Your logic should at least delete some rows from the sample data you've provided.  If it's just about change then I'd be using the abs() function. To not mask cases with missings I wouldn't use the sum() function. data weight_data; input ID Gender $ Starting_Weight End_Weight; del_flg= 0<=abs(Starting_Weight-End_Weight)<10; /* if 0<=abs(Starting_Weight-End_Weight)<10 then delete;*/ datalines; 1 M 170 180 2 M 182 175 3 M 155 162 4 M 203 196 5 F 124 135 6 F 152 155 7 F 118 133 8 F 160 152 9 F . 152 ; run; proc print data=weight_data; run; ... View more

Did you map (bind) the directory from your host machine to a directory within the Docker container?      ... View more

If you've got known strings like n/a that you want to convert to missings but also want to stay on the safe side and not just suppress any errors or warnings with the ?? modifier then you could also create your own informat using code similar to below. proc format; invalue char2num 'n/a' = . other = [best32.] ; run; data demo_1; infile datalines truncover; input charvar $; numvar_1=input(charvar,char2num32.); datalines; 11 2 n/a 4 ; data demo_2; infile datalines truncover; input charvar $; numvar_1=input(charvar,char2num32.); datalines; 11 2 n/a 4 xxx ; ... View more

If you can't find ready-made SAS data step code as suggested by @ballardw then you need to create this code by yourself based on the record description in the pdf.   Below some input which is hopefully helpful to you.   1. Using WSL (a Linux prompt for Windows) I've run below command to create the attached txt file which contains the first 2000 lines of your big file. This should allow you to inspect the source data in an editor. head -n 2000 ./Nat2023PublicUS.c20240509.r20240724.txt > ./Nat2023PublicUS.c20240509.r20240724_part01.txt I also created a part of the data step input statement with AI assistance (using the pdf record description as input). That's likely not fully correct but it should give you a start in case you can't find any ready made code. /* Define the file path */ %let filepath = 'C:\temp\Nat2023us\Nat2023PublicUS.c20240509.r20240724_part01.txt'; /* Read the data */ data natality2023; infile "&filepath" truncover; input FILLER1 $ 1-8 DOB_YY $ 9-12 DOB_MM $ 13-14 FILLER2 $ 15-18 DOB_TT $ 19-22 DOB_WK $ 23 FILLER3 $ 24-31 BFACIL $ 32 F_BFACIL $ 33 FILLER4 $ 34-49 BFACIL3 $ 50 FILLER5 $ 51-72 MAGE_IMPFLG $ 73 MAGE_REPFLG $ 74 MAGER 75-76 MAGER14 $ 77-78 MAGER9 $ 79 FILLER6 $ 80-83 MBSTATE_REC $ 84 FILLER7 $ 85-103 RESTATUS $ 104 MRACE31 $ 105-106 MRACE6 $ 107 MRACE15 $ 108-109 FILLER8 $ 110 MRACEIMP $ 111 MHISPX $ 112 FILLER9 $ 113-114 MHISP_R $ 115 F_MHISP $ 116 MRACEHISP $ 117 FILLER10 $ 118 MAR_P $ 119 DMAR $ 120 MAR_IMP $ 121 FILLER11 $ 122 F_MAR_P $ 123 MEDUC $ 124 FILLER12 $ 125 F_MEDUC $ 126 FILLER13 $ 127-141 **bleep**ERPT_FLG $ 142 FILLER14 $ 143-146 **bleep**ECOMB $ 147-148 **bleep**EREC11 $ 149-150 FRACE31 $ 151-152 FRACE6 $ 153 FRACE15 $ 154-155 FILLER15 $ 156-158 FHISPX $ 159 FHISP_R $ 160 F_FHISP $ 161 FRACEHISP $ 162 FEDUC $ 163 FILLER16 $ 164 f_FEDUC $ 165 FILLER17 $ 166-170 PRIORLIVE $ 171-172 PRIORDEAD $ 173-174 PRIORTERM $ 175-176 FILLER18 $ 177-178 LBO_REC $ 179 FILLER19 $ 180-181 TBO_REC $ 182 FILLER20 $ 183-197 ILLB_R $ 198-200 ILLB_R11 $ 201-202 FILLER21 $ 203-205 ILOP_R $ 206-208 ILOP_R11 $ 209-210 FILLER22 $ 211-213 ILP_R $ 214-216 ILP_R11 $ 217-218 FILLER23 $ 219-223 PRECARE $ 224-225 F_MPCB $ 226 PRECARE5 $ 227 FILLER24 $ 228-237 PREVIS $ 238-239 FILLER25 $ 240-241 PREVIS_REC $ 242-243 F_TPCV $ 244 FILLER26 $ 245-250 WIC $ 251 F_WIC $ 252 CIG_0 $ 253-254 CIG_1 $ 255-256 CIG_2 $ 257-258 CIG_3 $ 259-260 CIG0_R $ 261 CIG1_R $ 262 CIG2_R $ 263 CIG3_R $ 264 F_CIGS_0 $ 265 F_CIGS_1 $ 266 F_CIGS_2 $ 267 F_CIGS_3 $ 268 CIG_REC $ 269 F_TOBACO $ 270 FILLER27 $ 271-279 M_Ht_In $ 280-281 F_M_HT $ 282 BMI $ 283-286 BMI_R $ 287 FILLER28 $ 288-291 PWgt_R $ 292-294 F_PWGT $ 295 FILLER29 $ 296-298 DWgt_R $ 299-301 FILLER30 $ 302 F_DWGT $ 303 WTGAIN $ 304-305 WTGAIN_REC $ 306 F_WTGAIN $ 307 FILLER31 $ 308-312 RF_PDIAB $ 313 RF_GDIAB $ 314 RF_PHYPE $ 315 RF_GHYPE $ 316 RF_EHYPE $ 317 RF_PPTERM $ 318 F_RF_PDIAB $ 319 F_RF_GDIAB $ 320 F_RF_PHYPER $ 321 F_RF_GHYPER $ 322 F_RF_ECLAMP $ 323 F_RF_PPB $ 324 RF_INFTR $ 325 RF_FEDRG $ 326 RF_ARTEC $ 327 f_RF_INFT $ 328 F_RF_INF_DRG $ 329 F_RF_INF_ART $ 330 RF_CESAR $ 331 RF_CESARN $ 332-333 FILLER32 $ 334 F_RF_CESAR $ 335 F_RF_NCESAR $ 336 NO_RISKS $ 337 FILLER33 $ 338-342 IP_GON $ 343 IP_SYPH $ 344 IP_CHLAM $ 345 IP_HEPB $ 346 IP_HEPC $ 347 F_IP_GONOR $ 348 F_IP_SYPH $ 349 F_IP_CHLAM $ 350 F_IP_HEPATB $ 351 F_IP_HEPATC $ 352 NO_INFEC $ 353 FILLER34 $ 354-358 FILLER35 $ 359 OB_ECVS $ 360 OB_ECVF $ 361 FILLER36 $ 362 F_OB_SUCC $ 363 F_OB_FAIL $ 364 FILLER37 $ 365-382 LD_INDL $ 383 LD_AUGM $ 384 LD_STER $ 385 LD_ANTB $ 386 LD_CHOR $ 387 LD_ANES $ 388 F_LD_INDL $ 389 F_LD_AUGM $ 390 F_LD_STER $ 391 F_LD_ANTB $ 392 F_LD_CHOR $ 393 F_LD_ANES $ 394 NO_LBRDLV $ 395 FILLER38 $ 396-400 ME_PRES $ 401 ME_ROUT $ 402 ME_TRIAL $ 403 F_ME_PRES $ 404 F_ME_ROUT $ 405 F_ME_TRIAL $ 406 RDMETH_REC $ 407 DMETH_REC $ 408 F_DMETH_REC $ 409 FILLER39 $ 410-414 MM_MTR $ 415 MM_PLAC $ 416 MM_RUPT $ 417 MM_UHYST $ 418 MM_AICU $ 419 FILLER40 $ 420 F_MM_MTR $ 421 F_MM_PLAC $ 422 F_MM_RUPT $ 423 F_MM_UHYST $ 424 F_MM_AICU $ 425 FILLER41 $ 426 NO_MMORB $ 427 FILLER42 $ 428-432 ATTEND $ 433 MTRAN $ 434 PAY $ 435 PAY_REC $ 436 F_PAY $ 437 F_PAY_REC $ 438 FILLER43 $ 439-443 APGAR5 $ 444-445 APGAR5R $ 446 F_APGAR5 $ 447 APGAR10 $ 448-449 ; run; And of course because the source data is positional it's easy to only read the columns you actually need into SAS which hopefully will significantly reduce the effort. ... View more

@PaigeMiller wrote: Several of you have asked what type of field this is using native data base tools.   It is type DATE, with precision 10.   So does that help at all? How can a different user access this same table and see the field as character and length 20? It helps because now we know that as per SAS documentation this should map to a SAS numeric column with a Date9. format.  What engine are you using (ODBC, SQLSRV, ....)? If your code is identical and you're really connecting to the same table on the same database then the only thing I can think of that could cause this is some issue with a driver.   You could on both machine execute code as below and then compare the SAS logs. libname yourdb ....; /* run 1 */ options sastrace='d,' sastraceloc=saslog nostsuffix; proc sql inobs=1; select <problem col> from yourdb.<table>; quit; /* run 2 */ options sastrace=',,d,' sastraceloc=saslog nostsuffix; proc sql inobs=1; select <problem col> from yourdb.<table>; quit; Such log is likely also what SAS Tech Support will request from you. SASTRACE= SAS System Option     ... View more

If you are at a University then look into  https://www.sas.com/en_us/learn/academic-programs/software.html  https://www.sas.com/en_us/software/viya-for-learners.html  There are also many public training videos available. Just do a search. ... View more

I assume "latest" means the file with the highest number.  You will need to first create a directory listing and then use some logic to find the the file with the highest number (and it's not how they sort alphabetically because a2.csv will sort after a10.csv).   Can you execute OS commands out of SAS? Run below syntax and let us know if you see in the log XCMD or NOXCMD. proc options option=xcmd; run; ... View more

I assume the root cause of the missing values is that your conditions are never true.   if update_field in (&sdis6_decimal_0) then    You could easily test this by adding another else condition like: else to_numeric_value_c ='9999';   Given the info you've shared you want your character variables populated wth full precision but without trailing zeros. Format BESTn. does this for you. I assume you've used ifc() for missings to become blanks. You could create a custom format instead. See below code for further explanation. proc format; value myBest(default=16) . = ' ' other=[best16.] ; run; data test; input from_numeric_value; /* your syntax with format best32. */ to_numeric_value_c = strip(ifc(missing(from_numeric_value),"",put(from_numeric_value,best16.))); /* alternative syntax returning the same result */ to_numeric_value_c2=put(from_numeric_value,myBest.); datalines; 0.25 0 . 0.0025 ; run; proc print data=test; run; proc contents data=test; run;   Also note that if using ifc() you should use a length statement to avoid a wasteful length of the created character variable.   ....and just reading what @Kurt_Bremser wrote: Yes, of course, as this is likely for reporting just use the BESTn. or the custom format directly on the numerical variable. And there is also the missing option where you can change the default behaviour of printing missings as a dot. options missing=' ';   ... View more

Here some sample code to build upon for what @Kurt_Bremser suggested. libname src xlsx "c:\temp\Example.xlsx"; proc datasets lib=src nolist; copy in=src out=work; run; quit; libname src clear; ... View more

@JacquesR wrote: Thanks @Patrick and @Ksharp  That works. Annoying that the documentation page I linked to does not mention DBSASTYPE. I've used already multiple times the docu feedback button when I felt something is missing and several times my proposed changes actually made it into the docu. I also started to use AI assistance (mostly Copilot) when looking for solutions. Not that the answers are always correct but it's often giving me new ideas. If you want to test it with Copilot use below prompts and see what you get: proc import ms access short text to SAS character variable length 255 ...or even more fun: Just copy/paste your initial question into Copilot or similar. ... View more

Using Proc Import have you tried DBSASTYPE? I believe syntax similar to below could work. PROC IMPORT DATAFILE="C:\path\to\your\database.accdb" OUT=work.mydata DBMS=ACCESS REPLACE; TABLE="YourTableName"; DBSASTYPE=('ShortTextColumn'='CHAR(255)'); RUN; ... View more

The Viya 4 SAS Studio git integration is imho much more streamlined. With the future in mind (it's actually already present) I'd be looking into the migration path of SAS EG to SAS Studio and the git integration capabilities of SAS Studio.  The latest EG versions are now also compatible with SAS Viya but they don't offer the same richness in functionality. I'm especially fond of SAS Studio Flow and the growing number of SAS Studio Custom Steps available in public git repositories that one can use to build such flows.   ... View more

@cashaowan wrote: I run the codes you provided. SAS/Access Interface to PC Files is installed. The dataset I created has less than 5000 observations. Would appreciate if you can suggest the next SAS procedure.  Below one option: proc export data=sashelp.class outfile='c:\temp\myExcel.xlsx' dbms=xlsx replace ; sheet='Class'; run; And here some more options: https://blogs.sas.com/content/sasdummy/2012/01/25/export-to-excel-got-easier/ https://blogs.sas.com/content/sasdummy/2012/02/11/export-excel-methods/   Note: The path to the Excel file must be accessible from the location where the SAS process executes. If this is a SAS Server under Linux then it would be some Linux path.   ... View more

sas_execfilepath is an environment variable set and updated when you're using "PC SAS". If you're running in batch mode then SAS can't know in advance what program you want to run and though won't create this environment variable.  The -set option in the batch command @Ksharp shared lets you define and populate an environment variable that you then can query within your program. This then allows you to execute the exactly same code in batch.  Alternatively you can also query the value of SYSIN as it will also contain the path to the .sas file you're executing in batch. ... View more