topic Re: Compute with If Condition in SAS Programming

Compute with If Condition

DavidPhillips2 — Fri, 18 Mar 2016 15:00:02 GMT

Is there a way to do:

compute after gender but not after age / style={background=blue};

line ' ';

endcomp;

Re: Compute with If Condition

RW9 — Fri, 18 Mar 2016 15:18:02 GMT

Well, there maybe in report, but I prefer pre-arranging data in a datastep, som my suggestion would be to add a break var into your dataset, i.e. its always 0, except when you line, then break on that.

Re: Compute with If Condition

data_null__ — Fri, 18 Mar 2016 15:56:32 GMT

I don't quite understand your example. If you want a conditional line statement use $VARYING format as in the sample.

http://support.sas.com/kb/37/763.html

Re: Compute with If Condition

DavidPhillips2 — Fri, 18 Mar 2016 16:17:33 GMT

See screen shot. What I’m trying to do is only produce one line when the blue line is created rather than both the blue line and the light blue line.

compute after gender / style={background=blue};
line ' ';
endcomp;

compute after age / style={background=lightblue};
line ' ';
endcomp;

Re: Compute with If Condition

Cynthia_sas — Fri, 18 Mar 2016 18:15:04 GMT

Which line do you want between Female and Male??? The light blue line or the dark blue line?

The technique described (to use $varying. is the correct technique to suppress a line statement. You CANNOT execute a LINE statement conditionally, but you can conditionally assign a value to a "helper" variable that specifies the length of the line. When the length of the line is 0, then PROC REPORT will suppress the line.

Please see this Tech Support note: http://support.sas.com/kb/37/763.html which outlines the basic technique (illustrated with writing out text). And this paper http://support.sas.com/resources/papers/proceedings11/246-2011.pdf has more examples and explanation on pages 12 and 13.

cynthia

Re: Compute with If Condition

DavidPhillips2 — Fri, 18 Mar 2016 18:32:15 GMT

I want the last light blue line to not appear. Currently playing with

if residency_desc = "Total" then do;

call define(_col_, 'style', 'style=[background=lightblue]');

line ' ';

end;

else do;

call define(_col_, 'style', 'style=[background=blue]');

line ' ';

end;

But this produces two blank lines.

Re: Compute with If Condition

data_null__ — Fri, 18 Mar 2016 20:12:38 GMT

This might be helpful but seems a bit clunky.

proc sort  data=sashelp.class out=class;	
	by sex age;
   run;
data report;
   set class;
   by sex age;
   lastsex = last.sex;
   lastage = last.age;
   run;
proc report nowd data=report list out=test;
   columns sex lastsex age lastage name height weight;
   define sex / order;
   define age / order;
   define lastsex / order noprint;
   define lastage / order noprint;
   define name / display;
   define height / display;
   define weight / display;
   compute after lastage / style={background=lightblue};
      x = ' ';
      if lastsex eq 1 then lastage=0;
      line x $varying1. lastage;
      endcomp; 
	compute after sex / style={background=blue};		
		line ' ';
		endcomp;
	run;

Re: Compute with If Condition

DavidPhillips2 — Mon, 21 Mar 2016 17:19:41 GMT

if lastsex eq 1 then lastage=0;
      line x $varying1. lastage;

Could you explain what these two lines do? They seem to matter why is lastage being set to 0?

Re: Compute with If Condition

data_null__ — Mon, 21 Mar 2016 21:29:44 GMT

@DavidPhillips2 wrote:
if lastsex eq 1 then lastage=0;
      line x $varying1. lastage;
Could you explain what these two lines do? They seem to matter why is lastage being set to 0?

Lastage is both the indicator of last obs for an age group and used as the length for X in $VARYING. When LASTAGE is 0 it keeps the compute from printing a light blue line. Otherwise there would be a line between each row. When it is LASTSEX it is also LASTAGE but we want to suppress the printing of that line so set it (LASTAGE) to 0 and $VARYING prints nothing.

Re: Compute with If Condition

DavidPhillips2 — Tue, 22 Mar 2016 15:02:58 GMT

When I run this with my dataset and a third column I run into:

NOTE: Variable lastsex is uninitialized.ERROR: An unknown, abnormal error has occurred. This step is being terminated.

It’s hard to replicate my scenario via a post. Working on a simplification so I can post code and data.

This block is causing the error for me.

  compute after lastage / style={background=lightblue};
      x = ' ';
      if lastsex eq 1 then lastage=0;
      line x $varying1. lastage;
      endcomp;

Re: Compute with If Condition

data_null__ — Tue, 22 Mar 2016 15:32:10 GMT

@DavidPhillips2 wrote:

When I run this with my dataset and a third column I run into:

NOTE: Variable lastsex is uninitialized.ERROR: An unknown, abnormal error has occurred. This step is being terminated.

It’s hard to replicate my scenario via a post. Working on a simplification so I can post code and data.

This block is causing the error for me.
  compute after lastage / style={background=lightblue};
      x = ' ';
      if lastsex eq 1 then lastage=0;
      line x $varying1. lastage;
      endcomp; 

You need to create "last" indicator variables for your data as I did in this step. They also go in the column statement.

data report;
   set class;
   by sex age;
   lastsex = last.sex;
   lastage = last.age;
   run;

Re: Compute with If Condition

DavidPhillips2 — Tue, 22 Mar 2016 16:34:58 GMT

This is a bit simplified. Still simplifying and working on getting data for the post.

proc sort data=all;

by gender residency eth;

run;

data all; set all;

by gender residency eth;

lastGender = last.gender;

lastResidency = last.residency;

lastEth = last.eth;

run;

proc report data=all;

column (gender residency eth growthDeclineColumn perGrowthDeclineColumn lastGender lastResidency lastEth academic_period_desc , n);

define gender / group '' order=data;

define residency / group '' order=data;

define eth / group '' order=internal;

define lastEth / order=data;

define lastResidency / order=data;

define lastGender / order=data;

define growthDeclineColumn / group noprint '' order = data;

define perGrowthDeclineColumn / group noprint '' order = data;

define academic_period_desc / across ''

define n / analysis sum '' &tabulateFormatClause;

compute eth;

if eth=99 then call define(_row_,'style','style={font_weight=bold}');

endcomp;

compute n;

if growthDeclineColumn = 1 then call &shortFormat;

if perGrowthDeclineColumn = 1 then call define(_col_,'format','percent8.2');

endcomp;

compute after residency / style=[background=blue];

x = ' ';

if lastGender eq 1 then lastResidency =0;

line x $varying1. lastResidency;

endcomp;

Re: Compute with If Condition

DavidPhillips2 — Tue, 22 Mar 2016 17:40:12 GMT

if lastReport1 eq 1 or lastReport1 eq . then lastReport2 =0;

makes the proc report show without coloring. Oddly proc print of dataset all displays lastReport1 with values. I wonder if this has to do with the after statements.

Re: Compute with If Condition

data_null__ — Tue, 22 Mar 2016 18:39:06 GMT

You need to move the LAST indicator variables to the LEFT in the column statement. Notice in my example they are not at the end.

Re: Compute with If Condition

DavidPhillips2 — Tue, 22 Mar 2016 18:54:55 GMT

After moving them to the left the same error occurs.

Re: Compute with If Condition

data_null__ — Tue, 22 Mar 2016 19:30:07 GMT

Why are you using order=data?

Without a working example (like the one I wrote for you) I cannot help you debug your program. Working means includes DATA.

Re: Compute with If Condition

DavidPhillips2 — Wed, 23 Mar 2016 13:59:29 GMT

data all;
infile datalines DLM=',';
input GENDER $ residency_desc : $20. schev_ethnicity_desc $ ACADEMIC_PERIOD_DESC : $20. n
growthDeclineColumn perGrowthDeclineColumn lastGender lastResidency_desc lastSchev_ethnicity_desc ;
datalines;
Female,In-state,1,Fall 2015,1,0,0,0,0,1
Female,In-state,2,Fall 2015,47,0,0,0,0,1
Female,In-state,3,Fall 2015,18,0,0,0,0,1
Female,In-state,5,Fall 2015,20,0,0,0,0,1
Female,In-state,6,Fall 2015,30,0,0,0,0,1
Female,In-state,8,Fall 2015,230,0,0,0,0,1
Female,In-state,9,Fall 2015,3,0,0,0,0,1
Female,In-state,10,Fall 2015,6,0,0,0,0,1
Female,In-state,99,Fall 2015,355,0,0,0,1,1
Female,Out-of-state,2,Fall 2015,21,0,0,0,0,1
Female,Out-of-state,3,Fall 2015,13,0,0,0,0,1
Female,Out-of-state,5,Fall 2015,6,0,0,0,0,1
Female,Out-of-state,6,Fall 2015,11,0,0,0,0,1
Female,Out-of-state,8,Fall 2015,72,0,0,0,0,1
Female,Out-of-state,9,Fall 2015,10,0,0,0,0,1
Female,Out-of-state,99,Fall 2015,133,0,0,0,1,1
Female,Total,1,Fall 2015,1,0,0,0,0,1
Female,Total,2,Fall 2015,68,0,0,0,0,1
Female,Total,3,Fall 2015,31,0,0,0,0,1
Female,Total,5,Fall 2015,26,0,0,0,0,1
Female,Total,6,Fall 2015,41,0,0,0,0,1
Female,Total,8,Fall 2015,302,0,0,0,0,1
Female,Total,9,Fall 2015,13,0,0,0,0,1
Female,Total,10,Fall 2015,6,0,0,0,0,1
Female,Total,99,Fall 2015,488,0,0,0,0,0
Female,Total,99,Fall 2015,488,0,0,1,1,1
Male,In-state,1,Fall 2015,1,0,0,0,0,1
Male,In-state,2,Fall 2015,23,0,0,0,0,1
Male,In-state,3,Fall 2015,10,0,0,0,0,1
Male,In-state,5,Fall 2015,6,0,0,0,0,1
Male,In-state,6,Fall 2015,14,0,0,0,0,1
Male,In-state,8,Fall 2015,87,0,0,0,0,1
Male,In-state,9,Fall 2015,1,0,0,0,0,1
Male,In-state,10,Fall 2015,3,0,0,0,0,1
Male,In-state,99,Fall 2015,145,0,0,0,1,1
Male,Out-of-state,2,Fall 2015,4,0,0,0,0,1
Male,Out-of-state,3,Fall 2015,2,0,0,0,0,1
Male,Out-of-state,5,Fall 2015,1,0,0,0,0,1
Male,Out-of-state,6,Fall 2015,2,0,0,0,0,1
Male,Out-of-state,8,Fall 2015,16,0,0,0,0,1
Male,Out-of-state,9,Fall 2015,3,0,0,0,0,1
Male,Out-of-state,99,Fall 2015,28,0,0,0,1,1
Male,Total,1,Fall 2015,1,0,0,0,0,1
Male,Total,2,Fall 2015,27,0,0,0,0,1
Male,Total,3,Fall 2015,12,0,0,0,0,1
Male,Total,5,Fall 2015,7,0,0,0,0,1
Male,Total,6,Fall 2015,16,0,0,0,0,1
Male,Total,8,Fall 2015,103,0,0,0,0,1
Male,Total,9,Fall 2015,4,0,0,0,0,1
Male,Total,10,Fall 2015,3,0,0,0,0,1
Male,Total,99,Fall 2015,173,0,0,0,0,0
Male,Total,99,Fall 2015,173,0,0,1,1,1
Total,In-state,1,Fall 2015,2,0,0,0,0,1
Total,In-state,2,Fall 2015,70,0,0,0,0,1
Total,In-state,3,Fall 2015,28,0,0,0,0,1
Total,In-state,5,Fall 2015,26,0,0,0,0,1
Total,In-state,6,Fall 2015,44,0,0,0,0,1
Total,In-state,8,Fall 2015,317,0,0,0,0,1
Total,In-state,9,Fall 2015,4,0,0,0,0,1
Total,In-state,10,Fall 2015,9,0,0,0,0,1
Total,In-state,99,Fall 2015,500,0,0,0,1,1
Total,Out-of-state,2,Fall 2015,25,0,0,0,0,1
Total,Out-of-state,3,Fall 2015,15,0,0,0,0,1
Total,Out-of-state,5,Fall 2015,7,0,0,0,0,1
Total,Out-of-state,6,Fall 2015,13,0,0,0,0,1
Total,Out-of-state,8,Fall 2015,88,0,0,0,0,1
Total,Out-of-state,9,Fall 2015,13,0,0,0,0,1
Total,Out-of-state,99,Fall 2015,161,0,0,0,1,1
Total,Total,1,Fall 2015,2,0,0,0,0,1
Total,Total,2,Fall 2015,95,0,0,0,0,1
Total,Total,3,Fall 2015,43,0,0,0,0,1
Total,Total,5,Fall 2015,33,0,0,0,0,1
Total,Total,6,Fall 2015,57,0,0,0,0,1
Total,Total,8,Fall 2015,405,0,0,0,0,1
Total,Total,9,Fall 2015,17,0,0,0,0,1
Total,Total,10,Fall 2015,9,0,0,0,0,1
Total,Total,99,Fall 2015,661,0,0,0,0,0
Total,Total,99,Fall 2015,661,0,0,1,1,1
;

proc report data=all;

column (lastGender lastResidency_desc lastSchev_ethnicity_desc gender residency_desc schev_ethnicity_desc academic_period_desc, n);

define gender / group '' order=data;
define residency_desc / group '' order=data;
define schev_ethnicity_desc / group '' order=internal;

define lastGender / order=internal;
define lastResidency_desc / order=internal;
define lastSchev_ethnicity_desc / order=internal;

define academic_period_desc / across '';
define n / analysis sum '';

/*compute after residency_desc / style=[background=blue];
x = ' ';
if lastGender eq 1 then lastResidency_desc =0;
line x $varying1. lastResidency_desc;
endcomp; */

run;

Re: Compute with If Condition

data_null__ — Wed, 23 Mar 2016 14:41:30 GMT

I changed the data type on SCHEV_ETHNICITY_DESC I don't think this can work with order=data. I don't understand the extra rows of total 99. I think it's close.

data all;
infile datalines DLM=',';
input GENDER $ residency_desc : $20. schev_ethnicity_desc ACADEMIC_PERIOD_DESC : $20. n
growthDeclineColumn perGrowthDeclineColumn lastGender lastResidency_desc lastSchev_ethnicity_desc ;
datalines;
Female,In-state,1,Fall 2015,1,0,0,0,0,1
Female,In-state,2,Fall 2015,47,0,0,0,0,1
Female,In-state,3,Fall 2015,18,0,0,0,0,1
Female,In-state,5,Fall 2015,20,0,0,0,0,1
Female,In-state,6,Fall 2015,30,0,0,0,0,1
Female,In-state,8,Fall 2015,230,0,0,0,0,1
Female,In-state,9,Fall 2015,3,0,0,0,0,1
Female,In-state,10,Fall 2015,6,0,0,0,0,1
Female,In-state,99,Fall 2015,355,0,0,0,1,1
Female,Out-of-state,2,Fall 2015,21,0,0,0,0,1
Female,Out-of-state,3,Fall 2015,13,0,0,0,0,1
Female,Out-of-state,5,Fall 2015,6,0,0,0,0,1
Female,Out-of-state,6,Fall 2015,11,0,0,0,0,1
Female,Out-of-state,8,Fall 2015,72,0,0,0,0,1
Female,Out-of-state,9,Fall 2015,10,0,0,0,0,1
Female,Out-of-state,99,Fall 2015,133,0,0,0,1,1
Female,Total,1,Fall 2015,1,0,0,0,0,1
Female,Total,2,Fall 2015,68,0,0,0,0,1
Female,Total,3,Fall 2015,31,0,0,0,0,1
Female,Total,5,Fall 2015,26,0,0,0,0,1
Female,Total,6,Fall 2015,41,0,0,0,0,1
Female,Total,8,Fall 2015,302,0,0,0,0,1
Female,Total,9,Fall 2015,13,0,0,0,0,1
Female,Total,10,Fall 2015,6,0,0,0,0,1
Female,Total,99,Fall 2015,488,0,0,0,0,0
Female,Total,99,Fall 2015,488,0,0,1,1,1
Male,In-state,1,Fall 2015,1,0,0,0,0,1
Male,In-state,2,Fall 2015,23,0,0,0,0,1
Male,In-state,3,Fall 2015,10,0,0,0,0,1
Male,In-state,5,Fall 2015,6,0,0,0,0,1
Male,In-state,6,Fall 2015,14,0,0,0,0,1
Male,In-state,8,Fall 2015,87,0,0,0,0,1
Male,In-state,9,Fall 2015,1,0,0,0,0,1
Male,In-state,10,Fall 2015,3,0,0,0,0,1
Male,In-state,99,Fall 2015,145,0,0,0,1,1
Male,Out-of-state,2,Fall 2015,4,0,0,0,0,1
Male,Out-of-state,3,Fall 2015,2,0,0,0,0,1
Male,Out-of-state,5,Fall 2015,1,0,0,0,0,1
Male,Out-of-state,6,Fall 2015,2,0,0,0,0,1
Male,Out-of-state,8,Fall 2015,16,0,0,0,0,1
Male,Out-of-state,9,Fall 2015,3,0,0,0,0,1
Male,Out-of-state,99,Fall 2015,28,0,0,0,1,1
Male,Total,1,Fall 2015,1,0,0,0,0,1
Male,Total,2,Fall 2015,27,0,0,0,0,1
Male,Total,3,Fall 2015,12,0,0,0,0,1
Male,Total,5,Fall 2015,7,0,0,0,0,1
Male,Total,6,Fall 2015,16,0,0,0,0,1
Male,Total,8,Fall 2015,103,0,0,0,0,1
Male,Total,9,Fall 2015,4,0,0,0,0,1
Male,Total,10,Fall 2015,3,0,0,0,0,1
Male,Total,99,Fall 2015,173,0,0,0,0,0
Male,Total,99,Fall 2015,173,0,0,1,1,1
Total,In-state,1,Fall 2015,2,0,0,0,0,1
Total,In-state,2,Fall 2015,70,0,0,0,0,1
Total,In-state,3,Fall 2015,28,0,0,0,0,1
Total,In-state,5,Fall 2015,26,0,0,0,0,1
Total,In-state,6,Fall 2015,44,0,0,0,0,1
Total,In-state,8,Fall 2015,317,0,0,0,0,1
Total,In-state,9,Fall 2015,4,0,0,0,0,1
Total,In-state,10,Fall 2015,9,0,0,0,0,1
Total,In-state,99,Fall 2015,500,0,0,0,1,1
Total,Out-of-state,2,Fall 2015,25,0,0,0,0,1
Total,Out-of-state,3,Fall 2015,15,0,0,0,0,1
Total,Out-of-state,5,Fall 2015,7,0,0,0,0,1
Total,Out-of-state,6,Fall 2015,13,0,0,0,0,1
Total,Out-of-state,8,Fall 2015,88,0,0,0,0,1
Total,Out-of-state,9,Fall 2015,13,0,0,0,0,1
Total,Out-of-state,99,Fall 2015,161,0,0,0,1,1
Total,Total,1,Fall 2015,2,0,0,0,0,1
Total,Total,2,Fall 2015,95,0,0,0,0,1
Total,Total,3,Fall 2015,43,0,0,0,0,1
Total,Total,5,Fall 2015,33,0,0,0,0,1
Total,Total,6,Fall 2015,57,0,0,0,0,1
Total,Total,8,Fall 2015,405,0,0,0,0,1
Total,Total,9,Fall 2015,17,0,0,0,0,1
Total,Total,10,Fall 2015,9,0,0,0,0,1
Total,Total,99,Fall 2015,661,0,0,0,0,0
Total,Total,99,Fall 2015,661,0,0,1,1,1
;
 
proc report data=all list showall;
   column 
      (
         gender lastGender
         residency_desc lastResidency_desc
         lastSchev_ethnicity_desc schev_ethnicity_desc         
         academic_period_desc, n);
   define gender / group '';
   define residency_desc / group '';
   define schev_ethnicity_desc / group '' order=internal;
   define lastGender / order order=internal noprint;
   define lastResidency_desc / order order=internal noprint;
   define lastSchev_ethnicity_desc / order order=internal noprint;
   define academic_period_desc / across '';
   define n / analysis sum '';
   compute after lastResidency_desc / style={background=lightblue};
      x = ' ';
      if lastgender eq 1 then lastResidency_desc=0;
      line x $varying1. lastResidency_desc;
      endcomp; 
	compute after gender / style={background=blue};		
		line ' ';
		endcomp;
   run;

Re: Compute with If Condition

DavidPhillips2 — Thu, 24 Mar 2016 17:48:57 GMT

How can I group the year column to show side by side?

data all;
infile datalines DLM=',';
input GENDER $ residency_desc : $20. schev_ethnicity_desc ACADEMIC_PERIOD_DESC : $20. n
growthDeclineColumn perGrowthDeclineColumn lastGender lastResidency_desc lastSchev_ethnicity_desc ;
datalines;
Female,In-state,1,Fall 2014,1,0,0,0,0,1
Female,In-state,2,Fall 2014,47,0,0,0,0,1
Female,In-state,3,Fall 2014,18,0,0,0,0,1
Female,In-state,5,Fall 2014,20,0,0,0,0,1
Female,In-state,6,Fall 2014,30,0,0,0,0,1
Female,In-state,8,Fall 2014,230,0,0,0,0,1
Female,In-state,9,Fall 2014,3,0,0,0,0,1
Female,In-state,10,Fall 2014,6,0,0,0,0,1
Female,In-state,99,Fall 2014,355,0,0,0,1,1
Female,Out-of-state,2,Fall 2014,21,0,0,0,0,1
Female,Out-of-state,3,Fall 2014,13,0,0,0,0,1
Female,Out-of-state,5,Fall 2014,6,0,0,0,0,1
Female,Out-of-state,6,Fall 2014,11,0,0,0,0,1
Female,Out-of-state,8,Fall 2014,72,0,0,0,0,1
Female,Out-of-state,9,Fall 2014,10,0,0,0,0,1
Female,Out-of-state,99,Fall 2014,133,0,0,0,1,1
Female,Total,1,Fall 2014,1,0,0,0,0,1
Female,Total,2,Fall 2014,68,0,0,0,0,1
Female,Total,3,Fall 2014,31,0,0,0,0,1
Female,Total,5,Fall 2014,26,0,0,0,0,1
Female,Total,6,Fall 2014,41,0,0,0,0,1
Female,Total,8,Fall 2014,302,0,0,0,0,1
Female,Total,9,Fall 2014,13,0,0,0,0,1
Female,Total,10,Fall 2014,6,0,0,0,0,1
Female,Total,99,Fall 2014,488,0,0,0,0,0
Female,Total,99,Fall 2014,488,0,0,1,1,1
Male,In-state,1,Fall 2014,1,0,0,0,0,1
Male,In-state,2,Fall 2014,23,0,0,0,0,1
Male,In-state,3,Fall 2014,10,0,0,0,0,1
Male,In-state,5,Fall 2014,6,0,0,0,0,1
Male,In-state,6,Fall 2014,14,0,0,0,0,1
Male,In-state,8,Fall 2014,87,0,0,0,0,1
Male,In-state,9,Fall 2014,1,0,0,0,0,1
Male,In-state,10,Fall 2014,3,0,0,0,0,1
Male,In-state,99,Fall 2014,145,0,0,0,1,1
Male,Out-of-state,2,Fall 2014,4,0,0,0,0,1
Male,Out-of-state,3,Fall 2014,2,0,0,0,0,1
Male,Out-of-state,5,Fall 2014,1,0,0,0,0,1
Male,Out-of-state,6,Fall 2014,2,0,0,0,0,1
Male,Out-of-state,8,Fall 2014,16,0,0,0,0,1
Male,Out-of-state,9,Fall 2014,3,0,0,0,0,1
Male,Out-of-state,99,Fall 2014,28,0,0,0,1,1
Male,Total,1,Fall 2014,1,0,0,0,0,1
Male,Total,2,Fall 2014,27,0,0,0,0,1
Male,Total,3,Fall 2014,12,0,0,0,0,1
Male,Total,5,Fall 2014,7,0,0,0,0,1
Male,Total,6,Fall 2014,16,0,0,0,0,1
Male,Total,8,Fall 2014,103,0,0,0,0,1
Male,Total,9,Fall 2014,4,0,0,0,0,1
Male,Total,10,Fall 2014,3,0,0,0,0,1
Male,Total,99,Fall 2014,173,0,0,0,0,0
Male,Total,99,Fall 2014,173,0,0,1,1,1
Total,In-state,1,Fall 2014,2,0,0,0,0,1
Total,In-state,2,Fall 2014,70,0,0,0,0,1
Total,In-state,3,Fall 2014,28,0,0,0,0,1
Total,In-state,5,Fall 2014,26,0,0,0,0,1
Total,In-state,6,Fall 2014,44,0,0,0,0,1
Total,In-state,8,Fall 2014,317,0,0,0,0,1
Total,In-state,9,Fall 2014,4,0,0,0,0,1
Total,In-state,10,Fall 2014,9,0,0,0,0,1
Total,In-state,99,Fall 2014,500,0,0,0,1,1
Total,Out-of-state,2,Fall 2014,25,0,0,0,0,1
Total,Out-of-state,3,Fall 2014,15,0,0,0,0,1
Total,Out-of-state,5,Fall 2014,7,0,0,0,0,1
Total,Out-of-state,6,Fall 2014,13,0,0,0,0,1
Total,Out-of-state,8,Fall 2014,88,0,0,0,0,1
Total,Out-of-state,9,Fall 2014,13,0,0,0,0,1
Total,Out-of-state,99,Fall 2014,161,0,0,0,1,1
Total,Total,1,Fall 2014,2,0,0,0,0,1
Total,Total,2,Fall 2014,95,0,0,0,0,1
Total,Total,3,Fall 2014,43,0,0,0,0,1
Total,Total,5,Fall 2014,33,0,0,0,0,1
Total,Total,6,Fall 2014,57,0,0,0,0,1
Total,Total,8,Fall 2014,405,0,0,0,0,1
Total,Total,9,Fall 2014,17,0,0,0,0,1
Total,Total,10,Fall 2014,9,0,0,0,0,1
Total,Total,99,Fall 2014,661,0,0,0,0,0

Female,In-state,1,Fall 2015,1,0,0,0,0,1
Female,In-state,2,Fall 2015,47,0,0,0,0,1
Female,In-state,3,Fall 2015,18,0,0,0,0,1
Female,In-state,5,Fall 2015,20,0,0,0,0,1
Female,In-state,6,Fall 2015,30,0,0,0,0,1
Female,In-state,8,Fall 2015,230,0,0,0,0,1
Female,In-state,9,Fall 2015,3,0,0,0,0,1
Female,In-state,10,Fall 2015,6,0,0,0,0,1
Female,In-state,99,Fall 2015,355,0,0,0,1,1
Female,Out-of-state,2,Fall 2015,21,0,0,0,0,1
Female,Out-of-state,3,Fall 2015,13,0,0,0,0,1
Female,Out-of-state,5,Fall 2015,6,0,0,0,0,1
Female,Out-of-state,6,Fall 2015,11,0,0,0,0,1
Female,Out-of-state,8,Fall 2015,72,0,0,0,0,1
Female,Out-of-state,9,Fall 2015,10,0,0,0,0,1
Female,Out-of-state,99,Fall 2015,133,0,0,0,1,1
Female,Total,1,Fall 2015,1,0,0,0,0,1
Female,Total,2,Fall 2015,68,0,0,0,0,1
Female,Total,3,Fall 2015,31,0,0,0,0,1
Female,Total,5,Fall 2015,26,0,0,0,0,1
Female,Total,6,Fall 2015,41,0,0,0,0,1
Female,Total,8,Fall 2015,302,0,0,0,0,1
Female,Total,9,Fall 2015,13,0,0,0,0,1
Female,Total,10,Fall 2015,6,0,0,0,0,1
Female,Total,99,Fall 2015,488,0,0,0,0,0
Female,Total,99,Fall 2015,488,0,0,1,1,1
Male,In-state,1,Fall 2015,1,0,0,0,0,1
Male,In-state,2,Fall 2015,23,0,0,0,0,1
Male,In-state,3,Fall 2015,10,0,0,0,0,1
Male,In-state,5,Fall 2015,6,0,0,0,0,1
Male,In-state,6,Fall 2015,14,0,0,0,0,1
Male,In-state,8,Fall 2015,87,0,0,0,0,1
Male,In-state,9,Fall 2015,1,0,0,0,0,1
Male,In-state,10,Fall 2015,3,0,0,0,0,1
Male,In-state,99,Fall 2015,145,0,0,0,1,1
Male,Out-of-state,2,Fall 2015,4,0,0,0,0,1
Male,Out-of-state,3,Fall 2015,2,0,0,0,0,1
Male,Out-of-state,5,Fall 2015,1,0,0,0,0,1
Male,Out-of-state,6,Fall 2015,2,0,0,0,0,1
Male,Out-of-state,8,Fall 2015,16,0,0,0,0,1
Male,Out-of-state,9,Fall 2015,3,0,0,0,0,1
Male,Out-of-state,99,Fall 2015,28,0,0,0,1,1
Male,Total,1,Fall 2015,1,0,0,0,0,1
Male,Total,2,Fall 2015,27,0,0,0,0,1
Male,Total,3,Fall 2015,12,0,0,0,0,1
Male,Total,5,Fall 2015,7,0,0,0,0,1
Male,Total,6,Fall 2015,16,0,0,0,0,1
Male,Total,8,Fall 2015,103,0,0,0,0,1
Male,Total,9,Fall 2015,4,0,0,0,0,1
Male,Total,10,Fall 2015,3,0,0,0,0,1
Male,Total,99,Fall 2015,173,0,0,0,0,0
Male,Total,99,Fall 2015,173,0,0,1,1,1
Total,In-state,1,Fall 2015,2,0,0,0,0,1
Total,In-state,2,Fall 2015,70,0,0,0,0,1
Total,In-state,3,Fall 2015,28,0,0,0,0,1
Total,In-state,5,Fall 2015,26,0,0,0,0,1
Total,In-state,6,Fall 2015,44,0,0,0,0,1
Total,In-state,8,Fall 2015,317,0,0,0,0,1
Total,In-state,9,Fall 2015,4,0,0,0,0,1
Total,In-state,10,Fall 2015,9,0,0,0,0,1
Total,In-state,99,Fall 2015,500,0,0,0,1,1
Total,Out-of-state,2,Fall 2015,25,0,0,0,0,1
Total,Out-of-state,3,Fall 2015,15,0,0,0,0,1
Total,Out-of-state,5,Fall 2015,7,0,0,0,0,1
Total,Out-of-state,6,Fall 2015,13,0,0,0,0,1
Total,Out-of-state,8,Fall 2015,88,0,0,0,0,1
Total,Out-of-state,9,Fall 2015,13,0,0,0,0,1
Total,Out-of-state,99,Fall 2015,161,0,0,0,1,1
Total,Total,1,Fall 2015,2,0,0,0,0,1
Total,Total,2,Fall 2015,95,0,0,0,0,1
Total,Total,3,Fall 2015,43,0,0,0,0,1
Total,Total,5,Fall 2015,33,0,0,0,0,1
Total,Total,6,Fall 2015,57,0,0,0,0,1
Total,Total,8,Fall 2015,405,0,0,0,0,1
Total,Total,9,Fall 2015,17,0,0,0,0,1
Total,Total,10,Fall 2015,9,0,0,0,0,1
Total,Total,99,Fall 2015,661,0,0,0,0,0

;

proc report data=all list showall;
column
(
gender lastGender
residency_desc lastResidency_desc
lastSchev_ethnicity_desc schev_ethnicity_desc
academic_period_desc, n);
define gender / group '';
define residency_desc / group '';
define schev_ethnicity_desc / group '' order=internal;
define lastGender / order order=internal noprint;
define lastResidency_desc / order order=internal noprint;
define lastSchev_ethnicity_desc / order order=internal noprint;
define academic_period_desc / group across '';
define n / analysis sum '';
compute after lastResidency_desc / style={background=lightblue};
x = ' ';
if lastgender eq 1 then lastResidency_desc=0;
line x $varying1. lastResidency_desc;
endcomp;
compute after gender / style={background=blue};
line ' ';
endcomp;
run;

Re: Compute with If Condition

data_null__ — Thu, 24 Mar 2016 18:41:35 GMT

Change all the ORDERs to GROUPs. But I think it would be easier to create the LAST variables if you first transpose years to variables.

proc report data=all list;* showall;
   column
      (
         gender lastGender
         residency_desc lastResidency_desc
         lastSchev_ethnicity_desc schev_ethnicity_desc
         academic_period_desc, n
      );
   define gender / group ' ';
   define residency_desc / group ' ';
   define schev_ethnicity_desc / group ' ' order=internal;
   define lastGender / group order=internal noprint;
   define lastResidency_desc / group order=internal noprint;
   define lastSchev_ethnicity_desc / group order=internal noprint;
   define academic_period_desc /  across ' ';
   define n / analysis sum '';
   compute after lastResidency_desc / style={background=lightblue};
      x = ' ';
      if lastgender eq 1 then lastResidency_desc=0;
      line x $varying1. lastResidency_desc;
      endcomp;
   compute after gender / style={background=blue};
      line ' ';
      endcomp;
   run;

You're welcome.