SPSS Programming and Data Management, 4th Edition: A Guide for ...

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For more information about SPSS ® software products, please visit our Web site at http://www.spss.com or contact:SPSS Inc.233 South Wacker Drive, 11th FloorChicago, IL 60606-6412Tel: (312) 651-3000Fax: (312) 651-3668SPSS is a registered trademark and the other product names are the trademarks of SPSS Inc. for its proprietary computersoftware. No material describing such software may be produced or distributed without the written permission of the owners ofthe trademark and license rights in the software and the copyrights in the published materials.The SOFTWARE and documentation are provided with RESTRICTED RIGHTS. Use, duplication, or disclosure by theGovernment is subject to restrictions as set forth in subdivision (c) (1) (ii) of The Rights in Technical Data and Computer Softwareclause at 52.227-7013. Contractor/manufacturer is SPSS Inc., 233 South Wacker Drive, 11th Floor, Chicago, IL 60606-6412.Patent No. 7,023,453General notice: Other product names mentioned herein are used for identification purposes only and may be trademarks oftheir respective companies.SAS is a registered trademark of SAS Institute Inc.Python is a registered trademark of the Python Software Foundation.Microsoft, Visual Basic, Visual Studio, Office, Access, Excel, Word, PowerPoint, and Windows are either registered trademarksor trademarks of Microsoft Corporation in the United States and/or other countries.DataDirect, DataDirect Connect, INTERSOLV, and SequeLink are registered trademarks of DataDirect Technologies.Portions of this product were created using LEADTOOLS © 1991–2000, LEAD Technologies, Inc. ALL RIGHTS RESERVED.LEAD, LEADTOOLS, and LEADVIEW are registered trademarks of LEAD Technologies, Inc.Portions of this product were based on the work of the FreeType Team (http://www.freetype.org).A portion of the SPSS software contains zlib technology. Copyright © 1995–2002 by Jean-loup Gailly and Mark Adler. The zlibsoftware is provided “as-is,” without express or implied warranty. In no event shall the authors of zlib be held liable for anydamages arising from the use of this software.A portion of the SPSS software contains Sun Java Runtime libraries. Copyright © 2003 by Sun Microsystems, Inc. All rightsreserved. The Sun Java Runtime libraries include code licensed from RSA Security, Inc. Some portions of the libraries arelicensed from IBM and are available at http://oss.software.ibm.com/icu4j/. Sun makes no warranties to the software of any kind.Sax Basic is a trademark of Sax Software Corporation. Copyright © 1993–2004 by Polar Engineering and Consulting. Allrights reserved.SPSS Programming and Data Management, 4th Edition: A Guide for SPSS and SAS UsersCopyright © 2007 by SPSS Inc.All rights reserved.Printed in the United States of America.No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by anymeans—electronic, mechanical, photocopying, recording, or otherwise—without the prior written permission of the publisher.1234567890 10090807ISBN-13: 978-1-56827-390-7ISBN-10: 1-56827-390-8
PrefaceExperienced data analysts know that a successful analysis or meaningful report oftenrequires more work in acquiring, merging, and transforming data than in specifyingthe analysis or report itself. SPSS contains powerful tools for accomplishing andautomating these tasks. While much of this capability is available through thegraphical user interface, many of the most powerful features are available only throughcommand syntax—and you can make the programming features of its command syntaxsignificantly more powerful by adding the ability to combine it with a full-featuredprogramming language. This book offers many examples of the kinds of things thatyou can accomplish using SPSS command syntax by itself and in combination with thePython ® programming language.Using This BookThe contents of this book and the accompanying CD are discussed in Chapter 1. Inparticular, see the section “Using This Book” if you plan to run the examples on the CD.The CD also contains additional command files, macros, and scripts that are mentionedbut not discussed in the book and that can be useful for solving specific problems.This edition has been updated to include numerous enhanced data managementfeatures introduced in SPSS 15.0. Many examples will work with earlier versions, butsome examples rely on features not available prior to SPSS 15.0. Some of the Pythonexamples require SPSS 15.0.1 or later.For SAS UsersIf you have more experience with SAS than with SPSS for data management, seeChapter 22 for comparisons of the different approaches to handling various types ofdata management tasks. Quite often, there is not a simple command-for-commandrelationship between the two programs, although each accomplishes the desired end.iii
Page 1: SPSS Programmingand Data Management
Page 5 and 6: Contents1 Overview 1UsingThisBook..
Page 7 and 8: 4 File Operations 62WorkingwithMult
Page 9 and 10: CreatingVariableswithVECTOR .......
Page 11 and 12: MixingCommandSyntaxandProgramBlocks
Page 13 and 14: 17 Creating Procedures 327GettingSt
Page 15 and 16: TransformingDataValues.............
Page 17: spss.StartSPSSFunction ............
Page 20 and 21: 2Chapter 1• \examples\data contai
Page 22 and 23: Chapter2Best Practices and Efficien
Page 24 and 25: 6Chapter 2Figure 2-1Command syntax
Page 26 and 27: 8Chapter 2Figure 2-2Log with and wi
Page 28 and 29: 10Chapter 2Do Not Overwrite Origina
Page 30 and 31: 12Chapter 2BEGIN DATA1 2 3 4 5END D
Page 32 and 33: 14Chapter 2*create some data.DATA L
Page 34 and 35: 16Chapter 2MISSING VALUES CommandIf
Page 36 and 37: 18Chapter 2• Thesecondtimethedata
Page 38 and 39: 20Chapter 2ExampleYou can create a
Page 40 and 41: GettingDataintoSPSSChapter3Before y
Page 42 and 43: 24Chapter 3• Table joins are not
Page 44 and 45: 26Chapter 3GET DATA /TYPE=ODBC /CON
Page 46 and 47: 28Chapter 3GET DATA /TYPE=ODBC/CONN
Page 48 and 49: 30Chapter 3treating the Excel workb
Page 50 and 51: 32Chapter 3• The original data ty
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34Chapter 3GET DATA/TYPE=ODBC/CONNE
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36Chapter 3applications export text
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38Chapter 3• If all of the variab
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40Chapter 3CSV Delimited Text Files
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42Chapter 3You could define the sam
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44Chapter 3• The first forward sl
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46Chapter 3*wide_file.sps.*Read tex
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48Chapter 3• Although the third c
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50Chapter 3ExampleIn this example,
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52Chapter 3RECORD=6 CASE=student 1-
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54Chapter 3• The value that ident
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56Chapter 3the last value instead o
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58Chapter 3Repeating DataIn a repea
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60Chapter 3*get_sas.sps.GET SAS DAT
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File OperationsChapter4You can comb
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64Chapter 4DATA LIST FREE /file1Var
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66Chapter 4Merging Data FilesYou ca
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68Chapter 4ExampleExpanding the pre
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70Chapter 4DATASET NAME household.D
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72Chapter 4DATASET NAME retail.***s
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74Chapter 4Figure 4-5Cases added in
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76Chapter 4Aggregating DataThe AGGR
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78Chapter 4• As with the previous
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80Chapter 4• The DO IF structure
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82Chapter 4Transposing Cases and Va
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84Chapter 4cases, you may not be ab
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86Chapter 4Figure 4-13Data file aft
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88Chapter 4Figure 4-15Data file aft
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90Chapter 4Figure 4-17Related varia
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92Chapter 5Interview_date "Intervie
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94Chapter 5• User-defined missing
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96Chapter 5VARIABLE LEVELIncome_cat
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98Chapter 5• Attribute names that
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100Chapter 5Figure 5-4File properti
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102Chapter 6• ELSE = COPY retains
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104Chapter 6Figure 6-2Make Cutpoint
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106Chapter 6EXECUTE.• COMPUTE var
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108Chapter 6- COMPUTE Poisson_Distr
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110Chapter 6• The COMPUTE command
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112Chapter 6• For tel2, SUBSTR(#t
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114Chapter 6• COMPUTE #n... then
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116Chapter 6• Months can be repre
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118Chapter 6• Conversion function
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120Chapter 6Example*datediff.sps.DA
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122Chapter 6/StartDateTime (datetim
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124Chapter 7- ELSE IF gender = 1.-
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126Chapter 7Excluding Invalid Data
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128Chapter 7• Although MATCH FILE
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130Chapter 7• COMPUTE filtervar=(
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132Chapter 7Figure 7-5Results from
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134Chapter 8Conditional ProcessingC
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136Chapter 8Missing Values in DO IF
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138Chapter 8• The COMPUTE command
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140Chapter 8DO REPEAT v=var1 TO var
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142Chapter 8***real job starts here
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144Chapter 8*Vector vec no longer e
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146Chapter 8• LOOP IF continues a
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148Chapter 8• The VECTOR command
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150Chapter 8LOOP.- COMPUTE Z=Z+1.EN
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152Chapter 8Figure 8-7Tabular sourc
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154Chapter 8Figure 8-8Different res
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156Chapter 9Using Output as Input w
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158Chapter 9Figure 9-1Default and p
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160Chapter 9Figure 9-3Percentiles a
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162Chapter 9Figure 9-4Variables dim
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164Chapter 9values of the bootstrap
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166Chapter 9• All of the XSLT sty
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168Chapter 9 Page Title
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170Chapter 9Although you can easily
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172Chapter 9CategoryCountPercent
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174Chapter 9Figure 9-11XPath expres
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176Chapter 9Figure 9-13Main templat
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178Chapter 9• calls another temp
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180Chapter 9Figure 9-15Rounding cel
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182Chapter 9Exporting Data to Other
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184Chapter 9SPSS Variable Type Stat
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186Chapter 9• You can use APPEND
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188Chapter 9• The TABLE subcomman
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190Chapter 9• OUTPUT NEW creates
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192Chapter 10Scoring is available o
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194Chapter 10*Get data to be scored
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196Chapter 10You have the option of
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198Chapter 10file in PMML format—
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200Chapter 10EEEESelect Response fo
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202Chapter 10EEESelect Response for
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204Chapter 10EEEEReplace 'file spec
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206Chapter 10value of 1 means that
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208Chapter 10Running Your Scoring J
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IntroductionChapter11The SPSS-Pytho
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212Chapter 11creating and debugging
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214Chapter 12Within a program block
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216Chapter 12The functions in the s
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218Chapter 12• spss.GetVariableMe
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220Chapter 12• In order to retrie
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222Chapter 12"Joe's Bar and Grille"
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224Chapter 12Passing Values from a
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226Chapter 12ExampleSuppose you nee
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228Chapter 12Figure 12-3Output from
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230Chapter 12Example: Simple Messag
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232Chapter 12Figure 12-5Simple file
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234Chapter 12Figure 12-6Simple mult
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236Chapter 12Getting HelpHelp with
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238Chapter 13• Notice that the tr
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240Chapter 13• First, loop throug
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242Chapter 13Displaying Command Syn
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244Chapter 13ExampleLet’s say you
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246Chapter 13• The function GetSP
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248Chapter 13Raising an Exception t
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250Chapter 13• The Submit functio
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252Chapter 13Another feature of run
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Chapter14Working with Variable Dict
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256Chapter 14Summarizing Variables
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258Chapter 14• varList is created
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260Chapter 14in the if statement wi
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262Chapter 14• For variables with
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264Chapter 14A Python list of varia
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266Chapter 14For the dataset and in
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268Chapter 14EvaluateXPath function
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270Chapter 14the parseString functi
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272Chapter 14ExampleThe sample data
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274Chapter 14• Notice that the st
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276Chapter 15Reading Case Data with
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278Chapter 15*python_get_cases_sequ
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280Chapter 15DATA LIST LIST (',') /
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282Chapter 15Creating New SPSS Vari
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284Chapter 15• To set case values
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286Chapter 15Example: Reducing a St
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288Chapter 15*python_reformat_strin
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290Chapter 15• Thecodemakesuseoft
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292Chapter 15the Spssdata class, yo
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294Chapter 15a for loop. The Spssda
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296Chapter 15*python_check_missing.
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298Chapter 15*python_Spssdata_split
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300Chapter 15• The Spssdata class
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302Chapter 15• Once specification
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304Chapter 15ThePythondatatypeNone
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306Chapter 15Appending New Cases wi
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308Chapter 15• Case values for ea
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310Chapter 15• spssdata.Spssdata(
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312Chapter 15rating formula makes u
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Retrieving Output from SPSSCommands
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316Chapter 16Note: Thespssaux modul
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318Chapter 16*python_write_workspac
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320Chapter 16As an aid to understan
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322Chapter 16two-tuple whose first
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324Chapter 16subtype identifier for
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326Chapter 16• Using /FORMAT=DFRE
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328Chapter 17full computational pow
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330Chapter 17text file containing P
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332Chapter 17As a further alternati
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334Chapter 17• The StartProcedure
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336Chapter 17Figure 17-4Pivot table
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338Chapter 17• The firstargumentt
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340Chapter 17Treating Categories or
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342Chapter 17• The row categories
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Data TransformationsChapter18The Py
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346Chapter 18The inputs must be com
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348Chapter 18*python_trans_ismissin
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350Chapter 18with the trans Module
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352Chapter 18Figure 18-3Resulting d
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354Chapter 18• The replacement st
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356Chapter 18be substituted for the
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358Chapter 18Example*python_extende
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360Chapter 18help(extendedTransform
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362Chapter 18• The Python variabl
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364Chapter 19If you use the PythonW
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366Chapter 19to call GetDesignatedO
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368Chapter 19string passed in as th
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370Chapter 19in the designated View
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372Chapter 20Youconvertablockofcomm
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374Chapter 20*python_converted_synt
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376Chapter 20SET MPRINT=OFF.DEFINE
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378Chapter 20• Notice that the co
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380Chapter 20To facilitate using OL
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382Chapter 20We’ll assume that yo
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384Chapter 20Setting the value of s
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Special TopicsChapter21Using Regula
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388Chapter 21• The OpenDataFile f
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390Chapter 21Locale IssuesFor users
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SPSS for SAS ProgrammersChapter22Re
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394Chapter 22proc sql;connect to od
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396Chapter 22assigns it a numeric d
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398Chapter 22Merging Files with the
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400Chapter 22• In the SPSS code,
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402Chapter 22Variable LabelsBoth SP
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404Chapter 22Cleaning and Validatin
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406Chapter 22• END IF in SPSS is
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408Chapter 22proc format;value opfm
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410Chapter 22• As in the recoding
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412Chapter 22• Both languages all
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414Chapter 22run;• SPSS uses subs
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416Chapter 22EXECUTE.data new;forma
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418Chapter 22Creating Custom Functi
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420Chapter 22BEGIN PROGRAM.import s
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422Chapter 22• The SetMacroValue
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Python Functions and ClassesAppendi
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426Appendix A• The argument templ
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428Appendix AResultFigure A-2Simple
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430Appendix AFigure A-3Resulting ta
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432Appendix A• The firstargumentt
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434Appendix A• Cell values must b
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436Appendix Acol_cat2 = CellText.St
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438Appendix AExamples of using the
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440Appendix Aposition within the di
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442Appendix ASetCell Method.SetCell
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444Appendix Atable.SetCategories(ro
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446Appendix Aof Count, which displa
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448Appendix Aas there are elements
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450Appendix AResultFigure A-13Table
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452Appendix AFormat nameCodePercent
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454Appendix AIn this example, row c
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456Appendix Aspss.BaseProcedure Cla
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458Appendix A• The procedure defi
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460Appendix AExamplehandle='demo'sp
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462Appendix A3,,4,dEND DATA.MISSING
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464Appendix A• The SetValueNumeri
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466Appendix A• Changes to the act
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468Appendix AMethod Read mode Write
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470Appendix A• When appending cas
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472Appendix A• Cases from the act
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474Appendix A• String values are
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476Appendix A• The value returned
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478Appendix A• This method is onl
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480Appendix ASetValueChar Method.Se
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482Appendix Acur.close()SetVarAttri
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484Appendix AFormat TypesTypeDescri
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486Appendix ASetVarNameAndType Meth
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488Appendix ASetVarNValueLabel Meth
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490Appendix ANote: In the SPSS docu
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492Appendix A• For other function
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494Appendix AExample#Create a list
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496Appendix A• MOYR. Month and ye
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498Appendix Aspss.GetVariableName F
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500Appendix AExampleimport spssweig
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502Appendix Aspss.SetDefaultPlugInV
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504Appendix AExampleIn this example
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506Appendix Ain the same table. Not
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508Appendix Adef groupMeans(groupVa
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510Appendix AResultFigure A-15Outpu
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512Appendix A• You can also use t
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514Appendix Aappend Method.append(l
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516Indexconcatenating string values
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518IndexIDEusing a Python IDE to dr
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520Indexraw strings, 220, 237, 241r
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522IndexUPCASE (function), 109UPDAT
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