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s2d
Calcite | Level 5 s2d
Calcite | Level 5

Greetings:

I have a dataset like the following:

DateDaysVar1  .....Var10
1/1/2011105
1/2/2011158
1/3/2011123
1/4/2011369
1/5/2011593
1/6/20116112
1/7/20114122
1/8/2011796

I would like to sum the values of each variable in the array Var1 - Var 10 using the number of days in the cycle (variable is named 'Days'). Such that I could produce the following dataset as output:

DateDaysVar1 ......Var10Cycle_Sum_Var1....Cycle_Sum_Var10
1/1/2011105
1/2/2011158
1/3/2011123
1/4/20113693320
1/5/20115935228
1/6/201161126330
1/7/201141223816
1/8/201179674

33

Your suggestions are much appreciated! I know proc means, basic arrays and some do loops, etc. I'm not sure if a Macro or Proc SQL is called for in this situation.

2 REPLIES 2
art297
Opal | Level 21

If you aren't missing any dates and you will never need to accumulate beyond 10 days, then you could use something like:

data have;

  informat date mmddyy10.;

  format date mmddyy10.;

  input Date Days Var1-Var10;

  cards;

1/1/2011 . 10 1 1 1 1 1 1 1 1 5

1/2/2011 . 15 1 1 1 1 1 1 1 1 8

1/3/2011 . 12 1 1 1 1 1 1 1 1 3

1/4/2011 3 6  1 1 1 1 1 1 1 1 9

1/5/2011 5 9  1 1 1 1 1 1 1 1 3

1/6/2011 6 11 1 1 1 1 1 1 1 1 2

1/7/2011 4 12 1 1 1 1 1 1 1 1 2

1/8/2011 7 9  1 1 1 1 1 1 1 1 6

;

data want (drop=i j last:);

  set have;

  array current(10) var1-var10;

  array last(10,10);

  array cycle_sum_var(10);

  do i=1 to 10;

    last(i,1)=lag1(current(i));

    last(i,2)=lag2(current(i));

    last(i,3)=lag3(current(i));

    last(i,4)=lag4(current(i));

    last(i,5)=lag5(current(i));

    last(i,6)=lag6(current(i));

    last(i,7)=lag7(current(i));

    last(i,8)=lag8(current(i));

    last(i,9)=lag9(current(i));

    last(i,10)=lag10(current(i));

  end;

  if not missing(days) then do i=1 to 10;

    cycle_sum_var(i)=current(i);

    do j=1 to days-1;

      cycle_sum_var(i)=sum(cycle_sum_var(i),last(i,j));

    end;

  end;

run;

s2d
Calcite | Level 5 s2d
Calcite | Level 5

Thanks very much, art. 'Day's goes up to 30 in my dataset, so I made the necessary adjustments and it works quite well. Many thanks!

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