Well, I am not very good using macro language specially when I have to deal with quotes and special characters like in this case. If I were you I would avoid using macros because in my opinion SAS Base language is a much better tool to do what you need. I would: 1. Run SAS code (without macros) to test the email with one attachment. 2. Run SAS code to test the email with two or more attachments. 3. Once I am sure about the syntax then I would use the SAS Data Step to generate the list of n files using SAS Base (no macro at all). I believe this is a safer approach than using macros. Good luck CTorres ... View more

I think the problem here is that you can have only one ATTACH= option in the FILE statement. So you have to use the loop to generate the list of files to attach and the use only one attach= option. Something like:  (untested and may be more complex than that) FILENAME mail EMAIL; DATA _NULL_; FILE mail TO = "Lisa1245@yahoo.com" FROM = "argo34@yahoo.com" %macro send_email; %LET mylist=; %DO i=1 %TO %SYSFUNC(COUNTW(&FILENAMELIST1,’|’)); %LET NEXT_FILENAMELIST1 = %SCAN(&FILENAMELIST1,&i,|);    &LET mylist=&mylist. "%sysfunc(pathname(project))\&NEXT_FILE NAMELIST1..PDF";   /* here you build the list */ %END; ATTACH=("&mylist"); PUT "Hi Lisa,"; PUT " "; PUT "This is test"; PUT " "; PUT "Thanks," RUN; QUIT; %mend; CTorres ... View more

You can recreate the email sequence with the following additional Data step: data want(rename=seq=email);   set want(drop=email);   by ID;   retain seq;   if first.id then seq=1;      else seq=seq+1; run; CTorres ... View more

As far as I understand there isn't an out-the-box transformation to do that but you can use either the User Written Code Transformation or the New Transformation Wizard to generate the required SAS code. CTorres ... View more

Proc SQL produces ONLY one output Dataset. You can use a SAS Data Step to generate many datasets in one pass. The following program creates the three datasets you want using the today as the reference date to count the 0-12, 13-24 and 25-36 months back. data Customers_Active Customers_Inactive Customers_Lapsed;   set transaction_vw;   if transaction_date > today()-365 then output Customers_Active;   else if transaction_date > today()-730 then output Customers_Inactive;   else if transaction_date > today()-1095 then output Customers_Lapsed; run; Use the program as a starting point to get your results. Hope this helps, CTorres ... View more

IMO the blank will not hurt at all when you read the .cvs file. Take into account that SAS represents missing values with a . for numeric variables and with a blank for character variables. CTorres ... View more

So, the following would be the solution (untested) for your proc means assuming the class variables are character type: proc sql noprint;   create view type11 as   select distinct source, Year,                   /* from by statement in Proc means */      cltname, incentive,                          /* from class statement in Proc means */      '11' as _TYPE_, count(*) as _FREQ_,          /* _TYPE_ and _FREQ_ variables  */      Sum(Elig) as ELIG, sum(overall) as overal,   /* SUM statistics for var statement */        Sum(initial) as initial, sum(consecutive) as conservative   from temp   group by  source, Year, cltname, incentive;     /* from both by and class statements  */   create view type10 as   select distinct source, Year,      cltname, ' ' as incentive,      '10' as _TYPE_, count(*) as _FREQ_,      Sum(Elig) as ELIG, um(overall) as overal,      Sum(initial) as initial, sum(consecutive) as conservative   from temp   group by  source, Year, cltname;   create view type01 as   select distinct source, Year,      ' ' as cltname, incentive,      '01' as _TYPE_, count(*) as _FREQ_,      Sum(Elig) as ELIG, um(overall) as overal,      Sum(initial) as initial, sum(consecutive) as conservative   from temp   group by  source, Year, incentive;   create view type00 as   select distinct source, Year,      ' ' as cltname, ' ' as incentive,      '00' as _TYPE_, count(*) as _FREQ_,      Sum(Elig) as ELIG, um(overall) as overal,      Sum(initial) as initial, sum(consecutive) as conservative   from temp   group by  source, Year;   create table smry as   select * from type11   union all   select * from type10   union all   select * from type01   union all   select * from type00   order by 1,2,3,4; quit; CTorres ... View more

Hi Aanch16167, The following example shows how to convert a PROC MEANS to PROC SQL. You can use it as starting point to create your own solution: data grade;    input Name $ 1-8 Gender $ 11 Status $13 Year $ 15-16          Section $ 18 Score 20-21 FinalGrade 23-24;    datalines; Abbott    F 2 97 A 90 87 Branford  M 1 98 A 92 97 Crandell  M 2 98 B 81 71 Dennison  M 1 97 A 85 72 Edgar     F 1 98 B 89 80 Faust     M 1 97 B 78 73 Greeley   F 2 97 A 82 91 Hart      F 1 98 B 84 80 Isley     M 2 97 A 88 86 Jasper    M 1 97 B 91 93 Charly    M 1    B 90 90 Sandra    F 2 98   95 88 ; run; proc sort data=Grade out=GradeBySection;    by section; run; /****** PROC MEANS *******/ proc means data=GradeBySection missing noprint chartype;    by Section;    var Score FinalGrade;    class Status Year;    output out=Want_Means sum=; run; proc sort data=Want_Means;   by Section Status Year _TYPE_; run; /******* PROC SQL  *******/ proc sql noprint;   create view type11 as   select distinct Section, Status, Year, '11' as _TYPE_,       count(*) as _FREQ_, sum(Score) as Score, sum(FinalGrade) as FinalGrade   from grade   group by Section, Status, Year;   create view type10 as   select distinct Section, Status, '  ' as Year, '10' as _TYPE_,       count(*) as _FREQ_, sum(Score) as Score, sum(FinalGrade) as FinalGrade   from grade   group by Section, Status;   create view type01 as   select distinct Section, ' ' as Status, Year, '01' as _TYPE_,       count(*) as _FREQ_, sum(Score) as Score, sum(FinalGrade) as FinalGrade   from grade   group by Section, year;   create view type00 as   select distinct Section, ' ' as Status, '  ' as Year, '00' as _TYPE_,       count(*) as _FREQ_, sum(Score) as Score, sum(FinalGrade) as FinalGrade   from grade   group by Section;   create table Want_SQL as   select * from type11   union all   select * from type10   union all   select * from type01   union all   select * from type00   order by 1,2,3,4; quit; /****** Compare the results *******************/ proc compare data=Want_Means compare=Want_SQL; run; I hope this helps, CTorres ... View more

The same code works OK with the new supposition: if all values of PWPUMAS are the same then MAX(PWPUMAS) is this value for each IN_PUMA_ID You can also use the following code assuming both files are sorted by IN_PUMA_ID and PWPUMAS has the same value for each IN_PUMA_ID: Data new;   merge Agearank (in=in_rank) Agea (keep=IN_PUMA_ID PWPUMAS);   by IN_PUMA_ID;   if in_rank; run; CTorres ... View more