How to put two distribution curve together in Proc univariate

[iusing]

I use proc univaraiate to draw the distribution curve and histogram of two different groups of data by the following code:

Proc univariate data=data noprint;

     histogram money /cfill=ligr normal cframe=liy barwidth=8 cv=black;

     BY location;

RUN;

I would like to know how to put curves generated in the by statement together in one graph.

[Rick_SAS]

You can get a COMPARATIVE panel of histograms by using the CLASS stmt instead of the BY stmt: CLASS location;

If this isn't sufficient, then I ask whether you just want the normal curves by themselves (in a single plot), or whether you want the densities fpor each group overlaid on a histogram.  If on a histogram, then are you asking for the histogram of ALL the data, across all groups?

[iusing]

Actually, I just want the normal curves, how can I put into one graph to do the comparison

[Jay54]

You can do this using SGPLOT procedure.  If this is what you need, I can attach the code.

[iusing]

yup

how to draw it?

[Jay54 · Accepted solution]

This solution uses PROC SGPLOT's DENSITY statements.  Transform the data into multiple columns (one per class) and then use multiple density plots. I just used a data step with SASHELP.CARS to do that, but you can likely use proc transpose.

/*--Sort the data--*/

proc sort data=sashelp.cars out=cars;

  by origin;

  run;

/*--Separate the class data into multiple columns--*/

data cars1 cars2 cars3;

  set cars (keep=mpg_city origin);

  if origin='USA' then do; mpg_usa=mpg_city; output cars1; end;

  if origin='Asia' then do; mpg_asia=mpg_city; output cars2; end;

  if origin='Europe' then do; mpg_eur=mpg_city; output cars3; end;

  run;

/*--Merge data into one data set--*/

data MpgByOrigin;

  merge cars1(keep=mpg_usa) cars2(keep=mpg_asia) cars3(keep=mpg_eur);

  run;

/*--Create graph using SGPLOT--*/

title 'Milage Distribution by Origin';

proc sgplot data=mpgbyorigin;

  density mpg_usa / legendlabel='USA' lineattrs=(pattern=solid);

  density mpg_asia  / legendlabel='Asia' lineattrs=(pattern=solid);

  density mpg_eur  / legendlabel='Europe' lineattrs=(pattern=solid);

  keylegend / location=inside position=topright across=1;

  xaxis display=(nolabel);

  run;

[Rick_SAS]

One way is to transpose the data so that each category become a variable, and then use the SGPLOT DENSITY stmt.

To transpose the data, see http://blogs.sas.com/content/iml/2011/11/04/reshape-data-so-that-each-category-becomes-a-new-variabl...

Here's an example:

data combo;
keep Females Males;
merge sashelp.class(where=(sex="F") rename=(height=Females))
       sashelp.class(where=(sex="M") rename=(height=Males));
run;

proc sgplot data=combo;
density Females / legendlabel="Female";
density Males / legendlabel="Male";
xaxis label="Height";
run;