About antonbcristina

antonbcristina · ‎06-28-2023

I tested the subquery alone and it does produce an ERROR revealing the issue: 34 proc sql; 35 select ID from has_personID_var; ERROR: The following columns were not found in the contributing tables: ID. NOTE: PROC SQL set option NOEXEC and will continue to check the syntax of statements. 36 quit; NOTE: The SAS System stopped processing this step because of errors. NOTE: PROCEDURE SQL used (Total process time): real time 0.00 seconds cpu time 0.00 seconds However, the outer query does not see this as an issue. Here is a related post: https://communities.sas.com/t5/SAS-Procedures/SQL-subquery-wrong-variable-name-no-error/td-p/606354

antonbcristina · ‎06-26-2023

Absolutely! This has been discussed in several posts and here's a great solution to read through. If you want to see what's going on behind the scenes, display your calculated value (b-a) and the value you wish to compare against (let's call this d) in their hexidecimal representation using the HEX format, like so: data aa; input a b; c = b - a; d = 6.3; put c hex16.; put d hex16.; datalines; 2.9 9.2 ; You can see that the two values are very similar, except for the end due to rounding errors. SAS Documentation covers this topic here: https://documentation.sas.com/doc/en/pgmsascdc/v_037/lepg/n0o6e1t72yad42n10y9wf8pgmat8.htm#p0lghy68tpnudtn1je83d9vt1yf2 For your example, the ROUND function will do the trick like so: data aa; input a b; c = b - a; d = 6.3; if round(c,.1) = d; datalines; 2.9 9.2 ;

antonbcristina · ‎04-26-2018

I created dataset temp just to have some data to illustrate my point. The input statement tells SAS what to read in from the data lines I will be providing and the datalines statement start off the listing of the raw data. Your code would have only one DATA step and should look similar to this: data Final_drug_counts; set Final_drug; by seqn; if first.seqn then count=0; array drugs {*} DrugID:; do i = 1 to dim(drugs); count + (drugs[i]=40); end; run; Your other variables will remain in the dataset, unchanged.

antonbcristina · ‎04-26-2018

The easiest way would be create an array to hold all of your drug IDs and then loop through and count how many are equal to the specific drug ID you're looking for. data temp; input ID DrugID1 DrugID2; datalines; 1 40 57 2 40 40 ; run; data temp2; set temp; by id; if first.id then count=0; array drugs {*} DrugID:; do i = 1 to dim(drugs); count + (drugs[i]=40); end; run;

antonbcristina · ‎04-25-2018

Just created some sample data to work with here: data temp; input var1 var2 var3 ; datalines; 1 1 1 2 4 8 3 9 27 4 16 64 ; run; and a simple macro that creates a scatterplot: %macro graphthis(xaxis,yaxis); proc sgplot data=temp; scatter x=&xaxis y=&yaxis; run; %mend; Now, if you can write out your variables in a list, then store them in macro variables %let xs = var1; %let ys = var2 var3; and loop through the macro variables like so: %macro loopthrough(); %do i=1 %to %sysfunc(countw(&xs)); %do j=1 %to %sysfunc(countw(&ys)); %let x&i = %scan(&xs, &i, %str( )); %let y&i = %scan(&ys, &j, %str( )); %graphthis(&&x&i, &&y&i); %end; %end; %mend; options mprint mlogic symbolgen; %loopthrough();

antonbcristina · ‎04-24-2018

If you use the CATX function, your numeric variables will automatically be converted into character, with leading and trailing spaces removed. However, make sure you mention your variables as individual arguments for the function, not as one long concatenated string. I've included a space delimiter, the first argument to the CATX function, but you could change this to "|" if you need to. And of course, you can use this in PROC SQL as well. proc sql; select catx(' ',id,rank,count,date) as fin from have; quit;

antonbcristina · ‎04-24-2018

I've recreated a small sample of your sample here: data diseases; infile datalines dlm=' ' dsd; input year age $ gender $ disease :$50. cases pop; datalines; 1990 0-17 All Asthma 182000 64177000 1990 0-17 All "Dementia and Alzheimer's disease" . 64177000 1990 0-17 Female Asthma 71000 31295000 1990 0-17 Female "Dementia and Alzheimer's disease" 22000 31295000 1990 0-17 Male Asthma 111000 32883000 1990 0-17 Male "Dementia and Alzheimer's disease" . 32883000 run; So if you do have a scenario as you mentioned, the easiest way to validate your data is to transpose it and then check that all = sum of females and males, as below. If it isn't, then make it so. proc sort data=diseases; by year age disease; run; proc transpose data=diseases out=diseases_t; by year age disease; var cases pop; id gender; run; data diseases_validated; set diseases_t; valid = (all=sum(female,male)); run;

antonbcristina · ‎04-24-2018

This doesn't seem to be reflected in your sample. Is your data different?

antonbcristina · ‎04-24-2018

I think you meant to say: Yes, there is only a missing value in all if there is a missing value for both male and female. In this case, there is nothing that you can do to fix this. There is no way to calculate the All category without individual cases for either Female or Male.

antonbcristina · ‎04-24-2018

From the sample you showed, the only time that the All category has missing cases is when there are missing cases for both Females and Males. Is this always the case?

antonbcristina · ‎04-23-2018

First, I would suggest you to read in the dates using an informat like below, since you will need to compare dates in the process. :mmddyy10. Here is your data recreated: data test; infile datalines missover dsd dlm=' '; input entity vote_date :mmddyy10. passed $ failed $; datalines; 7 10/25/2015 Y 7 1/18/2016 Y 7 10/18/2016 Y 14 2/16/2017 Y 14 8/26/2017 Y 14 9/15/2017 Y run; Then use a RETAIN statement to keep track of the most recent date for passed and failed referendum (I used lastpassed_date and lastfailed_date to hold their values). data test2; set test; by entity vote_date; retain lastpassed_date lastfailed_date; if first.entity then do; lastpassed_date=.; lastfailed_date=.; end; if passed='Y' then lastpassed_date=vote_date; else if failed='Y' then lastfailed_date=vote_date; run; Now that you have these dates stored, you can compare them at the end of the program. Sounds like you might only want to keep the records where lastpassed_date is greater than lastfailed_date, making sure to check that lastfailed_date isn't missing. if lastpassed_date > lastfailed_date and not missing(lastfailed_date); Let me know if this works.

antonbcristina · ‎04-19-2018

You're on the right track, except that instead of hard coding the IDs you're better off using them directly from the data set. The merge below makes use of the IN= dataset option which creates a temporary variable (I named it b). b=1 if dataset dataB contributes to a merged observation b=0 if dataset dataB does not contribute to the merged observation By selecting only the observations where b is not equal to 1, you get all IDs that are not in dataB. data allAs; merge dataA dataB(in=b); by client_id; if b^=1; run;

antonbcristina · ‎02-09-2018

Ok, I'm guessing the birth date you have already is stored as a character string. What you could do is create a new variable that stores the numeric version of the character string. SAS stores dates numerically as the number of days since January 1st, 1960. To convert your character date (say bday_c) into a numeric one (say bday_n), you can use the following: bday_n = input(bday_c,mmddyy.); The INPUT function is used here, which has two arguments: a character string and an informat. The informat MMDDYY specifies that SAS should read the character string as having the month first (mm), then the day (dd), and finally the year (yy).

antonbcristina · ‎02-09-2018

And how would you like it to look?

antonbcristina · ‎02-09-2018

Can you post your code and log? It will help to figure out what is going on.

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