I have a file it is combination of some columns a,b,c,d,e . but i imported the file and then created a column in sam1  my output is like should be    account a1 b1 c1 d1 e1 reson  125422114 520 90 88 90 22 a1|b1|c1|d1|e1 1259852421 570 90   90 22 a1|b1||d1|e1 9987458 417 57 44 20 45 a1|b1|c1|d1|e1   Here my final required output is reason1 has values in reson a1 & b1 are  'Old_Var'  values in reson c1,d1 & e1 are 'New_Var' if  reson in   a1 or b1 and c1 or d or e1 then it would be 'Old&New Var' if reson any one in a1 or b1 then it would be 'Old Var' in to new variable. Please help to create a variable by finding the reson values.   proc import datafile='C:\Users\HP\Desktop\datasamplecol.xls' out=sam dbms=xls replace; run; data sam1; set sam; if a1 then a11='a1'; if b1 then b11='b1'; if c1 then c11='c1'; if d1 then d11='d1'; if e1 then e11='e1'; reson=compress(a11 || b11 || c11 || d11 || e11 ) ; run; proc sql; create table sam2  as select *, (case when reson contains ('a1') or reson contains ('b1') and reson contains ('c1') or reson contains ('d1') or reson contains ('e1') then 'Old & New var' when reson contains ('c') or reson contains ('d') or reson contains ('e') then 'New Var' when reson contains ('a') or reson contains ('b')then 'Old Var' else ' ' end) as reason from sam1; run;     ... View more

data ds; infile datalines; input name$ a$ b$ c$ d$ e$ f$; datalines; vnod yes no no no no yes jag no yes no yes no yes raki yes yes yes yes yes no ; run; data ds; infile datalines; input name$ a$ b$ c$ d$ e$ f$; datalines; vnod yes no no no no yes jag no yes no yes no yes raki yes yes yes yes yes no ; run; i need this dataet as output:  name    a      b     c     d      e    f       count(yes) vnod   yes    no    no   no   no   yes     2 jag      no     yes    no  yes   no  yes    3 raki     yes   yes   yes  yes  yes  no     5   i need to create a column count the  row wise 'yes' from a to f columns.  kindly help me. Thank  you   ... View more

data ds; infile datalines ; input id 5. name&$20. age 3. sex$7. sal 5.; datalines; 1002 sarvesh ranjani 30 male 32000 1006 radhe govinda swamy 30 female 30000 1047 yagna prajna shohel 52 male 32200 1098 keerthana gowsami 32 female 12000 ; run; data ds; infile datalines ; input id 5. name&$20. age 3. sex$7. sal 5.; datalines; 1002 sarvesh ranjani 30 male 32000 1006 radhe govinda swamy 30 female 30000 1047 yagna prajna shohel 52 male 32200 1098 keerthana gowsami 32 female 12000 ; run; 171 data ds; 172 infile datalines ; 173 input id 5. name&$20. age 3. sex$7. sal 5.; 174 datalines; NOTE: Invalid data for sal in line 175 33-37. RULE: ----+----1----+----2----+----3----+----4----+----5----+----6----+----7----+----8----+--- 175 1002 sarvesh ranjani 30 male 32000 id=1002 name=sarvesh ranjani age=. sex=30 mal sal=. _ERROR_=1 _N_=1 NOTE: Invalid data for age in line 176 30-32. 176 1006 radhe govinda swamy 30 female 30000 id=1006 name=radhe govinda swamy age=. sex=ale 300 sal=0 _ERROR_=1 _N_=2 NOTE: Invalid data for age in line 177 30-32. 177 1047 yagna prajna shohel 52 male 32200 id=1047 name=yagna prajna shohel age=. sex=e 322 sal=0 _ERROR_=1 _N_=3 NOTE: Invalid data for sal in line 178 35-39. 178 1098 keerthana gowsami 32 female 12000 id=1098 name=keerthana gowsami age=32 sex=femal sal=. _ERROR_=1 _N_=4 NOTE: The data set WORK.DS has 4 observations and 5 variables. NOTE: DATA statement used (Total process time): real time 0.01 seconds cpu time 0.01 seconds 179 ; 180 run;   ... View more