About ak2011

ak2011 · ‎11-29-2019

Thanks. I would recheck my SAS code.

ak2011 · ‎11-29-2019

Thanks. I would recheck my code to see if there are no errors.

ak2011 · ‎11-29-2019

Thanks for your response.

ak2011 · ‎11-29-2019

Thanks very much for your time. Your code works fine with the smaller dataset but there is still a problem with the flag(count)=idchem_char; Please read log below: 1 OPTIONS NONOTES NOSTIMER NOSOURCE NOSYNTAXCHECK; 72 73 74 /* MACRO APPROACH*/ 75 76 libname multi'/folders/myfolders/multisitedata'; NOTE: Libref MULTI refers to the same physical library as _TEMP3. NOTE: Libref MULTI was successfully assigned as follows: Engine: V9 Physical Name: /folders/myfolders/multisitedata 77 78 data idnew1(keep=id job idchem idchem_char id_job); 79 set multi.multiworkchempostauto; NOTE: Data file MULTI.MULTIWORKCHEMPOSTAUTO.DATA is in a format that is native to another host, or the file encoding does not match the session encoding. Cross Environment Data Access will be used, which might require additional CPU resources and might reduce performance. 80 /*length idchem_char $7;*/ 81 id_job=catx('_', id, job); 82 83 if idchem = 990005 then idchem_char = 'cla_exp'; 84 else if idchem = 990021 then idchem_char = 'bio_exp'; 85 else if idchem = 520299 then idchem_char = 'ali_exp'; 86 else if idchem = 420204 then idchem_char = 'iso_exp'; /* to adapt */ 87 88 else if idchem = 430101 then idchem_char = 'ben_exp'; 89 else if idchem = 430103 then idchem_char = 'xyl_exp'; 90 else if idchem = 430102 then idchem_char = 'tol_exp'; 91 else if idchem = 430104 then idchem_char = 'sty_exp'; /* to adapt */ 92 93 else if idchem = 460003 then idchem_char = 'sol_exp'; 94 else if idchem = 220501 then idchem_char = 'for_exp'; 95 else if idchem = 510004 then idchem_char = 'hyp_exp'; 96 else if idchem = 210701 then idchem_char = 'amo_exp'; /* to adapt */ 97 98 99 else if idchem = 211700 then idchem_char = 'chl_exp'; 100 else if idchem = 410002 then idchem_char = 'cau_exp'; 101 else if idchem = 411501 then idchem_char = 'pho_exp'; 102 else if idchem = 420401 then idchem_char = 'ace_exp'; /* to adapt */ 103 104 else if idchem = 211701 then idchem_char = 'hcl_exp'; 105 else if idchem = 460004 then idchem_char = 'wpo_exp'; /* to adapt */ 106 run; NOTE: There were 124695 observations read from the data set MULTI.MULTIWORKCHEMPOSTAUTO. NOTE: The data set WORK.IDNEW1 has 124695 observations and 5 variables. NOTE: DATA statement used (Total process time): real time 1.46 seconds cpu time 1.20 seconds 107 108 109 110 111 /* 1. Generate macrovariables */ 112 113 113 ! proc sql noprint; 114 /* Retrieve the list of distinct idchems (num) in a macrovariable : &list_idchem */ 115 select distinct idchem into:list_idchem separated by " " from idnew1; 116 /* Retrieve the list of distinct idchems (format) in a macrovariable : &list_idchem_char */ 117 select distinct idchem_char into:list_idchem_char separated by " " from idnew1; 118 /* Retrieve the number of distinct idchems in a macrovariable : &count_idchem */ 119 select count(distinct idchem_char) into:count_idchem trimmed from idnew1; 120 quit; NOTE: PROCEDURE SQL used (Total process time): real time 0.44 seconds cpu time 0.53 seconds 121 122 122 ! data _null_; 123 length temp $2000; 124 temp=cat('"',tranwrd(strip("&list_idchem_char")," ",'" "'),'"'); 125 call symput('list_idchem_char_q',temp); 126 run; NOTE: DATA statement used (Total process time): real time 0.00 seconds cpu time 0.00 seconds 127 128 %put &list_idchem; 110001 110002 110004 110005 110007 110008 110009 110010 110011 110012 110013 110014 110015 110016 110017 110018 110019 110020 110021 110024 110025 110026 110028 110029 110030 110033 110501 111101 111102 111110 111301 111303 111401 111501 111600 112001 112002 112003 112005 112201 112400 112600 112601 112800 112900 113000 113001 114800 115000 118200 118201 118204 118205 130001 130101 140001 140002 140003 140004 140005 140006 140007 140008 140009 140010 140012 140013 140014 140015 140016 140017 140018 145001 150001 150002 150007 150008 150009 150010 150011 150012 150013 150014 150015 150016 150017 150018 150019 150020 150022 150023 150024 150025 150026 150027 150028 150029 150030 160001 170001 170002 170003 170004 170005 170006 170008 170009 201602 210100 210601 210602 210701 210703 210801 210901 211601 211602 211700 211701 211702 220001 220101 220102 220501 220603 221101 221102 221103 221301 225001 260001 260002 270001 310001 310002 310003 310004 311201 311301 312001 312201 312401 312501 312601 312801 312901 313001 314701 314801 315001 317901 318201 370001 370002 370004 370005 370006 370008 370009 370010 370011 370012 370013 370014 370015 370016 410001 410002 410003 410005 410704 410802 411501 411603 418000 420001 420002 420201 420202 420203 420204 420205 420303 420401 420403 420602 420701 420702 420801 420802 420803 420804 421001 421101 421302 421303 421404 421501 430101 430102 430103 430104 430201 430701 440001 440002 440003 440501 460002 460003 460004 460005 460006 460007 460008 460009 460011 460012 460013 460014 460015 460017 460019 460022 460025 460026 460027 460029 460030 460031 470001 470002 470003 470005 510001 510002 510003 510004 510005 510499 511299 511399 512299 512399 512499 512599 512699 512799 512899 512999 513099 513399 513499 514799 514899 515099 515199 515299 517499 517999 518099 518299 520197 520198 520199 520299 520599 520899 521199 521399 521499 521599 521699 521999 530193 530194 530195 530196 530197 530198 530199 530299 530399 531799 531899 890001 890002 890003 990005 990007 990008 990009 990012 990013 990014 990021 990022 129 %put &list_idchem_char; ace_exp ali_exp amo_exp ben_exp bio_exp cau_exp chl_exp cla_exp for_exp hcl_exp hyp_exp iso_exp pho_exp sol_exp sty_exp tol_exp wpo_exp xyl_exp 130 %put &list_idchem_char_q; "ace_exp" "ali_exp" "amo_exp" "ben_exp" "bio_exp" "cau_exp" "chl_exp" "cla_exp" "for_exp" "hcl_exp" "hyp_exp" "iso_exp" "pho_exp" "sol_exp" "sty_exp" "tol_exp" "wpo_exp" "xyl_exp" 131 %put &count_idchem; 18 132 133 /* 2. Transpose data and concatenate idchem */ 134 135 proc sort data=idnew1; 136 by id_job; 137 run; NOTE: There were 124695 observations read from the data set WORK.IDNEW1. NOTE: The data set WORK.IDNEW1 has 124695 observations and 5 variables. NOTE: PROCEDURE SORT used (Total process time): real time 0.38 seconds cpu time 0.39 seconds 138 139 data idnew_tr; 140 set idnew1; 141 142 array flag(&count_idchem) $ _temporary_; 143 by id_job; 144 retain flag; 145 146 if first.id_job then do; 147 count=0; 148 call missing(of flag(*)); 149 end; 150 151 count+1; 152 153 /*do i=1 to dim(flag);*/ 154 flag(count)=idchem_char; 155 /*end;*/ 156 157 idchem_list = catx(" ", of flag(*)); 158 if last.id_job then output; 159 160 drop count idchem idchem_char id job; 161 162 163 run; ERROR: Array subscript out of range at line 154 column 1. id=OSaa03 job=4 idchem=460013 id_job=OSaa03_4 idchem_char= FIRST.id_job=0 LAST.id_job=0 count=19 idchem_list= _ERROR_=1 _N_=54 NOTE: The SAS System stopped processing this step because of errors. NOTE: There were 55 observations read from the data set WORK.IDNEW1. WARNING: The data set WORK.IDNEW_TR may be incomplete. When this step was stopped there were 7 observations and 2 variables. WARNING: Data set WORK.IDNEW_TR was not replaced because this step was stopped. NOTE: DATA statement used (Total process time): real time 0.02 seconds cpu time 0.04 seconds 164 165 OPTIONS NONOTES NOSTIMER NOSOURCE NOSYNTAXCHECK; 177 ak.

ak2011 · ‎11-29-2019

Perfect! It works! Thanks very much!

ak2011 · ‎11-27-2019

Hi, May I please know the SAS code to place zeros under ali_exp and iso_exp variables ( in the merged file) of the attached file? I was expecting SAS to place zeros there since it is either exposed(1) or not exposed(0). Thanks. /* Reading 6 different idchems data*/ data t1; input id$ job idchem; datalines; os1 1 990005 os1 1 990021 os1 1 211700 os1 2 211700 os1 2 990021 os1 2 210701 os1 2 990005 os2 1 210701 os2 1 990005 os2 2 990021 os2 3 210701 os2 3 990005 os3 3 210701 os3 1 211700 os4 1 210701 os4 1 990005 os4 1 211700 os5 1 520299 os5 1 420204 os6 2 520299 os6 3 420204 os6 4 990005 os7 1 520299 ; run; 1 OPTIONS NONOTES NOSTIMER NOSOURCE NOSYNTAXCHECK; 72 73 74 /* Reading 6 different idchems data*/ 75 data t1; 76 input id$ job idchem; 77 datalines; NOTE: The data set WORK.T1 has 23 observations and 3 variables. NOTE: DATA statement used (Total process time): real time 0.01 seconds cpu time 0.01 seconds 101 ; 102 run; 103 proc print; run; NOTE: There were 23 observations read from the data set WORK.T1. NOTE: PROCEDURE PRINT used (Total process time): real time 0.20 seconds cpu time 0.20 seconds 104 105 /* 1st part of work*/ 106 data t1p1; 107 set t1; 108 if idchem ne 990005 and idchem ne 990021 and idchem ne 210701 and idchem ne 211700 then delete; run; NOTE: There were 23 observations read from the data set WORK.T1. NOTE: The data set WORK.T1P1 has 18 observations and 3 variables. NOTE: DATA statement used (Total process time): real time 0.01 seconds cpu time 0.02 seconds 109 110 /*TRANSPOSING VARIABLES*/ 111 112 proc sort data=t1p1; by id job; NOTE: There were 18 observations read from the data set WORK.T1P1. NOTE: The data set WORK.T1P1 has 18 observations and 3 variables. NOTE: PROCEDURE SORT used (Total process time): real time 0.01 seconds cpu time 0.01 seconds 113 proc transpose data=t1p1 out=t1p1b prefix=idchem; 114 by id job; 115 var idchem; 116 run; NOTE: There were 18 observations read from the data set WORK.T1P1. NOTE: The data set WORK.T1P1B has 9 observations and 7 variables. NOTE: PROCEDURE TRANSPOSE used (Total process time): real time 0.02 seconds cpu time 0.03 seconds 117 118 /*cla*/ 119 data clan; 120 set t1p1b; 121 if idchem1=990005 or idchem2=990005 or idchem3=990005 or idchem4=990005 then cla_exp=1; 122 else cla_exp=0; 123 put _all_; run; id=os1 job=1 _NAME_=idchem idchem1=990005 idchem2=990021 idchem3=211700 idchem4=. cla_exp=1 _ERROR_=0 _N_=1 id=os1 job=2 _NAME_=idchem idchem1=211700 idchem2=990021 idchem3=210701 idchem4=990005 cla_exp=1 _ERROR_=0 _N_=2 id=os2 job=1 _NAME_=idchem idchem1=210701 idchem2=990005 idchem3=. idchem4=. cla_exp=1 _ERROR_=0 _N_=3 id=os2 job=2 _NAME_=idchem idchem1=990021 idchem2=. idchem3=. idchem4=. cla_exp=0 _ERROR_=0 _N_=4 id=os2 job=3 _NAME_=idchem idchem1=210701 idchem2=990005 idchem3=. idchem4=. cla_exp=1 _ERROR_=0 _N_=5 id=os3 job=1 _NAME_=idchem idchem1=211700 idchem2=. idchem3=. idchem4=. cla_exp=0 _ERROR_=0 _N_=6 id=os3 job=3 _NAME_=idchem idchem1=210701 idchem2=. idchem3=. idchem4=. cla_exp=0 _ERROR_=0 _N_=7 id=os4 job=1 _NAME_=idchem idchem1=210701 idchem2=990005 idchem3=211700 idchem4=. cla_exp=1 _ERROR_=0 _N_=8 id=os6 job=4 _NAME_=idchem idchem1=990005 idchem2=. idchem3=. idchem4=. cla_exp=1 _ERROR_=0 _N_=9 NOTE: There were 9 observations read from the data set WORK.T1P1B. NOTE: The data set WORK.CLAN has 9 observations and 8 variables. NOTE: DATA statement used (Total process time): real time 0.01 seconds cpu time 0.01 seconds 124 proc print; 125 Title "cla exposure"; 126 run; NOTE: There were 9 observations read from the data set WORK.CLAN. NOTE: PROCEDURE PRINT used (Total process time): real time 0.26 seconds cpu time 0.26 seconds 127 128 /*%ge id-job-Cla*/ 129 proc freq data=clan; 130 table cla_exp; 131 run; NOTE: There were 9 observations read from the data set WORK.CLAN. NOTE: PROCEDURE FREQ used (Total process time): real time 0.15 seconds cpu time 0.14 seconds 132 133 134 /*Bio*/ 135 data bion; 136 set t1p1b; 137 if idchem1=990021 or idchem2=990021 or idchem3=990021 or idchem4=990021 then bio_exp=1; else bio_exp=0; 138 id_job=catx('_', id, job); 139 put _all_;run; id=os1 job=1 _NAME_=idchem idchem1=990005 idchem2=990021 idchem3=211700 idchem4=. bio_exp=1 id_job=os1_1 _ERROR_=0 _N_=1 id=os1 job=2 _NAME_=idchem idchem1=211700 idchem2=990021 idchem3=210701 idchem4=990005 bio_exp=1 id_job=os1_2 _ERROR_=0 _N_=2 id=os2 job=1 _NAME_=idchem idchem1=210701 idchem2=990005 idchem3=. idchem4=. bio_exp=0 id_job=os2_1 _ERROR_=0 _N_=3 id=os2 job=2 _NAME_=idchem idchem1=990021 idchem2=. idchem3=. idchem4=. bio_exp=1 id_job=os2_2 _ERROR_=0 _N_=4 id=os2 job=3 _NAME_=idchem idchem1=210701 idchem2=990005 idchem3=. idchem4=. bio_exp=0 id_job=os2_3 _ERROR_=0 _N_=5 id=os3 job=1 _NAME_=idchem idchem1=211700 idchem2=. idchem3=. idchem4=. bio_exp=0 id_job=os3_1 _ERROR_=0 _N_=6 id=os3 job=3 _NAME_=idchem idchem1=210701 idchem2=. idchem3=. idchem4=. bio_exp=0 id_job=os3_3 _ERROR_=0 _N_=7 id=os4 job=1 _NAME_=idchem idchem1=210701 idchem2=990005 idchem3=211700 idchem4=. bio_exp=0 id_job=os4_1 _ERROR_=0 _N_=8 id=os6 job=4 _NAME_=idchem idchem1=990005 idchem2=. idchem3=. idchem4=. bio_exp=0 id_job=os6_4 _ERROR_=0 _N_=9 NOTE: There were 9 observations read from the data set WORK.T1P1B. NOTE: The data set WORK.BION has 9 observations and 9 variables. NOTE: DATA statement used (Total process time): real time 0.01 seconds cpu time 0.02 seconds 140 proc print; 141 Title "bio exposure"; 142 run; NOTE: There were 9 observations read from the data set WORK.BION. NOTE: PROCEDURE PRINT used (Total process time): real time 0.13 seconds cpu time 0.13 seconds 143 144 145 /*%ge id-job-bio*/ 146 proc freq data=bion; 147 table bio_exp; 148 run; NOTE: There were 9 observations read from the data set WORK.BION. NOTE: PROCEDURE FREQ used (Total process time): real time 0.10 seconds cpu time 0.09 seconds 149 150 151 /* amo*/ 152 data amon; 153 set t1p1b; 154 if idchem1=210701 or idchem2=210701 or idchem3=210701 or idchem4=210701 then amo_exp=1; else amo_exp=0; 155 id_job=catx('_', id, job); 156 put _all_;run; id=os1 job=1 _NAME_=idchem idchem1=990005 idchem2=990021 idchem3=211700 idchem4=. amo_exp=0 id_job=os1_1 _ERROR_=0 _N_=1 id=os1 job=2 _NAME_=idchem idchem1=211700 idchem2=990021 idchem3=210701 idchem4=990005 amo_exp=1 id_job=os1_2 _ERROR_=0 _N_=2 id=os2 job=1 _NAME_=idchem idchem1=210701 idchem2=990005 idchem3=. idchem4=. amo_exp=1 id_job=os2_1 _ERROR_=0 _N_=3 id=os2 job=2 _NAME_=idchem idchem1=990021 idchem2=. idchem3=. idchem4=. amo_exp=0 id_job=os2_2 _ERROR_=0 _N_=4 id=os2 job=3 _NAME_=idchem idchem1=210701 idchem2=990005 idchem3=. idchem4=. amo_exp=1 id_job=os2_3 _ERROR_=0 _N_=5 id=os3 job=1 _NAME_=idchem idchem1=211700 idchem2=. idchem3=. idchem4=. amo_exp=0 id_job=os3_1 _ERROR_=0 _N_=6 id=os3 job=3 _NAME_=idchem idchem1=210701 idchem2=. idchem3=. idchem4=. amo_exp=1 id_job=os3_3 _ERROR_=0 _N_=7 id=os4 job=1 _NAME_=idchem idchem1=210701 idchem2=990005 idchem3=211700 idchem4=. amo_exp=1 id_job=os4_1 _ERROR_=0 _N_=8 id=os6 job=4 _NAME_=idchem idchem1=990005 idchem2=. idchem3=. idchem4=. amo_exp=0 id_job=os6_4 _ERROR_=0 _N_=9 NOTE: There were 9 observations read from the data set WORK.T1P1B. NOTE: The data set WORK.AMON has 9 observations and 9 variables. NOTE: DATA statement used (Total process time): real time 0.01 seconds cpu time 0.01 seconds 157 proc print data=amon; 158 Title "amo exposure"; 159 run; NOTE: There were 9 observations read from the data set WORK.AMON. NOTE: PROCEDURE PRINT used (Total process time): real time 0.15 seconds cpu time 0.16 seconds 160 161 /*%ge id-job-amo*/ 162 proc freq data=amon; 163 table amo_exp; 164 run; NOTE: There were 9 observations read from the data set WORK.AMON. NOTE: PROCEDURE FREQ used (Total process time): real time 0.10 seconds cpu time 0.09 seconds 165 166 /* chl*/ 167 data chln; 168 set t1p1b; 169 if idchem1=211700 or idchem2=211700 or idchem3=211700 or idchem4=211700 then chl_exp=1; else chl_exp=0; 170 id_job=catx('_', id, job); 171 put _all_; run; id=os1 job=1 _NAME_=idchem idchem1=990005 idchem2=990021 idchem3=211700 idchem4=. chl_exp=1 id_job=os1_1 _ERROR_=0 _N_=1 id=os1 job=2 _NAME_=idchem idchem1=211700 idchem2=990021 idchem3=210701 idchem4=990005 chl_exp=1 id_job=os1_2 _ERROR_=0 _N_=2 id=os2 job=1 _NAME_=idchem idchem1=210701 idchem2=990005 idchem3=. idchem4=. chl_exp=0 id_job=os2_1 _ERROR_=0 _N_=3 id=os2 job=2 _NAME_=idchem idchem1=990021 idchem2=. idchem3=. idchem4=. chl_exp=0 id_job=os2_2 _ERROR_=0 _N_=4 id=os2 job=3 _NAME_=idchem idchem1=210701 idchem2=990005 idchem3=. idchem4=. chl_exp=0 id_job=os2_3 _ERROR_=0 _N_=5 id=os3 job=1 _NAME_=idchem idchem1=211700 idchem2=. idchem3=. idchem4=. chl_exp=1 id_job=os3_1 _ERROR_=0 _N_=6 id=os3 job=3 _NAME_=idchem idchem1=210701 idchem2=. idchem3=. idchem4=. chl_exp=0 id_job=os3_3 _ERROR_=0 _N_=7 id=os4 job=1 _NAME_=idchem idchem1=210701 idchem2=990005 idchem3=211700 idchem4=. chl_exp=1 id_job=os4_1 _ERROR_=0 _N_=8 id=os6 job=4 _NAME_=idchem idchem1=990005 idchem2=. idchem3=. idchem4=. chl_exp=0 id_job=os6_4 _ERROR_=0 _N_=9 NOTE: There were 9 observations read from the data set WORK.T1P1B. NOTE: The data set WORK.CHLN has 9 observations and 9 variables. NOTE: DATA statement used (Total process time): real time 0.01 seconds cpu time 0.01 seconds 172 173 proc print data=chln; 174 Title"chl exposure"; 175 run; NOTE: There were 9 observations read from the data set WORK.CHLN. NOTE: PROCEDURE PRINT used (Total process time): real time 0.15 seconds cpu time 0.15 seconds 176 177 /*%ge id-job-chl*/ 178 proc freq data=chln; 179 table chl_exp; 180 run; NOTE: There were 9 observations read from the data set WORK.CHLN. NOTE: PROCEDURE FREQ used (Total process time): real time 0.11 seconds cpu time 0.10 seconds 181 182 183 /*2nd part of work*/ 184 data t2; 185 set t1; 186 if idchem ne 520299 and idchem ne 420204 then delete; run; NOTE: There were 23 observations read from the data set WORK.T1. NOTE: The data set WORK.T2 has 5 observations and 3 variables. NOTE: DATA statement used (Total process time): real time 0.04 seconds cpu time 0.04 seconds 187 proc sort data=t2; by id job; NOTE: There were 5 observations read from the data set WORK.T2. NOTE: The data set WORK.T2 has 5 observations and 3 variables. NOTE: PROCEDURE SORT used (Total process time): real time 0.04 seconds cpu time 0.04 seconds 188 proc transpose data=t2 out=t2b prefix=idchem; 189 by id job; 190 /*id job;*/ 191 var idchem; 192 run; NOTE: There were 5 observations read from the data set WORK.T2. NOTE: The data set WORK.T2B has 4 observations and 5 variables. NOTE: PROCEDURE TRANSPOSE used (Total process time): real time 0.02 seconds cpu time 0.02 seconds 193 194 /*ali*/ 195 data alin; 196 set t2b; 197 if idchem1= 520299 or idchem2=520299 then ali_exp=1; 198 else ali_exp=0; 199 id_job=catx('_', id, job); 200 put _all_; 201 run; id=os5 job=1 _NAME_=idchem idchem1=520299 idchem2=420204 ali_exp=1 id_job=os5_1 _ERROR_=0 _N_=1 id=os6 job=2 _NAME_=idchem idchem1=520299 idchem2=. ali_exp=1 id_job=os6_2 _ERROR_=0 _N_=2 id=os6 job=3 _NAME_=idchem idchem1=420204 idchem2=. ali_exp=0 id_job=os6_3 _ERROR_=0 _N_=3 id=os7 job=1 _NAME_=idchem idchem1=520299 idchem2=. ali_exp=1 id_job=os7_1 _ERROR_=0 _N_=4 NOTE: There were 4 observations read from the data set WORK.T2B. NOTE: The data set WORK.ALIN has 4 observations and 7 variables. NOTE: DATA statement used (Total process time): real time 0.02 seconds cpu time 0.01 seconds 202 proc print data=alin; 203 Title "ali exposure"; 204 run; NOTE: There were 4 observations read from the data set WORK.ALIN. NOTE: PROCEDURE PRINT used (Total process time): real time 0.11 seconds cpu time 0.10 seconds 205 206 /*%ge id-job-ali*/ 207 proc freq data=alin; 208 table ali_exp; 209 run; NOTE: There were 4 observations read from the data set WORK.ALIN. NOTE: PROCEDURE FREQ used (Total process time): real time 0.11 seconds cpu time 0.09 seconds 210 211 212 /*iso exposure*/ 213 data ison; 214 set t2b; 215 if idchem1=420204 or idchem2=420204 then iso_exp=1; 216 else iso_exp=0; 217 id_job=catx('_', id, job); 218 put _all_; 219 run; id=os5 job=1 _NAME_=idchem idchem1=520299 idchem2=420204 iso_exp=1 id_job=os5_1 _ERROR_=0 _N_=1 id=os6 job=2 _NAME_=idchem idchem1=520299 idchem2=. iso_exp=0 id_job=os6_2 _ERROR_=0 _N_=2 id=os6 job=3 _NAME_=idchem idchem1=420204 idchem2=. iso_exp=1 id_job=os6_3 _ERROR_=0 _N_=3 id=os7 job=1 _NAME_=idchem idchem1=520299 idchem2=. iso_exp=0 id_job=os7_1 _ERROR_=0 _N_=4 NOTE: There were 4 observations read from the data set WORK.T2B. NOTE: The data set WORK.ISON has 4 observations and 7 variables. NOTE: DATA statement used (Total process time): real time 0.01 seconds cpu time 0.01 seconds 220 proc print; 221 Title "iso exposure"; 222 223 /*%ge id-job-iso*/ NOTE: There were 4 observations read from the data set WORK.ISON. NOTE: PROCEDURE PRINT used (Total process time): real time 0.12 seconds cpu time 0.11 seconds 224 proc freq data=ison; 225 table iso_exp; 226 run; NOTE: There were 4 observations read from the data set WORK.ISON. NOTE: PROCEDURE FREQ used (Total process time): real time 0.10 seconds cpu time 0.09 seconds 227 228 /* Merging the 6 different idchem files*/ 229 230 data mn; merge clan bion amon chln alin ison; 231 drop _name_; 232 run; NOTE: There were 9 observations read from the data set WORK.CLAN. NOTE: There were 9 observations read from the data set WORK.BION. NOTE: There were 9 observations read from the data set WORK.AMON. NOTE: There were 9 observations read from the data set WORK.CHLN. NOTE: There were 4 observations read from the data set WORK.ALIN. NOTE: There were 4 observations read from the data set WORK.ISON. NOTE: The data set WORK.MN has 9 observations and 13 variables. NOTE: DATA statement used (Total process time): real time 0.02 seconds cpu time 0.02 seconds 233 234 proc print data=mn; 235 Title "Merged exposure files for cla ,bio, amo,chl,ali and iso pollutants"; 236 run; NOTE: There were 9 observations read from the data set WORK.MN. NOTE: PROCEDURE PRINT used (Total process time): real time 0.20 seconds cpu time 0.21 seconds 237 238 proc freq data=mn; 239 tables cla_exp*bio_exp; 240 tables cla_exp*amo_exp; 241 tables cla_exp*chl_exp; 242 tables bio_exp*cla_exp; 243 tables bio_exp*amo_exp; 244 tables bio_exp*chl_exp; 245 run; NOTE: There were 9 observations read from the data set WORK.MN. NOTE: PROCEDURE FREQ used (Total process time): real time 0.53 seconds cpu time 0.52 seconds 246 247 248 249 250 OPTIONS NONOTES NOSTIMER NOSOURCE NOSYNTAXCHECK; 262 Thanks in advance. ak.

ak2011 · ‎11-26-2019

Hi, I am working with a large dataset in SAS Studio with over 100,000 obs and I receive this warning from SAS: Maximum log size reached... I read SAS online documentation and someone suggested proc printo log= '/folders/myfolders/ak. log Comments/questions on this: 1. a.Will SAS create the ak.log file or I have to create it myself in SAS studio or any other drive out like "C" out of SAS studio? b. Can it be any extentions like .pdf or .doc for the printto statement or it is specifically .log 2. Should I write the printto statatement before or after reading the large dataset or before or after the proc print statement of the large dataset? Where exactly in the data steps should the proc printo statement be written? 3. I tried the proc printot statement before reading the large dataset and I received nothing in SAS log to see if there are errors, warnings or notes in my code. 4. a. If SAS Studio cannot effectively handle over 100,000 obs, do you think R can do that easily? ie. Will R also give the same warning like SAS Studio? b. Will regular SAS (not Studio) also give the same warning message if I were to use the same 100000+ records that I am using? Thanks in advance. ak.

ak2011 · ‎11-25-2019

I really appreciate your expert input! I am almost there:Comments(steps) #1 and 2 ok; afew things to resolve, however.: Warning: Not all variables are in list-list18. Is there a way I can correct the warning?Also steps 3 and 4 are difficult to process by SAS. It took quite a long time for #3 and for # 4, SAS has not been able to process it. I think the entire data with 18 idchems should be split into 2 or 3 for this macro approah for easy processing by SAS. I would be pleased if you could help me again (if possible) to split the data into 2 or 3. Thanks in advance for your help. ak. 1 OPTIONS NONOTES NOSTIMER NOSOURCE NOSYNTAXCHECK; 72 73 /* MACRO APPROACH*/ 74 75 libname multi'/folders/myfolders/multisitedata'; NOTE: Libref MULTI refers to the same physical library as _TEMP3. NOTE: Libref MULTI was successfully assigned as follows: Engine: V9 Physical Name: /folders/myfolders/multisitedata 76 77 data idnew1(keep=id job idchem idchem_char id_job); 78 set multi.multiworkchempostauto; NOTE: Data file MULTI.MULTIWORKCHEMPOSTAUTO.DATA is in a format that is native to another host, or the file encoding does not match the session encoding. Cross Environment Data Access will be used, which might require additional CPU resources and might reduce performance. 79 /*length idchem_char $7;*/ 80 id_job=catx('_', id, job); 81 82 if idchem = 990005 then idchem_char = 'cla_exp'; 83 else if idchem = 990021 then idchem_char = 'bio_exp'; 84 else if idchem = 520299 then idchem_char = 'ali_exp'; 85 else if idchem = 420204 then idchem_char = 'iso_exp'; /* to adapt */ 86 87 else if idchem = 430101 then idchem_char = 'ben_exp'; 88 else if idchem = 430103 then idchem_char = 'xyl_exp'; 89 else if idchem = 430102 then idchem_char = 'tol_exp'; 90 else if idchem = 430104 then idchem_char = 'sty_exp'; /* to adapt */ 91 92 else if idchem = 460003 then idchem_char = 'sol_exp'; 93 else if idchem = 220501 then idchem_char = 'for_exp'; 94 else if idchem = 510004 then idchem_char = 'hyp_exp'; 95 else if idchem = 210701 then idchem_char = 'amo_exp'; /* to adapt */ 96 97 98 else if idchem = 211700 then idchem_char = 'chl_exp'; 99 else if idchem = 410002 then idchem_char = 'cau_exp'; 100 else if idchem = 411501 then idchem_char = 'pho_exp'; 101 else if idchem = 420401 then idchem_char = 'ace_exp'; /* to adapt */ 102 103 else if idchem = 211701 then idchem_char = 'hcl_exp'; 104 else if idchem = 460004 then idchem_char = 'wpo_exp'; /* to adapt */ 105 run; NOTE: There were 124695 observations read from the data set MULTI.MULTIWORKCHEMPOSTAUTO. NOTE: The data set WORK.IDNEW1 has 124695 observations and 5 variables. NOTE: DATA statement used (Total process time): real time 1.43 seconds cpu time 1.22 seconds 106 107 108 109 110 /* 1. Generate macrovariables */ 111 112 112 ! proc sql noprint; 113 /* Retrieve the list of distinct idchems (num) in a macrovariable : &list_idchem */ 114 select distinct idchem into:list_idchem separated by " " from idnew1; 115 /* Retrieve the list of distinct idchems (format) in a macrovariable : &list_idchem_char */ 116 select distinct idchem_char into:list_idchem_char separated by " " from idnew1; 117 /* Retrieve the number of distinct idchems in a macrovariable : &count_idchem */ 118 select count(distinct idchem_char) into:count_idchem trimmed from idnew1; 119 quit; NOTE: PROCEDURE SQL used (Total process time): real time 0.46 seconds cpu time 0.55 seconds 120 121 121 ! data _null_; 122 length temp $2000; 123 temp=cat('"',tranwrd("&list_idchem_char"," ",'" "'),'"'); 124 call symput('list_idchem_char_q',temp); 125 run; NOTE: DATA statement used (Total process time): real time 0.00 seconds cpu time 0.01 seconds 126 127 %put &list_idchem; 110001 110002 110004 110005 110007 110008 110009 110010 110011 110012 110013 110014 110015 110016 110017 110018 110019 110020 110021 110024 110025 110026 110028 110029 110030 110033 110501 111101 111102 111110 111301 111303 111401 111501 111600 112001 112002 112003 112005 112201 112400 112600 112601 112800 112900 113000 113001 114800 115000 118200 118201 118204 118205 130001 130101 140001 140002 140003 140004 140005 140006 140007 140008 140009 140010 140012 140013 140014 140015 140016 140017 140018 145001 150001 150002 150007 150008 150009 150010 150011 150012 150013 150014 150015 150016 150017 150018 150019 150020 150022 150023 150024 150025 150026 150027 150028 150029 150030 160001 170001 170002 170003 170004 170005 170006 170008 170009 201602 210100 210601 210602 210701 210703 210801 210901 211601 211602 211700 211701 211702 220001 220101 220102 220501 220603 221101 221102 221103 221301 225001 260001 260002 270001 310001 310002 310003 310004 311201 311301 312001 312201 312401 312501 312601 312801 312901 313001 314701 314801 315001 317901 318201 370001 370002 370004 370005 370006 370008 370009 370010 370011 370012 370013 370014 370015 370016 410001 410002 410003 410005 410704 410802 411501 411603 418000 420001 420002 420201 420202 420203 420204 420205 420303 420401 420403 420602 420701 420702 420801 420802 420803 420804 421001 421101 421302 421303 421404 421501 430101 430102 430103 430104 430201 430701 440001 440002 440003 440501 460002 460003 460004 460005 460006 460007 460008 460009 460011 460012 460013 460014 460015 460017 460019 460022 460025 460026 460027 460029 460030 460031 470001 470002 470003 470005 510001 510002 510003 510004 510005 510499 511299 511399 512299 512399 512499 512599 512699 512799 512899 512999 513099 513399 513499 514799 514899 515099 515199 515299 517499 517999 518099 518299 520197 520198 520199 520299 520599 520899 521199 521399 521499 521599 521699 521999 530193 530194 530195 530196 530197 530198 530199 530299 530399 531799 531899 890001 890002 890003 990005 990007 990008 990009 990012 990013 990014 990021 990022 128 %put &list_idchem_char; ace_exp ali_exp amo_exp ben_exp bio_exp cau_exp chl_exp cla_exp for_exp hcl_exp hyp_exp iso_exp pho_exp sol_exp sty_exp tol_exp wpo_exp xyl_exp 129 %put &list_idchem_char_q; "" "ace_exp" "ali_exp" "amo_exp" "ben_exp" "bio_exp" "cau_exp" "chl_exp" "cla_exp" "for_exp" "hcl_exp" "hyp_exp" "iso_exp" "pho_exp" "sol_exp" "sty_exp" "tol_exp" "wpo_exp" "xyl_exp" 130 %put &count_idchem; 18 131 132 /* 2. Transpose data and concatenate idchem */ 133 134 proc sort data=idnew1; 135 by id_job; 136 run; NOTE: There were 124695 observations read from the data set WORK.IDNEW1. NOTE: The data set WORK.IDNEW1 has 124695 observations and 5 variables. NOTE: PROCEDURE SORT used (Total process time): real time 0.31 seconds cpu time 0.31 seconds 137 138 data idnew_tr; 139 set idnew1; 140 141 array flag(&count_idchem) $ _temporary_; 142 by id_job; 143 retain flag; 144 145 if first.id_job then do; 146 count=0; 147 call missing(of flag(*)); 148 end; 149 150 count+1; 151 152 do i=1 to dim(flag); 153 /*flag(count)=idchem_char;*/ 154 end; 155 156 idchem_list = catx(" ", of flag(*)); 157 if last.id_job then output; 158 159 /*drop count i idchem idchem_char id job;*/ 160 drop idchem_list list1-list&count_idchem; 161 run; WARNING: Not all variables in the list list1-list18 were found. NOTE: There were 124695 observations read from the data set WORK.IDNEW1. NOTE: The data set WORK.IDNEW_TR has 11058 observations and 7 variables. NOTE: DATA statement used (Total process time): real time 0.28 seconds cpu time 0.28 seconds 162 163 OPTIONS NONOTES NOSTIMER NOSOURCE NOSYNTAXCHECK; 175

ak2011 · ‎11-25-2019

I would appreciate if someone could explain this to me and provide me the the right code to resolve this problem: I have a smaller dataset with 17 obs. I transposed and found exposed(1) and unexposed(0) variables and found an association between them. The resulting data was 8 obs but with dots(.) ie. missing values but proc freq did not display or used the missing values in the computations even if I don't use the /missing or /missprint options.(Results attached,please). However, when I apply the same code for the larger dataset(over 100,000 obs), the dots(.) were displayed and missing values in thousands were indicated in the proc freq results(not shown). II want to understand why no missing data were indicated in the proc freq for the smaller dataset (even though it had dots(.) like the larger dataset. May I know the code to remove the dots(.) to blanks (ie. nothing) so that SAS will not show any missing value like in the case of the smaller dataset. Thanks. data idnew1; input id$ job idchem; datalines; os1 1 990005 os1 1 990021 os1 1 211700 os1 2 211700 os1 2 990021 os1 2 210701 os1 2 990005 os2 1 210701 os2 1 990005 os2 2 990021 os2 3 210701 os2 3 990005 os3 3 210701 os3 1 211700 os4 1 210701 os4 1 990005 os4 1 211700 ; run; /*TRANSPOSING VARIABLES*/ proc sort data=idnew1; by id job; proc transpose data=idnew1 out=idnew1b prefix=idchem; by id job; /*id job;*/ var idchem; run; /*Cla exposure*/ data clat; set idnew1b; if idchem1='990005'or idchem2='990005' or idchem3='990005' or idchem4='990005' then cla_exp=1; else cla_exp=0; id_job=catx('_', id, job); put _all_; drop _name_; run; proc print data=clat; Title "Cla exposure"; run; /*Bio exposure*/ data biot; set idnew1b; if idchem1='990021' or idchem2='990021' or idchem3='990021' or idchem4='990021' then bio_exp=1; else bio_exp=0; id_job=catx('_', id, job); put _all_; drop _name_; run; Title "Bio exposure"; proc print data=biot; run; /*Amo exposure*/ data amot; set idnew1mb; if idchem1='210701' or idchem2='210701' or idchem3='210701' or idchem4='210701' then amo_exp=1; else amo_exp=0; id_job=catx('_', id, job); put _all_; drop _name_; run; proc print data=amot; Title "Amo exposure"; run; /*Chl exposure*/ data chlt; set idnew1b; if idchem1='211700' or idchem2='211700' or idchem3='211700'or idchem4='211700' then chl_exp=1; else chl_exp=0; id_job=catx('_', id, job); put _all_; drop _name_; run; proc print data=chlt; Title "chl exposure"; run; /* Merging clat,biot and amot files*/ data mlt; merge clat biot amot chlt; run; proc print data=mlt; Title "Merged exposure files for cla ,bio, amo and chl pollutants"; run; /*CROSS ASSOCIATIONS:clat,biot,amot,chlt*/ proc freq data=mlt; tables cla_exp*bio_exp; tables cla_exp*amo_exp; tables cla_exp*chl_exp; tables bio_exp*cla_exp; tables bio_exp*amo_exp; tables bio_exp*chl_exp; run;

ak2011 · ‎11-25-2019

Hi, Your code is right since it is working well with the smaller dataset but when I apply it to the larger one is when the error generates. I think it has to do with flag(count). Please recheck this code: Thanks.: OPTIONS NONOTES NOSTIMER NOSOURCE NOSYNTAXCHECK; 72 73 /* 2. Transpose data and concatenate idchem */ 74 75 proc sort data=idnew1; 76 by id_job; 77 run; NOTE: PROCEDURE SORT used (Total process time): real time 0.36 seconds cpu time 0.37 seconds NOTE: There were 124695 observations read from the data set WORK.IDNEW1. NOTE: The data set WORK.IDNEW1 has 124695 observations and 5 variables. 78 79 data idnew_tr; 80 set idnew1; 81 82 array flag(4) $ _temporary_; 83 by id_job; 84 retain flag; 85 86 if first.id_job then do; 87 count=0; 88 call missing(of flag(*)); 89 end; 90 91 count+1; 92 93 do i=1 to dim(flag); 94 flag(count)=idchem_char; 95 end; 96 97 idchem_list = catx(" ", of flag(*)); 98 if last.id_job then output; 99 100 drop count i idchem idchem_char id job; 101 run; ERROR: Array subscript out of range at line 94 column 3. id=OSaa01 job=2 idchem=530196 idchem_char= id_job=OSaa01_2 FIRST.id_job=0 LAST.id_job=1 count=5 i=1 idchem_list= _ERROR_=1 _N_=8 NOTE: The SAS System stopped processing this step because of errors. NOTE: There were 9 observations read from the data set WORK.IDNEW1. WARNING: The data set WORK.IDNEW_TR may be incomplete. When this step was stopped there were 1 observations and 2 variables. WARNING: Data set WORK.IDNEW_TR was not replaced because this step was stopped. NOTE: DATA statement used (Total process time): real time 0.02 seconds cpu time 0.02 seconds 102 103 OPTIONS NONOTES NOSTIMER NOSOURCE NOSYNTAXCHECK; 115 Thanks. ak.

ak2011 · ‎11-25-2019

Sorry for back and forth communication: the flag(count) =... did not work. I expect the "count" to be in "blue" like what you sent me but it wasn't like that: Please recheck the code below: OPTIONS NONOTES NOSTIMER NOSOURCE NOSYNTAXCHECK; 72 73 /* 2. Transpose data and concatenate idchem */ 74 75 proc sort data=idnew1; 76 by id_job; 77 run; NOTE: Input data set is already sorted, no sorting done. NOTE: PROCEDURE SORT used (Total process time): real time 0.00 seconds cpu time 0.01 seconds 78 79 data idnew_tr; 80 set idnew1; 81 82 array flag(4) $ _temporary_; 83 by id_job; 84 retain flag; 85 86 if first.id_job then do; 87 count=0; 88 call missing(of flag(*)); 89 end; 90 91 count+1; 92 flag(count)=idchem_char; 93 94 idchem_list = catx(" ", of flag(*)); 95 if last.id_job then output; 96 97 drop count i idchem idchem_char id job; 98 run; WARNING: The variable i in the DROP, KEEP, or RENAME list has never been referenced. ERROR: Array subscript out of range at line 92 column 2. id=OSaa01 job=2 idchem=530196 idchem_char= id_job=OSaa01_2 FIRST.id_job=0 LAST.id_job=1 count=5 idchem_list= _ERROR_=1 _N_=8 NOTE: The SAS System stopped processing this step because of errors. NOTE: There were 9 observations read from the data set WORK.IDNEW1. WARNING: The data set WORK.IDNEW_TR may be incomplete. When this step was stopped there were 1 observations and 2 variables. WARNING: Data set WORK.IDNEW_TR was not replaced because this step was stopped. NOTE: DATA statement used (Total process time): real time 0.01 seconds cpu time 0.02 seconds 99 100 101 OPTIONS NONOTES NOSTIMER NOSOURCE NOSYNTAXCHECK; 113 Thanks. ak.

ak2011 · ‎11-25-2019

Thanks. A little problem again on flag(count) line 88: Can you please check for me? 1 OPTIONS NONOTES NOSTIMER NOSOURCE NOSYNTAXCHECK; 72 73 data idnew_tr; 74 set idnew1; 75 76 array flag(4) $ _temporary_; 77 by id_job; 78 retain flag; 79 80 if first.id_job then do; 81 count=0; 82 call missing(of flag(*)); 83 end; 84 85 count+1; 86 87 do i=1 to dim(flag); 88 flag(count)=idchem_char; 89 end; 90 91 idchem_list = catx(" ", of flag(*)); 92 if last.id_job then output; 93 94 drop count i idchem idchem_char id job; 95 run; ERROR: Array subscript out of range at line 88 column 3. id=OSaa01 job=2 idchem=530196 idchem_char= id_job=OSaa01_2 FIRST.id_job=0 LAST.id_job=1 count=5 i=1 idchem_list= _ERROR_=1 _N_=8 NOTE: The SAS System stopped processing this step because of errors. NOTE: There were 9 observations read from the data set WORK.IDNEW1. WARNING: The data set WORK.IDNEW_TR may be incomplete. When this step was stopped there were 1 observations and 2 variables. WARNING: Data set WORK.IDNEW_TR was not replaced because this step was stopped. NOTE: DATA statement used (Total process time): real time 0.01 seconds cpu time 0.01 seconds Thanks. ak.

ak2011 · ‎11-25-2019

Thanks. Maybe I did not clarify things well. The dummies have been created alright but now I need to find id_job variables and find the associations between say cla_exp * bio_exp, etc using the proc frequency. Now the exposed(1) and unexposed(0) variables have been created but I need to find the associations between them. Thanks. ak.

ak2011 · ‎11-25-2019

Thanks very much! It works for the smaller dataset. I am trying it on the larger dataset but the only trouble is the idchem_char. Sas generated an error message. Actually it is not your fault, for the smaller dataset I am used datalines but in the larger one, I am reading directly from a file(not datalines). Can you please help me to resolve the idchem_char problem? The code is founld below: 1 OPTIONS NONOTES NOSTIMER NOSOURCE NOSYNTAXCHECK; 72 73 /* MACRO APPROACH*/ 74 75 data chem1(keep=id job idchem); 76 length idchem_char $7; 77 set multi.multiworkchempostauto; NOTE: Data file MULTI.MULTIWORKCHEMPOSTAUTO.DATA is in a format that is native to another host, or the file encoding does not match the session encoding. Cross Environment Data Access will be used, which might require additional CPU resources and might reduce performance. 78 /*input id$ job idchem;*/ 79 /*id_job=catx('_', id, job);*/ 80 length idchem_char $7; 81 if idchem = 990005 then idchem_char = 'cla_exp'; 82 else if idchem = 990021 then idchem_char = 'bio_exp'; 83 else if idchem = 520299 then idchem_char = 'ali_exp'; 84 else if idchem = 420204 then idchem_char = 'iso_exp'; /* to adapt */ 85 86 else if idchem = 430101 then idchem_char = 'ben_exp'; 87 else if idchem = 430103 then idchem_char = 'xyl_exp'; 88 else if idchem = 430102 then idchem_char = 'tol_exp'; 89 else if idchem = 430104 then idchem_char = 'sty_exp'; /* to adapt */ 90 91 else if idchem = 460003 then idchem_char = 'sol_exp'; 92 else if idchem = 220501 then idchem_char = 'for_exp'; 93 else if idchem = 510004 then idchem_char = 'hyp_exp'; 94 else if idchem = 210701 then idchem_char = 'amo_exp'; /* to adapt */ 95 96 97 else if idchem = 211700 then idchem_char = 'chl_exp'; 98 else if idchem = 410002 then idchem_char = 'cau_exp'; 99 else if idchem = 411501 then idchem_char = 'pho_exp'; 100 else if idchem = 420401 then idchem_char = 'ace_exp'; /* to adapt */ 101 102 else if idchem = 211701 then idchem_char = 'hcl_exp'; 103 else if idchem = 460004 then idchem_char = 'wpo_exp'; /* to adapt */ 104 id_job=catx('_', id, job); 105 run; NOTE: There were 124695 observations read from the data set MULTI.MULTIWORKCHEMPOSTAUTO. NOTE: The data set WORK.CHEM1 has 124695 observations and 3 variables. NOTE: DATA statement used (Total process time): real time 1.89 seconds cpu time 1.11 seconds 106 107 /* 1. Generate macrovariables */ 108 109 109 ! proc sql noprint; 110 /* Retrieve the list of distinct idchems (num) in a macrovariable : &list_idchem */ 111 select distinct idchem into:list_idchem separated by " " from chem1; 112 /* Retrieve the list of distinct idchems (format) in a macrovariable : &list_idchem_char */ 113 select distinct idchem_char into:list_idchem_char separated by " " from chem1; ERROR: The following columns were not found in the contributing tables: idchem_char. NOTE: PROC SQL set option NOEXEC and will continue to check the syntax of statements. 114 /* Retrieve the number of distinct idchems in a macrovariable : &count_idchem */ 115 select count(distinct idchem_char) into:count_idchem trimmed from chem1; ERROR: The following columns were not found in the contributing tables: idchem_char. 116 quit; NOTE: The SAS System stopped processing this step because of errors. NOTE: PROCEDURE SQL used (Total process time): real time 0.17 seconds cpu time 0.23 seconds 117 118 119 OPTIONS NONOTES NOSTIMER NOSOURCE NOSYNTAXCHECK; 131 Thanks. ak.

ak2011 · ‎11-25-2019

Hi, Your proc sql approach is very helpful but is there a way to use the same proc sql for cross tabulations for a larger dataset with 30 idchems(not 4 like the smaller dataset). eg. cla_exp * bio_exp; cla_exp* amo_exp etc. I would really appreciate your help. Thanks in advance. ak.

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