IMO you should not have to do this "complex" transformation from a text field to another text field if you use SAS Dates with formats: From text to text (your solution): data final;   date_hoc="20140202";    /* text field */ run; proc sql; create table Report as select   Put(mdy(input(substr(strip(put(DATE_HOC,$10.)),5,2),2.),input(substr(strip(put(DATE_HOC,$10.)),7),2.),input(substr(strip(put(DATE_HOC,$10.)),1,4),4.)),date9.) as Date_Hoc from final; quit; From numeric field to SAS Date (number) - my suggestion : data final;   date_hoc=20140202;  /* numeric field */ run; proc sql; create table Report as select   input(DATE_HOC,yymmdd8.) as Date_Hoc format date9.   /* SAS date */ from final; quit; The advantage of a SAS Date is that you can display it in many ways using different formats and also you can get more information from the date using functions as YEAR, MONTH, DAY, etc. CTorres ... View more

Please provide the libname statement you are using. Make sure you are using the engine ORACLE: LIBNAME oralib ORACLE  PATH=path  SCHEMA=schema  USER=user  PASSWORD="password" ; ... View more

I agree with RW9: using where instead of If when possible is better. Anyway, the correct syntax of the if statement would be: if pay_code EQ '1001' or pay_code EQ '1002' or pay_code EQ '1003' or pay_code EQ '5567'; CTorres ... View more

I developed other solution and I got the same result gotten by Xia-Keshan: It can be easily generalized includying more teams in the Array and updating the do's.  I assume a null value of winner when the result is a draw: data games;   infile cards truncover;   input date date9. team1 $ team2 $ winner $ ;   format date date9.; cards; 01jan2014 Team_A Team_B Team_A 05jan2014 Team_B Team_C Team_B 06jan2014 Team_C Team_A ; run; data winn_loss(drop=team:);   set games;   if winner = ' ' then do;      winner=team1;      losser=team1;   end;   else if winner = team1 then do;           losser=team2;        end;        else do;           winner=team2;           losser=team1;        end; run; data want(drop=i: pot:);   set winn_loss;   array team[3] Team_A Team_B Team_C (3*1000);   i_winn=0;   i_loss=0;   do i=1 to 3 while (i_winn=0);      if vinarrayx(winner) and vname(team)=winner then i_winn=i;   end;   do i=1 to 3 while (i_loss=0);      if vinarrayx(losser) and vname(team)=losser then i_loss=i;   end;   pot_win=round(team[i_winn]*0.05);   pot_los=round(team[i_loss]*0.05);   team[i_winn]=team[i_winn]+pot_los;   team[i_loss]=team[i_loss]-pot_los; run; CTorres ... View more

This is the result table:            date dummy2008 dummy2010 dummy2013 1 13/10/2008 1 0 0 2 01/01/2010 0 1 0 3 23/06/2013 0 0 1 4 13/10/2013 0 0 1 CTorres ... View more

Hi Ilikesas, Yes, maybe the PROC TRANSPOSE is not the rigth tool to solve your problem. Anyway, you can use the LET option to "allows duplicate values of an ID variable. PROC TRANSPOSE transposes the observation that contains the last occurrence of a particular ID value within the data set or BY group.". Check the following code witch includes two additional dates: one is duplicated and the other belongs to the same year. In this case the dates must be sorted. Maybe this is what you need: data have;   input date ddmmyy10.;   format date ddmmyy10.;   year=year(date);   N=1;   cards; 13/10/2008 01/01/2010 01/01/2010   <--- duplicated 23/06/2013 13/10/2013   <--- same year ; run; proc transpose data=have out=want(drop=_name_) let prefix=dummy;   by date;   id year;   var N; run; SAS Log: 120  data have; 121    input date ddmmyy10.; 122    format date ddmmyy10.; 123    year=year(date); 124    N=1; 125    cards; NOTE: The data set WORK.HAVE has 5 observations and 3 variables. NOTE: DATA statement used (Total process time):       real time           0.00 seconds       cpu time            0.00 seconds 131  ; 132  run; 133  proc transpose data=have out=want(drop=_name_) let prefix=dummy; 134    by date; 135    id year; 136    var N; 137  run; WARNING: The ID value "dummy2010" occurs twice in the same BY group. NOTE: The above message was for the following BY group:       date=01/01/2010 NOTE: There were 5 observations read from the data set WORK.HAVE. NOTE: The data set WORK.WANT has 4 observations and 4 variables. NOTE: PROCEDURE TRANSPOSE used (Total process time):       real time           0.00 seconds       cpu time            0.00 seconds CTorres ... View more

Hi Ilikesas, Although irrelevant at this point, the variation of my answer would be as follows: option missing=0; data have;   input id category $;   N=1;   cards; 01 A  02 B ; run; proc transpose data=have out=want(drop=_name_) prefix=dummy;   by ID;   id category;   copy category;   var N; run; CTorres ... View more

Try this: option missing=0; data have;   input date ddmmyy10.;   format date ddmmyy10.;   cards; 01/01/2010 23/06/2013 13/10/2008 ; run; data temp;   set have;   year=year(date);   N=1; run; proc transpose data=temp out=want(drop=_name_) prefix=dummy;   by date notsorted;   id year;   var N; run; CTorres ... View more