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SAS数据分析常用操作指南在当今数据驱动的时代，数据分析成为了企业决策、科学研究等领域的重要手段。
SAS 作为一款功能强大的数据分析软件，被广泛应用于各个行业。
本文将为您介绍 SAS 数据分析中的一些常用操作，帮助您更好地处理和分析数据。
一、数据导入与导出数据是分析的基础，首先要将数据导入到 SAS 中。
SAS 支持多种数据格式的导入，如 CSV、Excel、TXT 等。
以下是常见的导入方法：1、通过｀PROC IMPORT` 过程导入 CSV 文件｀｀｀sasPROC IMPORT DATAFILE=＇your_filecsv'OUT=your_datasetDBMS=CSV REPLACE;RUN;｀｀｀在上述代码中，将｀＇your_filecsv'｀替换为实际的 CSV 文件路径，｀your_dataset` 替换为要创建的数据集名称。
2、从 Excel 文件导入｀｀｀sasPROC IMPORT DATAFILE=＇your_filexlsx'OUT=your_datasetDBMS=XLSX REPLACE;RUN;｀｀｀导出数据同样重要，以便将分析结果分享给他人。
可以使用｀PROC EXPORT` 过程将数据集导出为不同格式，例如：｀｀｀sasPROC EXPORT DATA=your_datasetOUTFILE=＇your_filecsv'DBMS=CSV REPLACE;RUN;｀｀｀二、数据清洗与预处理导入的数据往往存在缺失值、异常值等问题，需要进行清洗和预处理。
1、处理缺失值可以使用｀PROC MEANS` 过程查看数据集中变量的缺失情况，然后根据具体情况选择合适的处理方法，如删除包含缺失值的观测、用均值或中位数填充等。
2、异常值检测通过绘制箱线图或计算统计量（如均值、标准差）来检测异常值。
对于异常值，可以选择删除或进行修正。
3、数据标准化/归一化为了消除不同变量量纲的影响，常常需要对数据进行标准化或归一化处理。
SAS数据导出导入经常导入和导出的数据格式包括：文本文件（txt格式）、纯数据文件（dat格式）、EXCEL文件（xls格式）、ACCESS文件（mdb格式）；程序如下：一、导入导出文本文件（txt格式）、纯数据文件（dat格式）；其实都是导入导出DLM文件（*.*），需要指定分隔符号。
如下（以txt为例，dat同样）：1.TAB分割，第一行为变量名PROC IMPORT OUT= WORK.aDATAFILE= "D:\cha\1.txt"DBMS=TAB REPLACE;GETNAMES=YES;DATAROW=2;RUN;PROC EXPORT DATA= WORK.FILELISTOUTFILE= "D:\filelist.txt"DBMS=TAB REPLACE;RUN;2.SPACE分割，第一行为变量名PROC IMPORT OUT= YANG.WORDDATAFILE= "D:\a\word.txt"DBMS=DLM REPLACE;DELIMITER='20'x;GETNAMES=YES;DATAROW=2;RUN;PROC EXPORT DATA= WORK.AAOUTFILE= "C:\b.txt"DBMS=DLM REPLACE;DELIMITER='20'x;RUN;二、导入导出EXCEL文件（xls格式）程序如下：PROC IMPORT OUT= WORK.ALLWORDDATAFILE= "F:\cc.xls"DBMS=EXCEL REPLACE;SHEET="Sheet1$";GETNAMES=YES;RUN;PROC EXPORT DATA= WORK.AOUTFILE= "D:\export1.xls"DBMS=EXCEL REPLACE;SHEET="nameofsheet";RUN;三、导入导出ACCESS文件（mdb格式）程序如下：PROC IMPORT OUT= WORK.aaDATATABLE= "username"DBMS=ACCESS REPLACE;DATABASE="D:\all\userinfo.mdb";RUN;PROC EXPORT DATA= WORK.AOUTTABLE= "export1"DBMS=ACCESS REPLACE;DATABASE="D:\example.mdb"; *must be an exsited database; RUN;。
SAS批量导入Excel%macro im_excel(/*positional parameters:keep in order*//*.SAS-data-set*/ dsn,/*fileref | "filepath"*/file/*keyword parameters*/,/*DBMS types: EXCEL | EXCELCS | XLS | XLSX */ dbms=excel ,/*replace: (blank) | REPLACE */ replace=replace ,/*range of spreedsheet:(blank) | rangename|sheet|sheet | sheetUR:LR */range=,/*firstobs : N*/ firstobs=1,/*obs: N */ obs=1048576,/*YES|NO */ getnames=yes,/*YES|NO */ scantext=yes,/*YES|NO */ scantime=yes,/*YES|NO */ usedate=yes,/*YES|NO */ mixed=no);proc import out=&dsndatafile=&filedbms=&dbms &replacerange="&range";dbdsopts="firstobs=&firstobs obs=&obs";getnames=&getnamesscantext=&scantextscantime=&scantimeusedate=&usedatemixed=&mixedrun;%mend im_excel;%macro im_1m1excel(RootPath,FileName,Extension); libname MyExcel Excel "&RootPath.\&Filename..&Extension"; proc sql noprint;select catt(trim(libname),'.',quote(trim(memname)),'n') into: namelist seperated by ' 'from dictionary.tableswhere libname in ('MYEXCEL');quit;%put &namelistdata &FileNameset &namelistrun;%mend im_1m1excel;%macro im_m1mexcel(dir=) ; filename indata pipe "dir &dir /b"; data FileName;length fname $20.;infile indata truncover;input fname $20.;dname=scan(fname,1,".");call symputx(cats('File',_n_),fname); call symputx(cats('ds',_n_),dname); call symputx('NumFile',_n_);run;%do i=1 %to &NumFileproc import out=&&ds&idatafile="&Dir\&&file&i"dbms=excel replace;run;%end;%mend;。
sas使用方法范文SAS（Statistical Analysis System）是一种统计分析软件，广泛应用于数据管理和分析。
它提供了一系列功能强大的工具和处理数据的方法。
下面将介绍SAS的使用方法，包括数据导入、数据处理、数据分析和数据可视化等。
1.数据导入：SAS可以导入多种格式的数据文件，如Excel、CSV和文本文件。
使用SAS的数据步骤（data step），可以将数据导入到SAS数据集中。
以下是一个导入Excel文件的示例代码：```data mydata;infile 'path_to_file\myfile.xlsx'dbms=xlsx replace;sheet='sheet1';getnames=yes;run;```2.数据处理：SAS提供了多种数据处理的方法。
例如，通过数据步骤可以对数据进行清洗、转换和整理。
以下是一些常用的数据处理操作：-选择变量：使用KEEP或DROP语句选择需要的变量。
-变量变换：使用COMPUTE语句创建新变量。
-数据过滤：使用WHERE语句根据条件筛选数据。
-数据合并：使用MERGE语句将多个数据集合并在一起。
3.数据分析：SAS提供了丰富的数据分析功能，可以进行统计分析、建模和预测等操作。
以下是一些常用的数据分析方法：-描述统计：使用PROCMEANS、PROCFREQ和PROCSUMMARY等过程进行数据的描述统计分析。
-方差分析：使用PROCANOVA进行方差分析。
-回归分析：使用PROCREG进行线性回归分析。
-聚类分析：使用PROCFASTCLUS进行聚类分析。
-因子分析：使用PROCFACTOR进行因子分析。
-时间序列分析：使用PROCARIMA进行时间序列分析。
4.数据可视化：SAS提供了多种方法用于数据可视化。
通过使用SAS的图形过程（PROCGPLOT和PROCSGPLOT等），可以绘制各种类型的图表，如柱状图、散点图、折线图和饼图等。
SAS数据的导入、导出及树状图的保存
数据的导入及导出
1数据的导入
1.1如图所示选择文件中的导出数据；
1.2点击导出数据后出现以下的对话框，在两个对话框中分别选择SASHELP,和class,然后点击下一步。
1.3点击next后，出现以下窗口，继续点next；
1.4然后出现以下对话框，点击browse
1.5然后选中多元数据文件包
1.6然后命名为数据集1，点击保存；
1.7然后点击保存-OK-finish，即完成了数据集的导出
2数据的导入
2.1选择文件-导入数据即出现以下对话框
2.2点击next-browse选中数据集1进行导入
2.3点击打开-ok-next出现以下对话框，将导入的文件命名为paper，选择finish，
3树状图的保存
3.1点击树状图-单击右键-文件-导出图像
3.2点击导出图像-出现下图-命名为树状图保存即可。
SAS使用技巧范文SAS（统计分析系统）是一种常用于统计分析和数据处理的软件工具。
它具有强大的数据管理和分析功能，可以用于处理大规模数据，进行统计建模和预测。
下面是一些SAS使用的技巧，可以帮助您更高效地使用这个软件。
1.数据导入和导出在SAS中，可以使用“数据步骤”（data step）或“导入向导”（import wizard）将数据导入到SAS系统中。
对于非常大的数据集，可以使用“数据步骤”的输入语句来减少内存的使用。
另外，SAS也支持各种数据格式的导入和导出，如CSV、Excel、SPSS等。
2.数据清洗和转换在进行数据分析之前，通常需要先对数据进行清洗和转换。
SAS提供了一系列的数据转换函数和过程，可以通过数据步骤或SAS语句来处理数据。
比如，可以使用“keep”语句来选择感兴趣的变量，使用“drop”语句来删除不需要的变量，使用“rename”语句来重命名变量。
3.数据合并和拆分有时候需要将多个数据集合并在一起，或将一个数据集拆分成多个部分进行分析。
SAS提供了“merge”和“append”过程来合并数据集，可以根据一个或多个共同变量来进行合并。
另外，可以使用“split”和“sample”过程来将一个数据集拆分成多个部分。
4.数据查询和筛选在进行数据分析时，需要根据一定的条件对数据进行查询和筛选。
SAS提供了类似于SQL的语句来完成这些任务。
可以使用“where”子句来筛选数据，使用“subset”函数来选择一部分数据。
另外，还可以使用“proc sql”过程来执行更复杂的查询操作。
5.数据汇总和计算在进行数据分析时，通常需要对数据进行汇总和计算。
SAS提供了一些过程和函数来完成这些任务。
可以使用“proc means”过程来计算变量的均值、标准差等统计量，使用“proc freq”过程来计算变量的频率分布，使用“proc summary”过程来进行更复杂的汇总操作。
6.数据图形化图形化是数据分析的重要环节，可以帮助我们更好地理解数据和发现规律。
数据分析—SAS数据导入导出鉴于市面上SAS基础知识学习资料较多，在这里不过多介绍。
现分享自己在SAS软件学习和使用过程中总结的相关数据导入导出常见问题，与大家分享。
导入csv、xlsx文件（import语句）PROC IMPORT DATAFILE="E:\xxxxxx\export.csv"out=test;run;a)导入的数据如字段名称为中文可能无法展现字段名称（var1/var2…）解决方法-设置变量名为任意值options validvarname=any;PROC IMPORT DATAFILE="E:\xxxxxx\export.csv"out=test;run;b)编码格式问题导致的导入数据乱码获得SAS编码（其实是通过启动时加载配置文件决定的，nls）启动后无法修改。
如尝试通过下面命令设置，会得到警告。
option encoding='utf-8';日志：因此，在导入导出的时候，我们可以指定导入或导出文件的编码。
比如要导入的csv文件为utf-8编码格式，变量名称为中文，可尝试以下代码options validvarname=any;filename nls " E:\xxxxxx\export.csv"ENCODING="utf-8";PROC IMPORT DATAFILE="E:\xxxxxx\export.csv"out=test;run;对应的utf-8编码文件导出代码为：filename export "E:\xxxxxx\export.csv"ENCODING="utf-8";PROC EXPORT DATA= TEST OUTFILE= exportDBMS=csv REPLACE;RUN;1。
SAS学习总结一、SAS的数据录入（1）直接输入data first;input name $ salary;datalines;a 12b 34c 56d 78;run;注意：datalines的位置以及数据录入后的分号（2）借助infile 可读入文本格式为dat、txt、csvA.最简单的形式data first;infile 'c:\users\lichao\desktop\sas\data\toadjump.dat';input Toadname $ Jump1 Jump2 Jump3 Jump4;run;proc print data=work.first;run;B.有空格的情况，需要数一下data second;infile 'c:\users\lichao\desktop\sas\data\onionring.dat';input Name $ 1-19 Jump1 22-24 Jump2 25-28 Jump3 30-31 Jump4 33-34 Jump5 37 Jump6 40;run;proc print data=work.second;run;C.格式重复的情况data third;infile 'c:\users\lichao\desktop\sas\data\exercise.dat';input Num1 Num2 Num3 @@;run;proc print data=work.third;run;注意：@@的用法D.其他的格式Ⅰ.输出特定的行data icecream;infile 'c:\users\lichao\desktop\sas\data\icecreamsales2.dat' firstobs=3 obs=5;input Flavor $ 1-9 Location Boxessold;run;proc print data=icecream;run;注意：firstobs和obs的位置不要改变，而且两者可以单独使用Ⅱ.有缺失值data class;infile 'c:\users\lichao\desktop\sas\data\allscores.dat' missover;input name $ test1 test2 test3 test4 test5;run;proc print data=class;run;注意：在有缺失值的情况下，如果输出有错误的话就用missoverⅢ.非正常的输入：data third;infile 'c:\users\lichao\desktop\sas\data\pumpkin.dat';input Name $16. num 3. type $2. date $11. (num1 num2 num3 num4 num5) (4.1); run;proc print data=third;run;注意：16. 和3. 、4.1等的表示方法，都是表示宽度，相比较数列数的方法更有效；输入格式相同的话可以加括号把格式写在后面的括号里。
SAS的导⼊、导出excel表格的实现⾸先 SAS 可以使⽤⼿动来导⼊,导出但是这样对于每次操作都需要来⼿动操作,所以就使⽤了 SAS 中的宏来编写代码需求:1. ⾸先是给定excel 的⽂件路径,来⽣成⼀个数据集2. 然后是对数据集中进⾏数据的处理3. 最后是对处理好的数据集导出为⼀个excel 格式的⽂件例⼦:1/* 导⼊excel的数据 */2 %macro import_excel(filepath, out);3 proc import datafile=&filepath out=&out dbms=excel replace;4 run;5 %mend import-excel;67/* 导出excel的数据 */8 %macro export_excel(dataset, filepath);9 proc export data=&dataset file=&filepath dbms=excel replace;10 run;11 %mend export_excel();1213/* 调⽤导⼊宏 */14 %import_excel('C:\Users\ZEK\Desktop\test.xlsx', a);15 run;1617/* 处理数据集 */18 data process;19set a;20if age>14 then desc='已满14岁';21else desc='未满14岁';22 run;2324/* 调⽤导出宏 */25 %export_excel(process, 'C:\Users\ZEK\Desktop\temp.xlsx');26 run;结果:在⽇志窗⼝中会输出这样的⼀个⽇志.注意:在编写代码的时候,最需要注意的是,导⼊和导出的语句是不⼀样的导⼊为:proc import datafile=路径名称out=数据集名称 dbms=excel replace;导出为:proc export data=数据集名称 file=路径名称 dbms=excel replace;千万要注意。
SASSAS DATA Step / Viewtable1.Internal raw data- Datalines or Cards2.External Raw data files- Infile + Input ;SAS DATA Step / PROC IMPORT1.SAS SASdata sasuser.saslin;set "F:\sas1.sas7bdat";run;proc contents data=sasuser.saslin;run;2.SAS PROC IMPORT /proc import datafile = "c:\data\hsb2.sav" out= work.hsb2;run;proc contents data=hsb2;run;SAS SAS recognizes the file type to be imported by file extension.SAS256256Infile LRECL=nListSASList Input12384INPUT Name $ Age Height;ListSAS ColumnColunmEList Column1234INPUT Name $ 1-10 Age 11-13 Height 14-18;$informat w.informat w.dDatew.(1)$CHARw.$HEXw. 16$w.(2)DATEw. ddmmmyy ddmmmyyyyDATETIMEw. ddmmmyy hh:mm:ss.ssDDMMYYw. ddmmyy ddmmyyyyJULIANw. yyddd yyyyddd JuliaMMDDYYw. mmddyy mmddyyyyTIMEw. hh:mm:ss.ss(3)COMMAw.d $HEXw. 16IBw.dPERCENTw.w.dINPUT Name $16. Age 3. +1 Type $1. +1 Date MMDDYY10.(Score1 Score2 Score3 Score4 Score5) (4.1);+n n n@nINPUT ParkName $ 1-22 State $ Year @40 Acreage COMMA9.;BreedMy dog Sam Breed: Rottweiler Vet Bills: $4781SAS RottweilBreed DogBreed2SAS Rottweiler Vet BillBreed: DogBreed203SAS RottweilerBreed:DogBreed 20SASnINPUT City $ State $ / NormalHigh NormalLow #3 RecordHigh RecordLow;Input@@SASINPUT City $ State $ NormalRain MeanDaysRain @@;SASINPUT@SASIFINPUTINPUT Type $ @;INPUT Name $ 9-38 AMTraffic PMTraffic; @ & @@ (1)(2) @SAS@@INFILE1FIRSTOBS=n : n2OBS=n n3INPUTSASINPUTSASMISSOVERTRUNCOVERcolumnTRUNCOVER SASDATAINFILE DLM= DSD1The DLM= optionTab2The DSD optionSASIMPORTIMPORT1234SAS56-set;SASDLM IMPORT DBMS=optionSAS REPLACE-set DBMS=identifier REPLACE;IMPORTIMPORT GETNAMES=NOIMPORTDILIMITER=statementPRO-setDBMS=DLM REPLACE;GETNAMES=NO;-RUN;IMPORT PC-setDBMS=identifier REPLACE;SASPROC CONTENTS DATA=data-set;CONTENTS SAS121.cars_novname.csvAcura,MDX,SUV,Asia,All,"$36,945 ","$33,337 ",3.5,6,265,17,23,4451,106,189 Acura,RSX Type S 2dr,Sedan,Asia,Front,"$23,820 ","$21,761",2,4,200,24,31,2778,101,172Acura,TSX 4dr,Sedan,Asia,Front,"$26,990 ","$24,647 ",2.4,4,200,22,29,3230,105,183 Acura,TL 4dr,Sedan,Asia,Front,"$33,195 ","$30,299 ",3.2,6,270,20,28,3575,108,186 Acura,3.5 RL 4dr,Sedan,Asia,Front,"$43,755 ","$39,014",3.5,6,225,18,24,3880,115,197proc import datafile="cars_novname.csv" out=mydata dbms=csv replace;getnames=no;run;proc contents data=mydata;run;SAS creates default variable names as VAR1-VARn when variables names are not present in the raw data file.2.proc import datafile="cars.txt" out=mydata dbms=tab replace;getnames=no;run;3.libname dis "c:\dissertation";proc import datafile="cars.txt" out=dis.mydata dbms=dlm replace;delimiter='09'x;getnames=yes;run;3.proc import datafile="cars_sp.txt" out=mydata dbms=dlm replace;getnames=no;run;4.Other kinds of delimitersYou can use delimiter= on the infile statement to tell SAS what delimiter you are using to separate variables in your raw data file. For example, below we have a raw data file that uses exclamation points ! to separate the variables in the file.22!2930!409917!3350!474922!2640!379920!3250!481615!4080!7827The example below shows how to read this file by using delimiter='!' on the infile statement.DATA cars;INFILE 'readdel1.txt' DELIMITER='!' ;INPUT mpg weight price;RUN;PROC PRINT DATA=cars;RUN;As you can see in the output below, the data was read properly.OBS MPG WEIGHT PRICE1 22 2930 40992 17 3350 47493 22 2640 37994 20 3250 48165 15 4080 7827It is possible to use multiple delimiters. The example file below uses either exclamation points or plus signs as delimiters.22!2930!409917+3350+474922!2640!379920+3250+481615+4080!7827By using delimiter='!+' on the infile statement, SAS will recognize both of these as valid delimiters.DATA cars;INFILE 'readdel2.txt' DELIMITER='!+' ;INPUT mpg weight price;RUN;PROC PRINT DATA=cars;RUN;As you can see in the output below, the data was read properly.OBS MPG WEIGHT PRICE1 22 2930 40992 17 3350 47493 22 2640 37994 20 3250 48165 15 4080 7827importProc import does not know the formats for your variables, but it is able to guess the format based on what the beginning of your dataset looks like. Most of the time, this guess is fine. But if the length of a variable differs from beginning to end of your file, you might end up with some truncated values.-Infile optionsFor more complicated file layouts, refer to the infile options described below.DLM=The dlm= option can be used to specify the delimiter that separates the variables in your raw data file. For example, dlm=','indicates a comma is the delimiter (e.g., a commaseparated file, .csv file). Or, dlm='09'x indicates that tabs are used to separate your variables (e.g., a tab separated file).DSDThe dsd option has 2 functions. First, it recognizes two consecutive delimiters as a missing value. For example, if your file contained the line 20,30,,50 SAS will treat this as 20 30 50 but with the the dsd option SAS will treat it as 20 30 . 50 , which is probably what you intended. Second, it allows you to include the delimiter within quoted strings. For example, you would want to use the dsd option if you had a comma separated file and your data included values like "George Bush, Jr.". With the dsd option, SAS will recognize that the comma in "George Bush, Jr." is part of the name, and not a separator indicating a new variable.FIRSTOBS=This option tells SAS what on what line you want it to start reading your raw data file. If the first record(s) contains header information such as variable names, then setfirstobs=n where n is the record number where the data actually begin. For example, if you are reading a comma separated file or a tab separated file that has the variable names on the first line, then use firstobs=2 to tell SAS to begin reading at the second line (so it will ignore the first line with the names of the variables).MISSOVERThis option prevents SAS from going to a new input line if it does not find values for all of the variables in the current line of data. For example, you may be reading a space delimited file and that is supposed to have 10 values per line, but one of the line had only 9 values. Without the missover option, SAS will look for the 10th value on the next line of data. If your data is supposed to only have one observation for each line of raw data, then this could cause errors throughout the rest of your data file. If you have araw data file that has one record per line, this option is a prudent method of trying to keep such errors from cascading through the rest of your data file.OBS=Indicates which line in your raw data file should be treated as the last record to be read by SAS. This is a good option to use for testing your program. For example, you might use obs=100 to just read in the first 100 lines of data while you are testing your program. When you want to read the entire file, you can remove the obs= option entirely.A typical infile statement for reading a comma delimited file that contains the variable names in the first line of data would be:INFILE "test.txt" DLM=',' DSD MISSOVER FIRSTOBS=2 ;DATA cars2;length make $ 20 ;INFILE 'readdsd.txt' DELIMITER=',' DSD ;INPUT make mpg weight price;RUN;PROC PRINT DATA=cars2;RUN;48,'Bill Clinton',21050,'George Bush, Jr.',180DATA guys2;length name $ 20 ;INFILE 'readdsd2.txt' DELIMITER=',' DSD ;INPUT age name weight ;RUN;PROC PRINT DATA=guys2;RUN;DATA cars2;length nf 8;INFILE 'F:\cars1.csv' DELIMITER=',' dsd MISSOVER firstobs=2 ;INPUT nf zh hh xb cs IHA fj;RUN;PROC PRINT DATA=cars2;RUN;FTPread raw data via FTP in SAS?SAS has the ability to read raw data directly from FTP servers. Normally, you would use FTP to download the data to your local computer and then use SAS to read the data stored on your local computer. SAS allows you to bypass the FTP step and read the data directly from the other computer via FTP without the intermediate step of downloading the raw data file to your computer. Of course, this assumes that you can reach the computer via the internet at the time you run your SAS program. The program below illustrates how to do this. After the filename in you put ftp to tell SAS to access the data via FTP. After that, you supply the name of the file (in this case 'gpa.txt'. lrecl= is used to specify the width of your data. Be sure to choose a value that is at least as wide as your widest record. cd= is used to specify the directory from where the file is stored. host= is used to specify the name of the site to which you want to FTP. user= is used toprovide your userid (or anonymous if connecting via anonymous FTP). pass= is used to supply your password (or your email address if connecting via anonymous FTP).FILENAME in FTP 'gpa.txt' LRECL=80CD='/local2/samples/sas/ats/'HOST=''USER='joebruin'PASS='yourpassword' ;DATA gpa ;INFILE in ;INPUT gpa hsm hss hse satm satv gender ;RUN;PROC PRINT DATA=gpa(obs=10) ;RUN;quarter1.dat1 120321 1236 154669 2113261 326264 1326 163354 3126651 420698 1327 142336 4226851 211368 1236 156327 6552371 378596 1429 145678 366578quarter2.dat2 140362 1436 114641 3624152 157956 1327 124869 3452152 215547 1472 165578 4125672 204782 1495 150479 3644742 232571 1345 135467 332567quarter3.dat3 140357 1339 142693 2058813 149964 1420 152367 2237953 159852 1479 160001 2548743 139957 1527 163567 2630883 150047 1602 175561 277552quarter4.dat4 479574 1367 155997 361344 496207 1459 140396 359414 501156 1598 135489 396404 532982 1601 143269 386954 563222 1625 147889 39556filename year ('d:\quarter1.dat' 'd:\quarter2.dat' 'd:\quarter3.dat' 'd:\quarter4.dat'); data temp;infile year;input quarter sales tax expenses payroll;run;proc print data = temp;run;excelReading an Excel file into SASSuppose that you have an Excel spreadsheet called auto.xls. The data for this spreadsheet are shown below.MAKE MPG WEIGHT PRICEAMC Concord 22 2930 4099AMC Pacer 17 3350 4749AMC Spirit 22 2640 3799Buick Century 20 3250 4816Buick Electra 15 4080 7827Using the Import Wizard is an easy way to import data into SAS. The Import Wizard can be found on the drop down file menu. Although the Import Wizard is easy it can be time consuming if used repeatedly. The very last screen of the Import Wizard gives you the option to save the statements SAS uses to import the data so that they can be used again. The following is an example that uses common options and also shows that the file was imported correctly.PROC IMPORT OUT= WORK.auto1DATAFILE= "C:\auto.xls"DBMS=EXCEL REPLACE;SHEET="auto1";GETNAMES=YES;MIXED=YES;USEDATE=YES;SCANTIME=YES;RUN;proc print data=auto1;run;Obs MAKE MPG WEIGHT PRICE1 AMC Concord 22 2930 40992 AMC Pacer 17 3350 47493 Amc Spirit 22 2640 37994 Buick Century 20 3250 48165 Buick Electra 15 4080 7827First we use the out= statement to tell SAS where to store the data once they are imported.Next the datafile= statement tells SAS where to find the file we want to import.The dbms= statement is used to identify the type of file being imported. This statement is redundant if the file you want to import already has an appropriate file extension, for example *.xls.The replace statement will overwrite an existing file.To specify which sheet SAS should import use the sheet="sheetname" statement. The default is for SAS to read the first sheet. Note that sheet names can only be 31 characters long.The getnames=yes is the default setting and SAS will automatically use the first row of data as variable names. If the first row of your sheet does not contain variable names use the getnames=no.SAS uses the first eight rows of data to determine whether the variable should be read as character or numeric. The default setting mixed=no assumes that each variable is either all character or all numeric. If you have a variable with both character and numeric values or a variable with missing values use mixed=yes statement to be sure SAS will read it correctly.Conveniently SAS reads date, time and datetime formats. The usedate=yes is the default statement and SAS will read date or time formatted data as a date. When usedate=no SAS will read date and time formatted data with a datetime format. Keep the default statement scantime=yes to read in time formatted data as long as the variable does not also contain a date format.Example 1: Making a permanent data fileWhat if you want the SAS data set created from proc import to be permanent? The answer is to use libname statement. Let's say that we have an Excel file called auto.xls in directory "d:\temp" and we want to convert it into a SAS data file (call it myauto) and put it into the directory "c:\dissertation". Here is what we can do.libname dis "c:\dissertation";proc import datafile="d:\temp\auto.xls" out=dis.myauto replace;run;Example 2: Reading in a specific sheetSometimes you may only want to read a particular sheet from an Excel file instead of the entire Excel file. Let's say that we have a two-sheet Excel file called auto2.xls. The example below shows how to use the option sheet=sheetname to read the second sheet called page2 in it.proc import datafile="auto2.xls" out=auto1 replace;sheet="page2";run;Example 3: Reading a file without variable namesWhat if the variables in your Excel file do not have variable names? The answer here is to use the statement getnames=no in proc import. Here is an example showing how to do this.proc import datafile="a:\faq\auto.xls" out=auto replace;getnames=no;run;Writing Excel files out from SASIt is very easy to write out an Excel file using proc export in SAS version 8. Consider the following sample data file below.Obs MAKE MPG WEIGHT PRICE1 AMC 22 2930 40992 AMC 17 3350 47493 AMC 22 2640 37994 Buick 20 3250 48165 Buick 15 4080 7827Here is a sample program that writes out an Excel file called mydata.xls into the directory "c:\dissertation".proc export data=mydata outfile='c:\dissertation\mydata.xls' replace; run;SAS1.data web;length site $41;input age site $ hits;datalines;12 /default.htm 123456130 /index.htm 97654254 /department/index.htm 987654;proc print;run;Obs site age hits1 /default.htm 12 1234562 /index.htm 130 976543 /department/index.htm 254 987654data web;input age site & $41. hits;datalines;12 /default.htm 123456130 /index.htm 97654254 /department/index.htm 987654;proc print;Obs age site hits1 12 /default.htm 1234562 130 /index.htm 976543 254 /department/index.htm 9876542.data fruit;infile 'C:\messy.txt' delimiter = ' ' dsd;length fruit $22;input zip fruit $ pounds;proc print;run;Obs fruit zip pounds1 apples, grapes kiwi 10034 1234562 oranges 92626 976543 pears apple 25414 987654data fruit;input zip fruit & $22. pounds;datalines;10034 apples, grapes kiwi 12345692626 oranges 9765425414 pears apple 987654;proc print;Obs zip fruit pounds1 10034 apples, grapes kiwi 1234562 92626 oranges 976543 25414 pears apple 987654read a SAS data file when I don't have its format libraryIf you try to use a SAS data file that has permanent formats but you don't have the format library, you will get errors like this.ERROR: The format $MAKEF was not found or could not be loaded.ERROR: The format FORGNF was not found or could not be loaded.Without the format library, SAS will not permit you to do anything with the data file. However, if you use options nofmterr; at the top of your program, SAS will go ahead and process the file despite the fact that it does not have the format library. You will not be able to see the formatted values for your variables, but you will be able to process your data file. Here is an example.OPTIONS nofmterr;libname in "c:\";PROC FREQ DATA=in.auto;TABLES foreign make;RUN;The following program creates exactly the same file, but is a more efficient program because SAS only reads the desired variables.DATA auto2;SET auto (KEEP = make mpg price);RUN;The drop data step option works in a similar way.DATA AUTO2;SET auto (DROP = rep78 hdroom trunk weight length turn displ gratio foreign);RUN;proc compare base = person1 compare = person2 brief; by id;id id;run;。
