If it's 0/1 data, and you're only comparing counts that could be equivalent of comparing the mean and N of those variables, or sum.
So you can run each data set through proc means summarizing the Mean and N and then compare them. If you want the 0/1 values then it's bit more work but doable.
ods select none;
proc means data=have1 N SUM MEAN;
var _numeric_;
ods output want = _summary1;
run;
ods select all;
Run something like that for each data set and then combine the results as follows:
data want;
length ds dsname $50.;
set _summary1 _summary2 indsname=ds;
dsname = ds;
run;
Then you can use proc transpose if you really want the long format. Otherwise you transpose and then merge so really it's the same operations, different order.
If your data is character this will not work. Instead you'll need to use PROC FREQ to replace the PROC MEANS.
Rough idea is here https://gist.github.com/statgeek/e0903d269d4a71316a4e
Refer to all variables using _all_, _numeric_ or _character_.
Here is a reference that illustrates how to refer to variables and datasets in a short cut list:
https://blogs.sas.com/content/iml/2018/05/29/6-easy-ways-to-specify-a-list-of-variables-in-sas.html
@lydiawawa wrote:
I have two very large datasets with the exact same variables name and row counts, and I'm doing comparisons between the variables. I'm hoping to generate frequency counts in output format such as below:
|
Variable
|
0_data1
|
1_data1
|
0_data2
|
1_data2
|
etc
|
|
ang1
|
45
|
3
|
45
|
2
|
|
|
ang2
|
43
|
23
|
42
|
23
|
|
|
ang3
|
44
|
43
|
44
|
43
|
|
|
ang4
|
23
|
343
|
23
|
321
|
|
|
etc
|
|
|
|
|
|
All variables are in character format with level '0' or '1', and I need to compare counts among levels. There are over 100 variables on each dataset , each dataset has over 10million rows.
To arrive at the output, I thought about outputting categorical variable frequency then merge outputs from both datasets by variable name.
Such that:
Original , there is no ID/index variable
|
ang1
|
ang2
|
ang3
|
ang4
|
Etc.
|
|
0
|
1
|
0
|
0
|
0
|
|
1
|
1
|
1
|
1
|
1
|
|
0
|
1
|
0
|
1
|
0
|
|
0
|
0
|
1
|
1
|
1
|
|
etc
|
|
|
|
|
To
|
Variable
|
0_data1
|
1_data1
|
|
ang1
|
45
|
3
|
|
ang2
|
43
|
23
|
|
ang3
|
44
|
43
|
|
ang4
|
23
|
343
|
|
etc
|
|
|
How to arrive at the above output for data1?
Appreciate for any inputs.
