Converting SAS datasets to SPSS

If you want to view SAS dataset in SPSS you can use GET SAS command of SPSS.

Here is the syntax;
get sas data='C:\data\class.sas7bdat'.

For conversion of SAS to SPSS we need to see if any formats assigned to variables in the dataset or not.
If there are no formats then we just follow following steps to convert SAS dataset to SPSS.

**STEP1: Creating .xpt file of a SAS dataset using Proc COPY.**

libname SAS 'c:\sas\data\';
libname SPSS xport 'c:\sas\data\class.xpt';

proc copy in=sas out=spss;
select class;
run;


**STEP2: Use SPSS command to convert the transport format SAS file to SPSS;**


You should use following commands to convert transport format file to SPSS data.


get sas data='c:\sas\data\class.xpt'.
execute.

*******************************************************************************************;
If there are formats then we need to convert the formats catalog to a SAS data set before converting the SAS dataset into a .XPT file. This has to be done inside SAS to use the SAS formats as the value labels for SPSS data.

**STEP1: Creating .xpt file of a SAS dataset using Proc COPY.**


libname formats 'c:\sas\catalogs';

proc format library=formats cntlout=fmts;
run;


***Transport file of SAS formats;**


libname fmt2spss xport 'c:\sas\fmts.xpt';


proc copy in=work out=fmt2spss;
select fmts;
run;

***Transport file of SAS dataset.**


libname SAS 'c:\sas\data';
libname SPSS xport 'c:\sas\data\class.xpt';


proc copy in=sas out=spss;
select class;
run;


**STEP3: Use SPSS command to convert the transport format SAS file and Formats to SPSS;**


*Use following SPSS command to convert transport format file to SPSS data;


get sas data='c:\sas\data\class.xpt' /formats='c:\sas\fmts.xpt'.
execute .

('’)

Delete observations from a SAS data set when all or most of variables has missing data

/* Sample data set */
data missing;
input n1 n2 n3 n4 n5 n6 n7 n8 c1 $ c2 $ c3 $ c4 $;
datalines;
1 . 1 . 1 . 1 4 a . c .
1 1 . . 2 . . 5 e . g h
1 . 1 . 3 . . 6 . . k i
1 . . . . . . . . . . .
1 . . . . . . . c . . .
. . . . . . . . . . . .
;
run;

*If you want to delete observation  if the data for every variable is missing then use the following code;

*Approach 1: Using the coalesce option inside the datastep;

data drop_misobs;

set missing;
if missing(coalesce(of _numeric_)) and missing(coalesce(of _character_)) then delete;
run;

 Pros:
*Simple code
Cons;
*This code doesn't work if we want to delete observation based on specific variables and not all of them.

*Approach 2:Using N/NMISS option inside the datastep;

data drop_missing;

set missing;
*Checks the Non missing values using ;

if n(n1, n2, n3, n4, n5, n6, n7, n8, c1, c2, c3, c4)=0 then delete;
run;

data drop_missing;

set missing;
*Checks the missing values using nmiss option;

if nmiss(n1, n2, n3, n4, n5, n6, n7, n8, c1, c2, c3, c4)=12 then delete; *12 is the total number of variables in the dataset missing.;
run;

*If you want to delete records based on few variables and don't want to type all the variable names in the IF-THEN clause use the following code;

*Task: Delete observations from the dataset if all variables in the dataset except (N1 and C1) has missing data;

proc contents data=missing out=contents(keep=memname name);
run;


*Create a macro variable names with list of variable names in the dataset;
proc sql;
select distinct name into:names separated by ','
from contents(where=(upcase(name) ^in ('N1','C1'))) where memname='MISSING'; *Excluding 2 variables in the dataset;
quit;


data remove_missing;
set missing;
if n(&names) lt 1 then delete;
run;

('’)