standard
TABLES syntax.
The utility program will not convert TABLES commands contained in macros. All macros are unaffected by
the conversion process.
IGRAPH Limitations
IGRAPH changed signicantly in release 16. Because of these changes, some subcommands and
keywords in IGRAPH syntax created before that release may not be honored. See the IGRAPH section in
the Command Syntax Reference for the complete revision history.
The conversion utility program may generate additional syntax that it stores in the INLINETEMPLATE
keyword within the GGRAPH syntax. This keyword is created only by the conversion program. Its syntax is
not intended to be user-editable.
Using the Conversion Utility Program
The conversion utility program, SyntaxConverter.exe, can be found in the installation directory. It is
designed to run from a command prompt. The general form of the command is:
syntaxconverter.exe [path]/inputfilename.sps [path]/outputfilename.sps
You must run this command from the installation directory.
If any directory names contain spaces, enclose the entire path and lename in quotation marks, as in:
syntaxconverter.exe /myfiles/oldfile.sps "/new files/newfile.sps"
Interactive versus Production Mode Command Syntax Rules
The conversion utility program can convert command les that use interactive or production mode syntax
rules.
Interactive. The interactive syntax rules are:
• Each command begins on a new line.
• Each command ends with a period (.).
Production mode. The Production Facility and commands in les accessed via the INCLUDE command in
a different command le use production mode syntax rules:
• Each command must begin in the rst column of a new line.
• Continuation lines must be indented at least one space.
• The period at the end of the command is optional.
If your command les use production mode syntax rules and don't contain periods at the end of each
command, you need to include the command line switch -b (or /b) when you run SyntaxConverter.exe, as
in:
syntaxconverter.exe -b /myfiles/oldfile.sps /myfiles/newfile.sps
SyntaxConverter Script (Windows Only)
On Windows, you can also run the syntax converter with the script SyntaxConverter.wwd, located in the
Samples directory of the installation directory.
1. From the menus choose:
Utilities > Run Script...
2. Navigate to the Samples directory and select SyntaxConverter.wwd.
This will open a simple dialog box where you can specify the names and locations of the old and new
command syntax les.
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Chapter 25. Encrypting data les, output documents,
and syntax les
You can protect condential information stored in a data le, an output document, or a syntax le by
encrypting the le with a password. Once encrypted, the le can only be opened by providing the
password. The option to encrypt a le is provided on the Save As dialogs for data les, output documents,
and syntax les. You can also encrypt a data le when sorting it and saving the sorted le.
• Passwords cannot be recovered if they are lost. If the password is lost the le cannot be opened.
• Passwords are limited to 10 characters and are case-sensitive.
Creating strong passwords
• Use eight or more characters.
• Include numbers, symbols and even punctuation in your password.
• Avoid sequences of numbers or characters, such as "123" and "abc", and avoid repetition, such as
"111aaa".
• Do not create passwords that use personal information such as birthdays or nicknames.
• Periodically change the password.
Modifying encrypted les
• If you open an encrypted le, make modications to it and choose File > Save, the modied le will be
saved with the same password.
• You can change the password on an encrypted le by opening the le, repeating the steps for
encrypting it, and specifying a different password in the Encrypt File dialog box.
• You can save an unencrypted version of an encrypted data le or output document by opening the le,
choosing File > Save As and deselecting Encrypt le with password in the associated Save As dialog
box. For an encrypted syntax le, select Syntax from the Save as type drop-down list to save an
unencrypted version of the le.
Note: Encrypted data les and output documents cannot be opened in versions of IBM SPSS Statistics
prior to version 21. Encrypted syntax les cannot be opened in versions prior to version 22.
266 IBM SPSS Statistics 27 Core System User's Guide
Notices
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268
IBM SPSS Statistics 27 Core System User's Guide
Index
A
Access (Microsoft) 15
active le
caching 39
creating a temporary active le 39
virtual active le 39
active window 1
adding group labels 130
aggregating data
aggregate functions 102
variable names and labels 102
algorithms 5
alignment
in Data Editor 50
output 116, 182
alternating row colors
pivot tables 135
aspect ratio 185
attributes
custom variable attributes 51
automated output modication 149, 150, 152–154
automated production 235
automatic output modication 149
automatic recovery 2
Automatic Recovery 179
autoscripts
associating with viewer objects 256
Basic 261
creating 256
trigger events 255
B
background color 137
banding 72
bi-directional text 181
binning 72
Blom estimates 84
BMP
les
exporting charts 120, 125
bookmarks
syntax editor 161
borders
displaying hidden borders 139
break variables
in Aggregate Data 101
breakpoints
syntax editor 160
C
caching
active le 39
captions 137
cases
nding duplicates 71
cases (continued)
nding in Data Editor 57
inserting new cases 56
restructuring into variables 105
selecting subsets 103, 104
sorting 95
weighting 104
categorical data
converting interval data to discrete categories 72
cell properties 137
cells in pivot tables
formats 135
hiding 133
selecting 139
showing 133
widths 139
centered moving average function 91
centering output 116, 182
character encoding 181
Chart Builder
gallery 167
Chart Editor
properties 168
chart options 185
charts
aspect ratio 185
creating from pivot tables 141
exporting 120
hiding 115
missing values 169
overview 167
size 169
templates 169, 185
wrapping panels 169
Cognos
exporting to Cognos TM1 35
reading Cognos Business Intelligence data 19
reading Cognos TM1 data 21
collapsing categories 72
color coding
syntax editor 159
colors in pivot tables
borders 136
column width
controlling default width 187
controlling maximum width 134
controlling width for wrapped text 134
in Data Editor 50
pivot tables 139
columns
changing width in pivot tables 139
selecting in pivot tables 139
COMMA format 47
, 48
comma-delimited les 10
command identiers 245
command language 155
command line switches
Index 269
command line switches (continued)
Production jobs 240
command syntax
accessing Command Syntax Reference 5
adding to menus 193
journal le 164, 165
output log 156
pasting 156
Production jobs rules 235
running 163
running with toolbar buttons 194
syntax rules 155
command syntax editor
auto-completion 159
bookmarks 157, 161
breakpoints 157, 160, 163
color coding 159
command spans 157
commenting or uncommenting text 162
formatting syntax 162
indenting syntax 162
line numbers 157
multiple views/panes 157
options 190
command syntax les 163, 164
comparing datasets 37
compatible custom dialog 200
computing variables
computing new string variables 78
conditional transformations 77
continuation text
for pivot tables 136
controlling number of rows to display 134
copy special 119
copying and pasting output into other applications 119
counting occurrences 79
Crosstabs
fractional weights 104
CSV format
reading data 10
saving data 23
CTABLES
converting TABLES command syntax to CTABLES 263
cumulative sum function 91
currency formats 184
custom attributes 51
custom currency formats 47, 184
Custom Dialog Builder
check box 210
check box group 221
color picker 217
combo box 210
combo box list items 211
compatible custom dialog package (spd) les 229
converting to enhanced dialogs 229
custom dialogs for extension commands 231
data source 202
dataset selector 209
date control 215
dialog properties 202
enabling rules 224
extension bundle les 228
eld chooser 208
eld source 209
Custom Dialog Builder (continued)
le browser 222
le type lter 223
ltering variable lists 209
help le 202
installing compatible custom dialogs 229
installing extensions containing dialogs 228
item group control 220
layout rules 203
list box 212
list box list items 211
localizing dialogs and help les 231
menu location 202
modifying compatible custom dialogs 229
modifying dialogs in installed extensions 228
number control 214
opening compatible custom dialog package les 229
opening extensions containing dialogs 228
preview 205
radio group 220
radio group buttons 221
saving compatible custom dialogs 229
saving extensions containing dialogs 228
secured text 216
source list 206
static text control 217
sub-dialog button 223
sub-dialog properties 224
syntax template 204
tab 223
table control 218
table control columns 218
target list 207
text control 213
Custom Dialog Builder for Extensions 200
custom tables
converting TABLES command syntax to CTABLES 263
custom variable attributes 51
D
data dictionary
applying from another le 68
Data Editor
alignment 50
changing data type 57
column width 50
data value restrictions 55
Data View 45
dening variables 46
descriptive statistics 58
descriptive statistics options 184
display options 59
editing data 55, 56
entering data 54
entering non-numeric data 54
entering numeric data 54
ltered cases 58
inserting new cases 56
inserting new variables 56
moving variables 57
multiple open data les 61, 179
multiple views/panes 59
printing 59
270 IBM SPSS Statistics 27 Core System User's Guide
Data Editor (continued)
roles 50
sending data to other applications 193
Variable View 45
data entry 54
data les
adding comments 175
dictionary information 22
encrypting 28
le information 22
flipping 96
improving performance for large les 39
multiple open data les 61, 179
opening 7
protecting 38
remote servers 43
restructuring 105
saving 23
saving output as IBM SPSS Statistics data les 243
saving subsets of variables 28
text 10
transposing 96
DATA LIST
versus GET DATA command 39
data transformations
computing variables 77
conditional transformations 77
delaying execution 182
functions 78
ranking cases 84
recoding values 80–82
string variables 78
time series 90
data types
changing 57
custom currency 47, 184
dening 47
display formats 48
input formats 48
Data View 45
databases
adding new elds to a table 32
appending records (cases) to a table 33
conditional expressions 17
converting strings to numeric variables 18
creating a new table 33
creating relationships 16
dening variables 18
Microsoft Access 15
parameter queries 17, 18
Prompt for Value 18
random sampling 17
reading 14, 15
replacing a table 33
replacing values in existing elds 32
saving 29
saving queries 19
selecting a data source 15
selecting data elds 15
specifying criteria 17
SQL syntax 19
table joins 16
updating 29
verifying results 19
databases (continued)
Where clause 17
datasets
comparing 37
renaming 62
date format variables
add or subtract from date/time variables 85
create date/time variable from set of variables 85
create date/time variable from string 85
extract part of date/time variable 85
date formats
two-digit years 182
date variables
dening for time series data 90
dBASE les
reading 7, 9
saving 23
default le locations 188
dening variables
applying a data dictionary 68
copying and pasting attributes 50, 51
data types 47
missing values 49
templates 50, 51
value labels 49, 63
variable labels 49
deleting multiple EXECUTES in syntax les 164, 165
deleting output 116
descriptive statistics
Data Editor 58
designated window 1
dialog boxes
dening variable sets 176
displaying variable labels 1, 179
displaying variable names 1, 179
reordering target lists 177
using variable sets 176
variable display order 179
variable icons 2
dictionary 22
difference function 91
disk space
temporary 39
display formats 48
display order 129
distributed mode
available procedures 44
data le access 43
relative paths 44
document recovery 2
DOLLAR format 47, 48
DOT format 47, 48
duplicate cases (records)
nding and ltering 71
E
editing data 55, 56
enhanced custom dialog 200
ensemble viewer
automatic data preparation 147
component model accuracy 146
component model details 147
model summary 146
Index 271
ensemble viewer (continued)
predictor frequency 146
predictor importance 146
entering data
non-numeric 54
numeric 54
using value labels 55
environment variables
SPSSTMPDIR 188
EPS les
exporting charts 120, 125
Excel les
adding menu item to send data to Excel 193
opening 7
reading 8
saving 23
saving value labels instead of values 23
Excel format
exporting output 120, 122, 246
excluding output from Viewer with OMS 248
EXECUTE (command)
pasted from dialog boxes 164, 165
export data 23
exporting
models 144
exporting charts
automated production 235
exporting data
adding menu items to export data 193
exporting output
Excel format 120, 122, 246
HTML 121
HTML format 120
OMS 243
PDF format 120, 123, 246
PowerPoint format 120
text format 246
Word format 120, 122, 246
extension bundles
batch installation 199
creating extension bundles 233
installing extension bundles 197
installing on Statistics Server 199
extension commands
custom dialogs 231
extensions
extension details 197
nding and installing new extensions 196
installing updates to extensions 196
removing extensions 196
viewing installed extensions 196
F
fast pivot tables 187
le information 22
le
locations
controlling default le locations 188
le transformations
aggregating data 101
merging data les 97, 98
restructuring data 105
sorting cases 95
split-le processing 102
le transformations (continued)
transposing variables and cases 96
weighting cases 104
les
adding a text le to the Viewer 117
opening 7
ltered cases
in Data Editor 58
nd and replace
Viewer documents 118
xed format 10
fonts
in Data Editor 59
in the outline pane 117
footers 126
footnotes
charts 169
markers 135
renumbering 138
freeeld format 10
functions
missing value treatment 78
G
GET DATA
versus DATA LIST command 39
versus GET CAPTURE command 39
GGRAPH
converting IGRAPH to GGRAPH 263
grid lines
pivot tables 139
group labels 130
grouping rows or columns 130
grouping variables
creating 105
H
headers 126
Help windows 5
hiding
captions 137
dimension labels 133
footnotes 138
procedure results 115
rows and columns 133
titles 133
toolbars 193
hiding (excluding) output from the Viewer with OMS 248
hiding variables
Data Editor 176
dialog lists 176
HTML
exporting output 120, 121
I
IBM SPSS Data Collection data
saving 34
IBM SPSS Statistics data le format
routing output to a data le 246, 249
icons
272 IBM SPSS Statistics 27 Core System User's Guide
icons (continued)
in dialog boxes 2
IGRAPH
converting IGRAPH to GGRAPH 263
import data 7, 14
imputations
nding in Data Editor 57
inner join 16
input formats 48
inserting group labels 130
interactive output 120
J
journal le 188
JPEG les
exporting charts 120, 125
justication
output 116, 182
K
keyed table 98
L
labels
deleting 130
inserting group labels 130
vs. subtype names in OMS 245
LAG (function) 91
lag function 79
language
changing output language 131
language settings 181
layers
creating 132
displaying 132, 133
in pivot tables 132
printing 126, 134, 136
lead function 79, 91
legacy tables 141
level of measurement
dening 47
line breaks
variable and value labels 49
local encoding 163, 164
logging in to a server 41
Lotus 1-2-3
les
adding menu item to send data to Lotus 193
opening 7
saving 23
M
measurement level
default measurement level 182
dening 47
icons in dialog boxes 2
unknown measurement level 66
measurement system 179
memory 179
menus
menus (continued)
customizing 193
merging data les
dictionary information 98
les with different cases 97
les with different variables 98
renaming variables 98
metales
exporting charts 120
Microsoft Access 15
missing values
charts 169
dening 49
in functions 78
replacing in time series data 92
scoring models 172
string variables 49
model viewer
split models 147
Model Viewer 143
models
activating 143
copying 144
exporting 144
interacting 143
merging model and transformation les 174
Model Viewer 143
models supported for export and scoring 171
printing 144
properties 144
scoring 171
moving rows and columns 129
multiple open data
les
suppressing 62
multiple response sets
dening 67
multiple categories 67
multiple dichotomies 67
multiple views/panes
Data Editor 59
syntax editor 157
N
nominal
measurement level 47, 65
normal scores
in Rank Cases 84
numeric format 47, 48
O
OMS
command identiers 245
controlling table pivots 246, 249
Excel format 246
excluding output from the Viewer 248
IBM SPSS Statistics data le format 246, 249
output object types 244
PDF format 246
SAV le format 246, 249
table subtypes 245
text format 246
Index 273
OMS (continued)
using XSLT with OXML 252
variable names in SAV les 249
Word format 246
XML 246, 250
online Help 5
opening
restore points 2
opening les
controlling default le locations 188
data les 7
dBASE les 7, 9
Excel les 7
Lotus 1-2-3 les 7
spreadsheet les 7
Stata les 9
SYSTAT les 7
tab-delimited les 7
text data les 10
options
charts 185
currency 184
data 182
descriptive statistics in Data Editor 184
general 179
language 181
output labels 184
pivot table look 187
scripts 189
syntax editor 190
temporary directory 188
two-digit years 182
Variable View 184
Viewer 182
ordinal
measurement level 47, 65
outer join 16
outline
changing levels 117
collapsing 116
expanding 116
in Viewer 116
output
alignment 116, 182
centering 116, 182
changing output language 131
closing output items 118
copying 115
deleting 115, 116
encrypting 127
exporting 120
hiding 115
interactive 120
modifying 149, 150, 152–154
moving 115
pasting into other applications 119
saving 127
showing 115
Viewer 115
Output Management System (OMS) 243, 252
output object types
in OMS 244
OXML 252
P
page numbering 127
page setup
chart size 127
headers and footers 126
pane splitter
Data Editor 59
syntax editor 157
pasting output into other applications 119
PDF
exporting output 120, 123
PDF format
exporting output 246
performance
caching data 39
pivot tables
alignment 137
alternating row colors 135
background color 137
borders 136
captions 137
cell formats 135
cell properties 137
cell widths 139
changing display order 129
changing the look 133
continuation text 136
controlling number of rows to display 135
controlling table breaks 140
creating charts from tables 141
default column width adjustment 187
default look for new tables 187
deleting group labels 130
displaying hidden borders 139
editing 129
exporting as HTML 120
fast pivot tables 187
fonts 137
footnote properties 135
footnotes 137–139
general properties 134
grid lines 139
grouping rows or columns 130
hiding 115
inserting group labels 130
inserting rows and columns 131
language 131
layers 132
legacy tables 141
manipulating 129
margins 137
moving rows and columns 129
pasting as tables 119
pasting into other applications 119
pivoting 129
printing large tables 140
printing layers 126
properties 134
render tables faster 187
rotating labels 130
scaling to t page 134, 136
selecting rows and columns 139
showing and hiding cells 133
274
IBM SPSS Statistics 27 Core System User's Guide
pivot tables (continued)
sorting rows 130
transposing rows and columns 130
undoing changes 132
ungrouping rows or columns 130
using icons 129
value labels 131
variable labels 131
pivoting
controlling with OMS for exported output 249
PNG les
exporting charts 120, 125
port numbers 41, 239
portable les
variable names 23
post-processing output 149, 150, 152–154
PostScript les (encapsulated)
exporting charts 120, 125
PowerPoint
exporting output as PowerPoint 123
PowerPoint format
exporting output 120
printing
chart size 127
charts 126
controlling table breaks 140
data 59
headers and footers 126
layers 126, 134, 136
models 144
page numbers 127
pivot tables 126
print preview 126
scaling tables 134, 136
space between output items 127
text output 126
prior moving average function 91
Production Facility
converting les to production jobs 241
using command syntax from journal le 179
Production jobs
command line switches 240
converting Production Facility les 241
exporting charts 235
output les 235
running multiple production jobs 240
scheduling production jobs 240
syntax rules 235
programming with command language 155
properties
pivot tables 134
tables 134
proportion estimates
in Rank Cases 84
Python
scripts 257
R
random number seed 78
random sample
databases 17
random number seed 78
selecting 104
ranking cases
fractional ranks 84
percentiles 84
Savage scores 84
tied values 85
Rankit estimates 84
recoding values 72, 80–82
remote servers
adding 41, 239
available procedures 44
data le access 43
editing 41, 239
logging in 41
relative paths 44
removing group labels 130
renaming datasets 62
reordering rows and columns 129
replacing missing values
linear interpolation 92
linear trend 92
mean of nearby points 92
median of nearby points 92
series mean 92
restore points
opening 2
saving 2
restricted numeric format 47
restructuring data
and weighted data 113
creating a single index variable for variables to cases
110
creating index variables for variables to cases 109
creating multiple index variables for variables to cases
111
example of cases to variables 107
example of one index for variables to cases 109
example of two indices for variables to cases 110
example of variables to cases 107
options for cases to variables 112
options for variables to cases 111
overview 105
selecting data for cases to variables 111
selecting data for variables to cases 108
sorting data for cases to variables 112
types of restructuring 105
variable groups for variables to cases 108
roles
Data Editor 50
rotating labels 130
rows
selecting in pivot tables 139
running median function 91
S
sampling
random sample 104
SAS les
opening 7
reading 7
saving 23
SAV le format
routing output to IBM SPSS Statistics data le 246
routing output to IBM SPSS Statistics data les 249
Index 275
Savage scores 84
saving
restore points 2
saving charts
BMP les 120, 125
EMF les 120
EPS les 120, 125
JPEG les 120, 125
metales 120
PICT les 120
PNG les 125
PostScript les 125
TIFF les 125
saving les
controlling default le locations 188
data les 23
database le queries 19
IBM SPSS Statistics data les 23
saving output
Excel format 120, 122
HTML 120, 121
HTML format 120
PDF format 120, 123
PowerPoint format 120, 123
text format 120, 124
Word format 120, 122
scale
measurement level 47, 65
scale variables
binning to create categorical variables 72
scaling
pivot tables 134, 136
scientic notation
suppressing in output 179
scoring
matching dataset elds to model elds 172
merging model and transformation XML les 174
missing values 172
models supported for export and scoring 171
scoring functions 173
scripts
adding to menus 193
autoscripts 255
Basic 259
creating 255
default language 189, 255
editing 255
languages 255
Python 257
running 255
running with toolbar buttons 194
startup scripts 261
search and replace
Viewer documents 118
seasonal difference function 91
select cases 103
selecting cases
based on selection criteria 104
date range 104
random sample 104
range of cases 104
time range 104
selection methods
selecting rows and columns in pivot tables 139
servers
adding 41, 239
editing 41, 239
logging in 41
names 41, 239
port numbers 41, 239
session journal 188
Shift Values 79
showing
captions 137
dimension labels 133
footnotes 138
results 115
rows or columns 133
titles 133
toolbars 193
sizes
in outline 117
smoothing function 91
sorting
pivot table rows 130
variables 96
sorting cases 95
sorting variables 96
space-delimited data 10
speed
caching data 39
spelling
dictionary 182
split-le processing 102
split-model viewer 147
splitting tables
controlling table breaks 140
spp les
converting to spj les 241
spreadsheet les
reading 9
SPSSTMPDIR environment variable 188
Stata
les
opening 7, 9
reading 7
saving 23
string format 47
string variables
breaking up long strings in earlier releases 23
computing new string variables 78
entering data 54
missing values 49
recoding into consecutive integers 82
style output 150
subsets of cases
random sample 104
selecting 103, 104
subtitles
charts 169
subtypes
vs. labels 245
syntax
accessing Command Syntax Reference 5
journal le 164, 165
output log 156
pasting 156
Production jobs rules 235
running 163
276 IBM SPSS Statistics 27 Core System User's Guide
syntax (continued)
running command syntax with toolbar buttons 194
syntax rules 155
Unicode command syntax les 163, 164
syntax converter 263
syntax editor
auto-completion 159
bookmarks 157, 161
breakpoints 157, 160, 163
color coding 159
command spans 157
commenting or uncommenting text 162
formatting syntax 162
indenting syntax 162
line numbers 157
multiple views/panes 157
options 190
syntax les
encrypting 165
SYSTAT les
opening 7
T
T4253H smoothing 91
tab-delimited
les
opening 7
saving 23
table breaks 140
table chart 141
table subtypes
vs. labels 245
TableLooks
applying 134
creating 134
tables
alignment 137
background color 137
cell properties 137
controlling table breaks 140
converting TABLES command syntax to CTABLES 263
fonts 137
margins 137
TABLES
converting TABLES command syntax to CTABLES 263
target lists 177
templates
charts 169
in charts 185
using an external data le as a template 68
variable denition 50, 51
temporary active le 39
temporary directory
setting location in local mode 188
SPSSTMPDIR environment variable 188
temporary disk space 39
text
adding a text le to the Viewer 117
adding to Viewer 117
data les 10
exporting output as text 120, 124, 246
TIFF les
exporting charts 120, 125
time series data
time series data (continued)
creating new time series variables 90
data transformations 90
dening date variables 90
replacing missing values 92
transformation functions 91
titles
adding to Viewer 117
charts 169
TM1
exporting to Cognos TM1 35
reading Cognos TM1 data 21
toolbars
creating 193, 194
creating new tools 194
customizing 193, 194
displaying in different windows 194
showing and hiding 193
transposing rows and columns 130
transposing variables and cases 96
trigger events
autoscripts 255
Tukey estimates 84
U
Unicode 7, 23, 181
Unicode command syntax les 163, 164
unknown measurement level 66
user-missing values 49
V
value labels
applying to multiple variables 66
copying 66
in Data Editor 59
in merged data les 98
in outline pane 184
in pivot tables 184
inserting line breaks 49
saving in Excel les 23
using for data entry 55
Van der Waerden estimates 84
variable attributes
copying and pasting 50, 51
custom 51
variable information 175
variable labels
in dialog boxes 1, 179
in merged data les 98
in outline pane 184
in pivot tables 184
inserting line breaks 49
variable lists
reordering target lists 177
variable names
generated by OMS 249
in dialog boxes 1, 179
mixed case variable names 46
portable les 23
rules 46
truncating long variable names in earlier releases 23
Index 277
variable names (continued)
wrapping long variable names in output 46
variable pairs
creating 105
variable sets
dening 176
using 176
Variable View
customizing 52, 53, 184
variables
dening 46
dening variable sets 176
denition information 175
display order in dialog boxes 179
nding in Data Editor 57
inserting new variables 56
moving 57
recoding 80–82
renaming for merged data les 98
restructuring into cases 105
sorting 96
vertical label text 130
Viewer
changing outline font 117
changing outline levels 117
changing outline sizes 117
collapsing outline 116
deleting output 116
display options 182
displaying data values 184
displaying value labels 184
displaying variable labels 184
displaying variable names 184
excluding output types with OMS 248
expanding outline 116
nd and replace information 118
hiding results 115
moving output 115
outline 116
outline pane 115
results pane 115
saving document 127
search and replace information 118
space between output items 127
virtual active le 39
Visual Bander 72
W
weighted data
and restructured data les 113
weighting cases
fractional weights in Crosstabs 104
wide tables
pasting into Microsoft Word 119
window splitter
Data Editor 59
syntax editor 157
windows
active window 1
designated window 1
Word format
exporting output 120, 122, 246
wide tables 120
wrapping
controlling column width for wrapped text 134
variable and value labels 49
X
XML
OXML output from OMS 252
routing output to XML 246
saving output as XML 243
table structure in OXML 250
XSLT
using with OXML 252
Y
years
two-digit values 182
Z
z scores
in Rank Cases 84
278 IBM SPSS Statistics 27 Core System User's Guide
IBM®
