如何通过将它除以前几天的观察总和来调整变量？

Question

我想要写一个代码运行这将在下面示出的公式：

调整体积在下面所示的每一个名称和日期= IntradayVolume /（dailyvolume五最后天）

我使用的代码：

*Division for calculating adjusted volume; 
proc sort data=sampledata_sumvolso02 out=sampledata_sumvolso02; 
by TRD_STCK_CD TRD_EVENT_DT; 
run; 

*Adjusted intraday volume for days of a week; 
data sampledata_adjvol02; 
    do until(last.TRD_STCK_CD); 
      do until(last.TRD_EVENT_DT); 
       set sampledata_sumvolso02; 
       by TRD_STCK_CD TRD_EVENT_DT; 

       if first.TRD_STCK_CD then 
        n=0; 

       if first.TRD_EVENT_DT then 
        n+1; 

       if n>7 then 
        do; 
          if not missing(IntradayVolume) then 
           adjusted_volume=divide(IntradayVolume,temp); 
           else call missing(adjusted_volume); 
        end; 

       if last.TRD_EVENT_DT then 
        temp=dailyvolume; 
       output; 
      end; 
    end; 
    drop temp n; 
run; 

这里是我的数据样本：

data WORK.SAMPLEDATA_SUMVOLSO02; 
    infile datalines dsd truncover; 
    input TRD_STCK_CD:$15. TRD_PR:32. TRD_TUROVR:14. TRD_EVENT_DT:DATE9. TRD_EVENT_TM:TIME5. TRD_EVENT_ROUNDED:32. TRD_EVENT_ROUFOR:$5. CountedVOLUME:32. DailyVolume:32. IntradayVolume:32.; 
    format TRD_TUROVR 14. TRD_EVENT_DT DATE9. TRD_EVENT_TM TIME5.; 
    label TRD_STCK_CD="TRD_STCK_CD" TRD_PR="TRD_PR" TRD_TUROVR="TRD_TUROVR" TRD_EVENT_DT="TRD_EVENT_DT"; 
datalines4; 
BALI1,850,9260,24MAR2008,9:14,34200,9:30,7871000,, 
BALI1,850,2000,23MAR2008,9:15,34200,9:30,1700000,, 
BALI1,850,10000,22MAR2008,9:15,34200,9:30,8500000,, 
BALI1,850,6000,21MAR2008,9:15,34200,9:30,5100000,, 
BALI1,850,10000,20MAR2008,9:29,34200,9:30,8500000,31671000,31671000 
BANK1,1164,10729,20MAR2008,9:38,36000,10:00,12488556,,12488556 
BANK1,1148,2000,21MAR2008,11:24,41400,11:30,2296000,, 
BANK1,1147,1575,22MAR2008,11:24,41400,11:30,1806525,16591081,4102525 
BHMN1,1013,1500,14MAR2008,9:00,34200,9:30,1519500,, 
BHMN1,1013,1500,15MAR2008,9:00,34200,9:30,1519500,, 
BHMN1,1013,1500,16MAR2008,9:00,34200,9:30,1519500,, 
BHMN1,1013,1500,17MAR2008,9:00,34200,9:30,1519500,, 
BHMN1,1013,1500,18MAR2008,9:00,34200,9:30,1519500,, 
BHMN1,1013,1500,19MAR2008,9:00,34200,9:30,1519500,, 
BHMN1,1013,1000,20MAR2008,9:00,34200,9:30,1013000,, 
BHMN1,1013,450,21MAR2008,9:00,34200,9:30,455850,, 
BHMN1,1013,1500,22MAR2008,9:00,34200,9:30,1519500,, 
BHMN1,1013,1500,23MAR2008,9:00,34200,9:30,1519500,, 
BHMN1,1013,1500,24MAR2008,9:04,34200,9:30,1519500,, 
BHMN1,1013,1500,25MAR2008,9:04,34200,9:30,1519500,, 
BHMN1,1013,601,26MAR2008,9:05,34200,9:30,608813,, 
BHMN1,1013,697,27MAR2008,9:06,34200,9:30,706061,, 
BHMN1,1013,1500,28MAR2008,9:08,34200,9:30,1519500,, 
BHMN1,1013,1500,29MAR2008,9:08,34200,9:30,1519500,, 
BHMN1,1013,1500,12MAR2008,9:09,34200,9:30,1519500,, 
BHMN1,1013,1500,13MAR2008,9:16,34200,9:30,1519500,, 
BHMN1,1013,1500,14MAR2008,9:22,34200,9:30,1519500,,25576224 
BHMN1,1013,1500,15MAR2008,9:41,36000,10:00,1519500,,1519500 
BHMN1,1013,1500,16MAR2008,10:13,37800,10:30,1519500,, 
BHMN1,1013,1500,17MAR2008,10:13,37800,10:30,1519500,,3039000 
BHMN1,1013,1500,18MAR2008,11:25,41400,11:30,1519500,,1519500 
BHMN1,1013,1500,19MAR2008,11:51,43200,12:00,1519500,33173724,1519500 
CHML1,12000,745,20MAR2008,9:00,34200,9:30,8940000,, 
CHML1,12000,82,21MAR2008,9:00,34200,9:30,984000,, 
CHML1,11998,206,22MAR2008,9:07,34200,9:30,2471588,, 
CHML1,11998,414,23MAR2008,9:09,34200,9:30,4967172,, 
CHML1,11998,348,24MAR2008,9:12,34200,9:30,4175304,, 
CHML1,11996,82,25MAR2008,9:15,34200,9:30,983672,, 
CHML1,11996,1240,26MAR2008,9:16,34200,9:30,14875040,, 
CHML1,11996,414,27MAR2008,9:17,34200,9:30,4966344,, 
CHML1,11970,1000,28MAR2008,9:21,34200,9:30,11970000,, 
CHML1,11964,158,29MAR2008,9:22,34200,9:30,1890312,, 
CHML1,11990,1946,20MAR2008,9:23,34200,9:30,23332540,,79555972 
CHML1,11851,500,19MAR2008,10:42,39600,11:00,5925500,, 
CHML1,11852,1054,18MAR2008,10:44,39600,11:00,12492008,, 
CHML1,11900,2000,17MAR2008,10:56,39600,11:00,23800000,,42217508 
CHML1,11913,244,16MAR2008,11:08,41400,11:30,2906772,, 
CHML1,11913,56,15MAR2008,11:09,41400,11:30,667128,, 
CHML1,11968,944,14MAR2008,11:13,41400,11:30,11297792,, 
CHML1,11968,2056,13MAR2008,11:27,41400,11:30,24606208,, 
CHML1,11987,380,14MAR2008,11:29,41400,11:30,4555060,,44032960 
CHML1,11988,620,11MAR2008,11:30,43200,12:00,7432560,, 
CHML1,11981,1663,12MAR2008,11:52,43200,12:00,19924403,, 
CHML1,11981,765,24MAR2008,11:52,43200,12:00,9165465,202328868,36522428 
CRBN1,1486,1700,22MAR2008,9:00,34200,9:30,2526200,, 
CRBN1,1485,3353,24MAR2008,9:21,34200,9:30,4979205,7505405,7505405 
DADE1,1685,2972,24MAR2008,10:04,37800,10:30,5007820,,5007820 
DADE1,1632,2000,20MAR2008,11:49,43200,12:00,3264000,, 
DADE1,1631,5000,21MAR2008,11:49,43200,12:00,8155000,, 
DADE1,1630,3000,22MAR2008,11:49,43200,12:00,4890000,, 
DADE1,1630,2000,23MAR2008,11:50,43200,12:00,3260000,, 
DADE1,1630,8000,24MAR2008,11:50,43200,12:00,13040000,37616820,32609000 
DFRB1,7450,124,24MAR2008,10:54,39600,11:00,923800,,923800 
DFRB1,7450,132,24MAR2008,11:16,41400,11:30,983400,1907200,983400 
DJBR1,7491,3000,24MAR2008,10:06,37800,10:30,22473000,22473000,22473000 
DRZK1,14890,72,24MAR2008,11:58,43200,12:00,1072080,1072080,1072080 
FIBR1,2846,100,24MAR2008,11:17,41400,11:30,284600,284600,284600 
FKAS1,3584,5173,20MAR2008,9:15,34200,9:30,18540032,, 
FKAS1,3584,3000,21MAR2008,9:15,34200,9:30,10752000,, 
FKAS1,3585,1827,22MAR2008,9:15,34200,9:30,6549795,,35841827 
FKAS1,3585,183,23MAR2008,9:35,36000,10:00,656055,, 
FKAS1,3585,3200,24MAR2008,9:35,36000,10:00,11472000,,12128055 
FKAS1,3539,2000,25MAR2008,11:02,41400,11:30,7078000,, 
FKAS1,3538,8000,26MAR2008,11:02,41400,11:30,28304000,, 
FKAS1,3538,2000,27MAR2008,11:02,41400,11:30,7076000,, 
FKAS1,3537,8000,28MAR2008,11:02,41400,11:30,28296000,, 
FKAS1,3537,2000,29MAR2008,11:02,41400,11:30,7074000,, 
FKAS1,3535,8000,20MAR2008,11:02,41400,11:30,28280000,, 
FKAS1,3535,2000,19MAR2008,11:03,41400,11:30,7070000,, 
FKAS1,3535,6617,18MAR2008,11:03,41400,11:30,23391095,, 
FKAS1,3533,100,17MAR2008,11:03,41400,11:30,353300,, 
FKAS1,3533,1283,16MAR2008,11:07,41400,11:30,4532839,, 
FKAS1,3533,2763,15MAR2008,11:08,41400,11:30,9761679,, 
FKAS1,3529,10000,14MAR2008,11:15,41400,11:30,35290000,, 
FKAS1,3516,10000,13MAR2008,11:17,41400,11:30,35160000,, 
FKAS1,3516,10000,12MAR2008,11:19,41400,11:30,35160000,, 
FKAS1,3516,39,11MAR2008,11:19,41400,11:30,137124,, 
FKAS1,3515,2000,19MAR2008,11:25,41400,11:30,7030000,, 
FKAS1,3515,198,24MAR2008,11:25,41400,11:30,695970,, 
FKAS1,3515,9802,20MAR2008,11:25,41400,11:30,34454030,,299144037 
FKAS1,3515,4000,21MAR2008,11:48,43200,12:00,14060000,, 
FKAS1,3513,6000,22MAR2008,11:52,43200,12:00,21078000,, 
FKAS1,3514,2000,23MAR2008,11:52,43200,12:00,7028000,, 
FKAS1,3514,1085,24MAR2008,11:52,43200,12:00,3812690,, 
FKAS1,3500,1000,25MAR2008,11:56,43200,12:00,3500000,396592609,49478690 
FOLD1,3198,390,24MAR2008,9:09,34200,9:30,1247220,,1247220 
FOLD1,3197,2000,27MAR2008,10:31,39600,11:00,6394000,, 
FOLD1,3191,2000,28MAR2008,10:32,39600,11:00,6382000,, 
FOLD1,3190,4000,20MAR2008,10:33,39600,11:00,12760000,, 
FOLD1,3190,542,18MAR2008,10:33,39600,11:00,1728980,, 
;;;; 

现在，我要划分Intradayvolume variabl e通过在今天之前的一周内汇总Dailyvolume变量。指定SAS诊断一周的几天并在数据集中使用日期变量进行调整非常重要。因为我的数据集的日期变量的格式是ddmmyy。我的意思是，SAS应该找出今天的某一天是哪一天，并将今天之前一周的Dailyvolume变量汇总为分母。

如何运行该公式？

在此先感谢。

Answer 1

data sampledata_adjvol (drop=cnt dv_:); 
    set Sampledata_SumVolSo; 
    by TRD_STCK_CD TRD_EVENT_DT; 
    retain dv_1 dv_2 dv_3 dv_4 cnt 0 dv_sum; 
    if first.TRD_STCK_CD then do; 
     cnt=0; 
     dv_1=0; 
     dv_2=0; 
     dv_3=0; 
     dv_4=0; 
     dv_sum=0; 
    end; 
     adjusted_volume_5=intradayvolume/dv_sum; 
    if last.TRD_EVENT_DT then do; 
     cnt=cnt+1; 
     if cnt=1 then dv_4=dailyvolume; 
     else if cnt=2 then dv_3=dailyvolume; 
     else if cnt=3 then dv_2=dailyvolume; 
     else if cnt=4 then dv_1=dailyvolume; 
     else do; 
      dv_sum=dailyvolume+dv_1+dv_2+dv_3+dv_4; 
      dv_4=dv_3; 
      dv_3=dv_2; 
      dv_2=dv_1; 
      dv_1=dailyvolume; 
     end; 
    end; 
run; 

Answer 2

我不确定你到底在做什么，但一种方法可能是创建一个临时数组并将其与日期相关联。然后查看该索引。在假期等情况下，你会遇到一些简单的方法问题，但它应该给你至少一个大致正确的答案。

比如（再次提示，我不完全理解你的变量或者你在做什么，所以这是一个近似的想法）：

*Adjusted intraday volume for days of a week; 
data sampledata_adjvol02; 
    array prevdat[32767] _temporary_; 
    do until(last.TRD_STCK_CD); 
      do until(last.TRD_EVENT_DT); 
       set sampledata_sumvolso02; 
       by TRD_STCK_CD TRD_EVENT_DT; 

       if first.TRD_STCK_CD then 
        n=0; 

       if first.TRD_EVENT_DT then 
        n+1; 

       if n>7 then 
        do; 
          if not missing(IntradayVolume) then 
           adjusted_volume=divide(IntradayVolume,prevdat[TRD_EVENT_DT-7]); 
           else call missing(adjusted_volume); 
        end; 

       if last.TRD_EVENT_DT then 
        temp=dailyvolume; 
       output; 
       prevdat[TRD_EVENT_DT] = sum(prevdat[TRD_EVENT_DT],countedVolume); 
      end; 

    end; 

    call missing(of prevdat[*]); 
    drop temp n; 
run;