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david27
Quartz | Level 8

Team,

 

I have this:

 

%let total_period=20;

%let period1=201303;
%let period2=201306;
%let period3=201309;
%let period4=201312;
%let period5=201403;
%let period6=201406;
%let period7=201409;
%let period8=201412;
%let period9=201503;
%let period10=201506;
%let period11=201509;
%let period12=201512;
%let period13=201603;
%let period14=201606;
%let period15=201609;
%let period16=201612;
%let period17=201703;
%let period18=201706;
%let period19=201709;
%let period20=201712;





data have;
input field :$8. _201303 _201306 _201309 _201312 _201403 _201406 _201409 _201412 _201503 _201506 _201509 _201512 _201603 _201606 _201609 _201612 _201703 _201706 _201709 _201712
;
datalines;
a 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
b 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
c 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
d 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
e 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
f 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
;
run;

 

 

I want to calculate mean as:

 

 

/*Excluding the period 201303 here*/
mean_ex_201303 = mean(_201306, _201309, _201312, _201403, _201406, _201409, _201412, _201503, _201506, _201509, _201512, _201603, _201606, _201609, _201612, _201703, _201706, _201709, _201712, );

/*Excluding the period 201306 here*/
mean_ex_201306 = mean(_201303, _201309, _201312, _201403, _201406, _201409, _201412, _201503, _201506, _201509, _201512, _201603, _201606, _201609, _201612, _201703, _201706, _201709, _201712, );

 

And this has to be done for all the periods i.e.201303 to 201712(all 20 months).

 

Please advise.

 

Thanks

 

1 ACCEPTED SOLUTION

Accepted Solutions
mkeintz
PROC Star

The "trick" here is to use two arrays constructed from variable name lists, where the lists are macrovars.  You don't need all those let statements:

 

data have;
  input field :$8. _201303 _201306 _201309 _201312 
                   _201403 _201406 _201409 _201412 
                   _201503 _201506 _201509 _201512 
                   _201603 _201606 _201609 _201612 
                   _201703 _201706 _201709 _201712;
datalines;
a 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
b 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
c 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
d 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
e 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
f 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
run;

/* Make a dummy data set with just the vars of interest*/
data dummy;  
  set have;
  keep _: ;
  stop;
run;
/* Use the dictionary metadata to build 2 variables lists */
proc sql noprint;
  select name, cats('mean_ex',name) into 
     :var_list separated by ' ',
     :mean_list separated by ' '
    from dictionary.columns where memname='DUMMY' and libname='WORK'
    order by name;
quit;
%let divisor=%eval(&sqlobs-1);
%put &=mean_list;
%put &=var_list;
%put &=divisor;

/* Now make an array of values and a corresponding array for means */
data want ;
  set have;
  array values {*} &var_list;
  array means  {*} &mean_list;
  sumvalues = sum(of values{*});
  do i=1 to dim(values);
    means{i} = (sumvalues - values{i}) / &divisor; 
  end;
  drop sumvalues;
run;

 

This program assumes you never have missing values, so the divisor is a constant (19 in your example).  If you do encounter missing vars then don't bother generating the divisor macrovar, and modify the data want step to:

 

/* Now make an array of values and a corresponding array for means */
data want ;
  set have;
  array values {*} &var_list;
  array means  {*} &mean_list;
  sumvalues=sum(of values{*});
  nvalues=n(of values{*});
  do i=1 to dim(values);
    means{i} = (sumvalues - values{i}) / (nvalues - n(values{i}));
  end;
  drop sumvalues nvalues;
run;
--------------------------
The hash OUTPUT method will overwrite a SAS data set, but not append. That can be costly. Consider voting for Add a HASH object method which would append a hash object to an existing SAS data set

Would enabling PROC SORT to simultaneously output multiple datasets be useful? Then vote for
Allow PROC SORT to output multiple datasets

--------------------------

View solution in original post

2 REPLIES 2
mkeintz
PROC Star

The "trick" here is to use two arrays constructed from variable name lists, where the lists are macrovars.  You don't need all those let statements:

 

data have;
  input field :$8. _201303 _201306 _201309 _201312 
                   _201403 _201406 _201409 _201412 
                   _201503 _201506 _201509 _201512 
                   _201603 _201606 _201609 _201612 
                   _201703 _201706 _201709 _201712;
datalines;
a 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
b 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
c 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
d 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
e 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
f 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
run;

/* Make a dummy data set with just the vars of interest*/
data dummy;  
  set have;
  keep _: ;
  stop;
run;
/* Use the dictionary metadata to build 2 variables lists */
proc sql noprint;
  select name, cats('mean_ex',name) into 
     :var_list separated by ' ',
     :mean_list separated by ' '
    from dictionary.columns where memname='DUMMY' and libname='WORK'
    order by name;
quit;
%let divisor=%eval(&sqlobs-1);
%put &=mean_list;
%put &=var_list;
%put &=divisor;

/* Now make an array of values and a corresponding array for means */
data want ;
  set have;
  array values {*} &var_list;
  array means  {*} &mean_list;
  sumvalues = sum(of values{*});
  do i=1 to dim(values);
    means{i} = (sumvalues - values{i}) / &divisor; 
  end;
  drop sumvalues;
run;

 

This program assumes you never have missing values, so the divisor is a constant (19 in your example).  If you do encounter missing vars then don't bother generating the divisor macrovar, and modify the data want step to:

 

/* Now make an array of values and a corresponding array for means */
data want ;
  set have;
  array values {*} &var_list;
  array means  {*} &mean_list;
  sumvalues=sum(of values{*});
  nvalues=n(of values{*});
  do i=1 to dim(values);
    means{i} = (sumvalues - values{i}) / (nvalues - n(values{i}));
  end;
  drop sumvalues nvalues;
run;
--------------------------
The hash OUTPUT method will overwrite a SAS data set, but not append. That can be costly. Consider voting for Add a HASH object method which would append a hash object to an existing SAS data set

Would enabling PROC SORT to simultaneously output multiple datasets be useful? Then vote for
Allow PROC SORT to output multiple datasets

--------------------------
Amir
PROC Star

Hi,

 

As @mkeintz has indicated, using dictionary tables is more dynamic than hard coding %let statements. Nonetheless, the following macro should generate the statements required with the setup you've shown, for use in a data step:

 

%macro mean_period;
   %do i = 1 %to &total_period;
      %let p_list =;

      /* start assignment of mean value */
      mean_ex_&&period&i = mean(

      %do j = 1 %to &total_period;
         %if &j ne &i %then
            %let p_list = &p_list _&&period&j;
      %end;

      /* add commas to the list */
      %let p_list = %sysfunc(tranwrd(&p_list,%str( ),%str(, )));

      /* finish mean value assignment */
      &p_list
      );
   %end;
%mend mean_period;

options mprint;
data want;
   set have
   %mean_period;
run;

 

 

Regards,

Amir.

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