Macrovariable values have a maximum length of 65,534 characters, your 1500 accounts are using up all that space and there is no option to increase that size. Since you define the macro variables within the macro then they disappear when that macro is finished and you can't call them outside of the macro. Use the %global statement to define the macro. The ERROR message is an indicator, you have shown how you're calling the macro variables so we can't tell you if you have another error or not. Here some info on macro variable scope: http://support.sas.com/documentation/cdl/en/mcrolref/61885/HTML/default/viewer.htm#a001072111.htm#a001072130 Check the scope of your variables by using some %put statements inside your macro and outside. HTH %MACRO FORMAT_DATASET(LIB=,TABLE=); PROC DATASETS LIBRARY=&LIB; DELETE &TABLE; RUN; DATA &LIB..LISTFILE(DROP=ACCT_NBR); SET &LIB..&TABLE(KEEP=ACCT_NBR); FORMAT ACCT_NBR_MQ $QUOTE20. ACCT_NBR_DQ $QUOTE24.; ACCT_NBR_MQ=PUT(INPUT(ACCT_NBR,22.),Z18.); ACCT_NBR_DQ=PUT(INPUT(ACCT_NBR,22.),Z22.); RUN; PROC SQL; SELECT ACCT_NBR_DQ INTO :ACCT_NBR_DQ SEPARATED BY "," FROM &LIB..LISTFILE; SELECT ACCT_NBR_MQ INTO :ACCT_NBR_MQ SEPARATED BY "," FROM &LIB..LISTFILE; QUIT; %LET ACCT_NBR_D=%SYSFUNC(TRANWRD(%BQUOTE(&ACCT_NBR_DQ),%BQUOTE("),%BQUOTE('))); %LET ACCT_NBR_M=%SYSFUNC(TRANWRD(%BQUOTE(&ACCT_NBR_MQ),%BQUOTE("),%BQUOTE('))); %put &ACCT_NBR_D.; %put &ACCT_NBR_M.; %MEND FORMAT_DATASET; %put &ACCT_NBR_D.; %put &ACCT_NBR_M.; ... View more

Or just do it in a datastep, since you need to pre-process it there. data x;     input id dol @@; datalines; 0 9 1 5 1 8 1 10 1 3 2 10 3 4 ; data x_with_indicator ;    set x ;    by id ;      if not first.id;    run ; ... View more

That is what the documentation says, but it does that ONLY if there are missing values. If you have a format that assumes this, but have no actual missing values then the results end up in your table, not in the missing which isn't what I'd expect according to the documentation. ... View more

That's fine, there's ways around it, just not the behaviour I would have expected by default.  I do understand that SAS uses the underlying value rather than the actual formatted value. If it was a space in a character value then it would be considered a missing observation. If it is a space in the format of a numeric variable it IS considered a missing observation if there is other missing numeric observations, but if there are no missing observations it doesn't work. I'd expect it to be treated the same whether or not there were other missing values. So in LinLin's example the table should have 1 missing and 1 blank not 2 missing. ... View more

If you change the length on the table the information in the fields won't change, you should be able to drop the old column and add a new one with the correct defn and update that.  Not sure about the efficiencies of that but someone else may know. ... View more

You can with PROC SQL. I think it just recreates the dataset though or at least read that somewhere. data class;     set sashelp.class; run; proc sql; alter table work.class     modify sex char(5); quit; proc contents data=class; run; ... View more

Here's a simple example to get what the OP has. It doesn't remove the missing either...not sure why. On a Windows XP, SAS 9.2.3 Regardless of where the format is applied the results are the same. data class;     set sashelp.class; run; proc format;     value age     11='Pre Teen'     12='Pre Teen'     13='Teen'     14='Teen'     15='Teen'     16=" "; run; proc freq data=class;     table age;     format age age.; run;                                                                 Cumulative    Cumulative                                 Age    Frequency     Percent     Frequency      Percent                            ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ                            Pre Teen           7       36.84             7        36.84                            Teen              11       57.89            18        94.74                                               1        5.26            19       100.00 ... View more

Yes, I think you're correct. It doesn't appear possible to change the length of a variable without recreating the table. Changing the table structure could change the data if you reduced the length so this makes some sense. PROC SQL or PROC DATASETS can be used to change the format but not the length. I thought the modify statement within a datastep might work, but I couldn't get it to work either (though that doesn't mean it can't be). You can use a data step and specify the length before you the SET statement as in QLi's code to change the length. EDIT: NOTE in SAS DOCs that say it is a fixed attribute and cannot be changed via proc datasets: http://support.sas.com/documentation/cdl/en/basess/58133/HTML/default/viewer.htm#a001397456.htm *Via PROC SQL; data class;     set sashelp.class; run; proc sql; alter table work.class     modify sex format=$5.; quit; proc contents data=class; run; *Via a datastep; data class;     length sex $5.;     set class; run; proc contents data=class; run; ... View more

Try Tools>Options>Preferences>Advanced Tab - this is assuming you're on SAS 9.2 on Windows, may differ in other versions. EDIT: This appears to control output and log, not sure about editor windows. ... View more

You can use proc transpose and the functions that KSharp has suggested, or use some transformations with proc means. I prefer the transformations as its easier for me to understand. For geometric mean take the log of your variable and then exponentiate the resulting mean of the logged variable. For harmonic mean take the inverse of your variable and then n/sum(inverse) is the number you're looking for. data class;     set sashelp.class;     harm=1/height;     geom=log(height); run; ods table summary=step1; proc means data=class n mean sum; class sex; var height harm geom; run; data step2;     set step1;     geometric_mean=exp(geom_mean);     harmonic_mean=harm_n/harm_sum;     keep sex height_mean geometric_mean harmonic_mean; run; You can verify it using KSharps formulas: proc sort data=class; by sex; run; proc transpose data=class out=class2; by sex; var height; run; data class3;     set class2;     mean=mean(of col:);     harmean=harmean(of col:);     geomean=geomean(of col:); run; ... View more