Hi,   I have a proc frequency statement with multiple variables for cross tablulation.   Example:    proc freq data=abc.mydataset; format _CHAR_ $missfmt.; format _NUMERIC_ missfmt.; tables var_1*(var_2 date_1 num_1 var_3 num_2 date_2 num_3) / NOCUM NOPERCENT MISSING; run;   This particular dataset has over 19,000 observations.  It took 1 hour to run the freq statement on my local machine.    Any advice on ways to speed this up?  I know it is large. ... View more

Hi,   I am just now playing with the prompt manager feature in SAS EG.  I am using a proc sql script in a program task and I want the prompt to populate the where clause of the script.  If I only have one variable (field 1 = 'x') it works just fine.  However, I want to write it so I can enter multiple values with the prompt.  (field 1 in ('x','y')).  I get a syntax error when I do this.  I have tried putting the quotes in a single text prompt, multiple text promp, etc. but I can't seem to get it to work correctly.  Can you guys tell me what I am missing? ... View more

Hi,   I am trying to build a process that takes a daily file and compares it to the data already stored in a dataset.  I want to create a dataset out of the file and compare it to the main dataset to see if there were any observations that had data changed in any variable.  For example, I have a dataset 3 observations in it.  The variables are ID, Name, Date1, Date2, Amount.    1 Red 5/1/2017, 5/30/2017, $400.00 2 Blue 6/1/2017, 6/30/2017, $500.00 3 Blue 6/1/2017, 7/31/2017, $350.00   I get a file that has 1 observation with 2 data fields that are different from my original dataset.   2 Blue 6/1/2017, 7/31/2017, $600.00   I need to be able to do the following:   1. Update the old (primary) dataset with the new data in the updated file. 2. Add new records if they are in the new file but not the old (primary) dataset. 3. Generate a dataset or report that gives the observation, which variables were updated, and what the updates were.   I have found this article and it makes pretty good sense.  However, I want to make sure there isn't something built in for this that would make it a little easier.   Using PROC COMPARE to identify new and updated ... - PharmaSUG   If there is a better way, please let me know. ... View more

Hello,   I have recently been researching ways to come up with some basic statistics for the variable data in my datasets.  I found code that works well for me in THIS article by Rick Wicklin using proc iml.  I had some questions about his code but he is referring questions to this forum.  I want to take the following code that he used as an example in the blog and modify it to only pull back the variables I need.  Currently, it pulls back the statistics for all variables in the dataset.  I also am confused on how I would then export this to a dataset.  Could someone point me in the right direction on both of these questions?   proc iml; use work.datagapanalysis; read all var _NUM_ into x[colname=nNames]; n = countn(x,"col"); nmiss = countmiss(x,"col"); read all var _CHAR_ into x[colname=cNames]; close work.datagapanalysis; c = countn(x,"col"); cmiss = countmiss(x,"col"); /* combine results for num and char into a single table */ Names = cNames || nNames; rNames = {" Missing", "Not Missing"}; cnt = (cmiss // c) || (nmiss // n); print cnt[r=rNames c=Names label=""]; ... View more