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Posted 07-23-2012 09:07 AM
(1341 views)

Hi everyone,

My goal is to create a large data table that has descriptive statistics accompanying each observation. I am loading in a large file for which each observation has its own mean, standard deviation and percentiles. The variable that I am using to calculate all of this is named 'tapefile'. Basically what I am trying to do is create a large data table that neatly displays these statistics. I have been trying to accomplish this by saving the proc univariate command as a variable and then printing. I am new to sas so I am not entirely sure if this is even possible. Below is a sample of the data table that I seek to achieve.

Observation | Mean | Std Dev | 50th Percentile | 60th Percentile | 70th Percentile | 80th Percentile | 90th Percentile | 100th Percentile |
---|---|---|---|---|---|---|---|---|

1 | ||||||||

2 | ||||||||

3 | ||||||||

4 |

Here is a sample of my code as well:

options ls=176 ps=44;

libname master 'library location';

filename input0 'file location';

data detail;

infile input0 lrecl=605 recfm=f;

input (long list of ebcdic variables);

run;

proc sort data=detail;

by tapefile;

run;

proc univariate data=detail noprint;

var tapefile;

output out=res mean=mean pctlpts = 50 to 100 by 10 pctlpre=p;

run;

proc print data=detail label;

var tapefile tab_guca_mod_1 res;

label

p50="50th Percentile"

p60="60th Percentile"

p70="70th Percentile"

p80="80th Percentile"

p90="90th Percentile"

p100="100th Percentile";

run;

Thank you for any help you may be able to provide; I greatly appreciate it.

3 REPLIES 3

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Assuming you're asking to add in the overall statistics rather than the statistics for "each observation has its own mean, standard deviation and percentiles".

You can calculate the stats in proc means and then merge then in using a SQL cross join.

proc means data=sashelp.class ;

var height;

output out=stats mean= std= p50= p60= p70= p80= p90= max=/autoname;

run;

proc sql;

create table class as

select *

from sashelp.class

cross join stats;

quit;

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**same** set of percentiles attached to **all** values of tapefile? Or are you using TAPEFILE as shorthand to indicate you want to do the same thing to each variable in the (long list of ebcdic variables)? You might show some dummy output of what you expect your final table to look like.

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Try this technique:

**data** detail ;

input tapefile larry more curly ;

cards ;

3 31 32 33

1 11 12 13

2 21 22 23

;

**proc** **sort** data=detail ;

by tapefile ;

**run** ;

**proc** **transpose** data=detail out=long ;

by tapefile ;

var larry more curly ;

**run** ;

**proc** **univariate** data=long noprint ;

by tapefile ;

output out=res mean=mean

pctlpts = **50** to **100** by **10** pctlpre=p ;

**run** ;

**proc** **print** data=res label ;

label

p50="50th Percentile"

p60="60th Percentile"

p70="70th Percentile"

p80="80th Percentile"

p90="90th Percentile"

p100="100th Percentile" ;

**run** ;

Torri92 wrote:

Hi everyone,

My goal is to create a large data table that has descriptive statistics accompanying each observation. I am loading in a large file for which each observation has its own mean, standard deviation and percentiles. The variable that I am using to calculate all of this is named 'tapefile'. Basically what I am trying to do is create a large data table that neatly displays these statistics. I have been trying to accomplish this by saving the proc univariate command as a variable and then printing. I am new to sas so I am not entirely sure if this is even possible. Below is a sample of the data table that I seek to achieve.

Observation | Mean | Std Dev | 50th Percentile | 60th Percentile | 70th Percentile | 80th Percentile | 90th Percentile | 100th Percentile |
---|---|---|---|---|---|---|---|---|

1 | ||||||||

2 | ||||||||

3 | ||||||||

4 |

Here is a sample of my code as well:

options ls=176 ps=44;

libname master 'library location';

filename input0 'file location';

data detail;

infile input0 lrecl=605 recfm=f;

input (long list of ebcdic variables);

run;

proc sort data=detail;

by tapefile;

run;

proc univariate data=detail noprint;

var tapefile;

output out=res mean=mean pctlpts = 50 to 100 by 10 pctlpre=p;

run;

proc print data=detail label;

var tapefile tab_guca_mod_1 res;

label

p50="50th Percentile"

p60="60th Percentile"

p70="70th Percentile"

p80="80th Percentile"

p90="90th Percentile"

p100="100th Percentile";

run;

Thank you for any help you may be able to provide; I greatly appreciate it.

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