topic Re: n% of total observation in SAS Programming

n% of total observation

kggunes — Thu, 13 Dec 2012 11:22:41 GMT

Hello,

For each observation I would like to create a variable showing the percentage of the total observation. To put it simply, let's say I have 100 observations and i want to see the "8%" in the 8th observation (kind of percentiles).

I am aware of Proc UNIVARIATE; PCTLPTS= but couldn't find a good example application of it :smileyplain: Could anyone suggest an easy solution?

Many thanks!

Re: n% of total observation

Linlin — Thu, 13 Dec 2012 11:37:01 GMT

Is this what you want?

data calss;

set sashelp.class nobs=nobs;

per=_n_/nobs;

format per percent6.2;

run;

proc print;run;

Obs Name Sex Age Height Weight per

1 Alfred M 14 69.0 112.5 5.3%

2 Alice F 13 56.5 84.0 11%

3 Barbara F 13 65.3 98.0 16%

4 Carol F 14 62.8 102.5 21%

5 Henry M 14 63.5 102.5 26%

6 James M 12 57.3 83.0 32%

7 Jane F 12 59.8 84.5 37%

8 Janet F 15 62.5 112.5 42%

9 Jeffrey M 13 62.5 84.0 47%

10 John M 12 59.0 99.5 53%

11 Joyce F 11 51.3 50.5 58%

12 Judy F 14 64.3 90.0 63%

13 Louise F 12 56.3 77.0 68%

14 Mary F 15 66.5 112.0 74%

15 Philip M 16 72.0 150.0 79%

16 Robert M 12 64.8 128.0 84%

17 Ronald M 15 67.0 133.0 89%

18 Thomas M 11 57.5 85.0 95%

19 William M 15 66.5 112.0 100%

Re: n% of total observation

kggunes — Thu, 13 Dec 2012 12:39:46 GMT

Hello Linlin,

Thank you for the prompt and quick answer! If I may ask one more thing to enhance the question.. what if I want to see the percent by group - in the same output dataset? For this example, how can we group the percent answer for males and females separately?

Re: n% of total observation

Linlin — Thu, 13 Dec 2012 14:06:37 GMT

Hi,

Is this what you want?

data calss;
do until(done1);
set sashelp.class end=done1;
if upcase(sex)='F' then girls+1;
    else boys+1;
end;
do until(done2);
   set sashelp.class end=done2 nobs=nobs;
if upcase(sex)='F' then g+1;
    else b+1;
n+1;
percent_t=n/nobs;
percent_f=g/girls;
percen_m=b/boys;
output;
end;
format per: percent8.2;
run;
proc print;run;                                        percent_ percent_
   Obs Name     Sex Age Height Weight girls boys g   b   n     t         f      percen_m

     1 Alfred    M    14   69.0    112.5    9     10   0   1   1    5.3%      .00%       10%
     2 Alice     F    13   56.5     84.0    9     10   1   1   2     11%       11%       10%
     3 Barbara   F    13   65.3     98.0    9     10   2   1   3     16%       22%       10%
     4 Carol     F    14   62.8    102.5    9     10   3   1   4     21%       33%       10%
     5 Henry     M    14   63.5    102.5    9     10   3   2   5     26%       33%       20%
     6 James     M    12   57.3     83.0    9     10   3   3   6     32%       33%       30%
     7 Jane      F    12   59.8     84.5    9     10   4   3   7     37%       44%       30%
     8 Janet     F    15   62.5    112.5    9     10   5   3   8     42%       56%       30%
     9 Jeffrey   M    13   62.5     84.0    9     10   5   4   9     47%       56%       40%
    10 John      M    12   59.0     99.5    9     10   5   5 10     53%       56%       50%
    11 Joyce     F    11   51.3     50.5    9     10   6   5 11     58%       67%       50%
    12 Judy      F    14   64.3     90.0    9     10   7   5 12     63%       78%       50%
    13 Louise    F    12   56.3     77.0    9     10   8   5 13     68%       89%       50%
    14 Mary      F    15   66.5    112.0    9     10   9   5 14     74%      100%       50%
    15 Philip    M    16   72.0    150.0    9     10   9   6 15     79%      100%       60%
    16 Robert    M    12   64.8    128.0    9     10   9   7 16     84%      100%       70%
    17 Ronald    M    15   67.0    133.0    9     10   9   8 17     89%      100%       80%
    18 Thomas    M    11   57.5     85.0    9     10   9   9 18     95%      100%       90%
    19 William   M    15   66.5    112.0    9     10   9 10 19    100%      100%      100%

Re: n% of total observation

kggunes — Thu, 13 Dec 2012 14:09:09 GMT

Awesome.. Thanks!

Re: n% of total observation

TomKari — Thu, 13 Dec 2012 16:50:47 GMT

Here's another option:

data work.class;
set sashelp.class;
varseq = _n_;
run;

proc sort data=work.class;
by sex;

proc rank data = work.class groups=100 ties=mean out=work.rankedclass;
by sex;
var varseq;
ranks varseq_rank;
run;

Tom