Hi again!   I can't seem to wrap my head around creating a proportion in a long format of my data. I will provide a portion of my data below:   input STUDYNO:32. PID:BEST. Day_1826:DATE9. Day_InitialIW:DATE9. TRICHOT_1YR:BEST12. Personal_consumption_expenditure:BEST12. Month:32. Interval:$5. TimeFrame:$20. ExpenseType:$20. Value:32.; format PID BEST. Day_1826 DATE9. Day_InitialIW DATE9. TRICHOT_1YR BEST12. Personal_consumption_expenditure BEST12.; label STUDYNO="Sample size: 55,144,41,185,191, Total:616" PID="SUBJID#" Day_1826="Day1826" Day_InitialIW="IWInitial" TRICHOT_1YR="RA 273, UR 140, RNA 80, Missing 123"; datalines; 2 486 30DEC1992 05OCT1993 1 68.892 1 Month PreResYr House 3164.5029543 2 486 30DEC1992 05OCT1993 1 68.892 1 Month PreResYr Consume 820.0784735 2 486 30DEC1992 05OCT1993 1 68.892 1 Month PreResYr Durable . 2 486 30DEC1992 05OCT1993 1 68.892 1 Month PreResYr Health 332.71026714 2 486 30DEC1992 05OCT1993 1 68.892 1 Month PreResYr Insure . 2 486 30DEC1992 05OCT1993 1 68.892 1 Month PreResYr Loan 0 2 486 30DEC1992 05OCT1993 1 68.892 1 Month PreResYr Tax . 2 486 30DEC1992 05OCT1993 1 68.892 1 Month PreResYr Educa . 2 486 30DEC1992 05OCT1993 1 68.892 1 Month PreResYr Gift 16262.542769 2 486 30DEC1992 05OCT1993 1 68.892 1 Month PreResYr Enter 209.70802449 2 486 30DEC1992 05OCT1993 1 68.892 1 Month PreResYr Recre 0 2 486 30DEC1992 05OCT1993 1 68.892 1 Month PreResYr FinPlan . 2 486 30DEC1992 05OCT1993 1 68.892 1 Month PreResYr Legala 0 2 486 30DEC1992 05OCT1993 1 68.892 1 Month PreResYr IncomeTL 61368.08592 2 486 30DEC1992 05OCT1993 1 68.892 1 Month PreResYr Trans 3334.881462 2 486 30DEC1992 05OCT1993 1 68.892 1 Month PreResYr AlcSpend 72.87460203 2 486 30DEC1992 05OCT1993 1 68.892 1 Month PostResYr House 3075.6491125 2 486 30DEC1992 05OCT1993 1 68.892 1 Month PostResYr Consume 808.7741655 2 486 30DEC1992 05OCT1993 1 68.892 1 Month PostResYr Durable . 2 486 30DEC1992 05OCT1993 1 68.892 1 Month PostResYr Health 316.74626874 What I want to do is create a proportion of the PostResYr Value for each ExpenseType over the PreResYr Value for each expense type. I feel that I am on the right track but cant think of a way to complete this. Ultimately, i want to do a stacked bar chart with the x axis being the expense type, the bars being the sum of the proportions and the different segments being the Trichot_1YR.    The code that I was trying to do was the following:   data Proportion3; set Proportion2; if Value = 0 then Value = 1; run; %macro Val(Exp); data Proportion3; set Proportion3; If TimeFrame = 'PreResYr' then PreVal = Value; If TimeFrame = 'PostResYr' then PostVal = Value; if ExpenseType = '&Exp' then Proportion = PostVal/PreVal ; run; %mend; %Val(House); %Val(Consume); %Val(Durable); %Val(Trans); %Val(Health); %Val(Insure); %Val(Loan); %Val(Tax); %Val(Educa); %Val(Gift); %Val(Enter); %Val(Recre); %Val(FinPlan); %Val(Legala); %Val(AlcSpend); %Val(IncomeTL); However, I cannot populate "Proportion" because the PreVal and PostVal are not on the same row.   I have managed to create it the long way by creating a new variable for each ExpenseType such that PostResYr_House/PreResYr_House = PropHouse   However, I cannot put each of the variables in the X-axis of my stacked bar chart.   Any help, resources, or direction would be appreciated!   My thoughts as of now are to make two different datasets for Pre and Post and then merge them for the proportion maybe using Proc sql as it seems easier to join?   Let me know if you need clarification or any additional information. ... View more

Hi all!   I am trying to create a correlation matrix where I get the pearson value for each of the ExpenseType's against the others using the "Value" variable. However, I only want these for quarters (months 1-4, 5-8, etc..). A snap shot of my data is below:   input STUDYNO:32. PID:BEST. Day_1826:DATE9. Day_InitialIW:DATE9. TRICHOT_1YR:BEST12. Personal_consumption_expenditure:BEST12. Month:32. Interval:$5. TimeFrame:$20. ExpenseType:$20. Value:32.; format PID BEST. Day_1826 DATE9. Day_InitialIW DATE9. TRICHOT_1YR BEST12. Personal_consumption_expenditure BEST12.; label STUDYNO="Sample size: 55,144,41,185,191, Total:616" PID="SUBJID#" Day_1826="Day1826" Day_InitialIW="IWInitial" TRICHOT_1YR="RA 273, UR 140, RNA 80, Missing 123"; datalines; 2 486 30DEC1992 05OCT1993 1 68.892 1 Month PreResYr House 3164.5029543 2 486 30DEC1992 05OCT1993 1 68.892 1 Month PreResYr Consume 820.0784735 2 486 30DEC1992 05OCT1993 1 68.892 1 Month PreResYr Durable . 2 486 30DEC1992 05OCT1993 1 68.892 1 Month PreResYr Health 332.71026714 2 486 30DEC1992 05OCT1993 1 68.892 1 Month PreResYr Insure . 2 486 30DEC1992 05OCT1993 1 68.892 1 Month PreResYr Loan 0 2 486 30DEC1992 05OCT1993 1 68.892 1 Month PreResYr Tax . 2 486 30DEC1992 05OCT1993 1 68.892 1 Month PreResYr Educa . 2 486 30DEC1992 05OCT1993 1 68.892 1 Month PreResYr Gift 16262.542769 2 486 30DEC1992 05OCT1993 1 68.892 1 Month PreResYr Enter 209.70802449 2 486 30DEC1992 05OCT1993 1 68.892 1 Month PreResYr Recre 0 2 486 30DEC1992 05OCT1993 1 68.892 1 Month PreResYr FinPlan . 2 486 30DEC1992 05OCT1993 1 68.892 1 Month PreResYr Legala 0 2 486 30DEC1992 05OCT1993 1 68.892 1 Month PreResYr IncomeTL 61368.08592 2 486 30DEC1992 05OCT1993 1 68.892 1 Month PreResYr Trans 3334.881462 2 486 30DEC1992 05OCT1993 1 68.892 1 Month PreResYr AlcSpend 72.87460203 2 486 30DEC1992 05OCT1993 1 68.892 1 Month PostResYr House 3075.6491125 2 486 30DEC1992 05OCT1993 1 68.892 1 Month PostResYr Consume 808.7741655 2 486 30DEC1992 05OCT1993 1 68.892 1 Month PostResYr Durable . 2 486 30DEC1992 05OCT1993 1 68.892 1 Month PostResYr Health 316.74626874 The code that I have been tinkering with looks like this:    proc corr data= Sub.Tall_M_IndEXP_Better_JB_011119; var value; by ExpenseType; where Month between 1 and 4; run;  However, this gives me the 15 separate correlations when I want a matrix.   Any suggestions? Am i going to have to transpose these expense types into variables to able to get a correlation between them?     ... View more

Hi all!   I have some time series data with which I want to plot the means and medians. I am wondering if you are able to call upon the mean and median (and other functions) within the proc sgplot?   For instance, I have the following code where I am making 14 separate line plots :   %Macro Line(ET); proc sgplot data = Sub.Tall_M_IndEXP_Better_JB_011119; where ExpenseType like &ET; series x = Month y = mean(Value) / group= Trichot_1YR curvelabel; xaxis values =(1 to 12 by 1); run; %mend; %Line('Tax') %Line('Trans') I am getting an error when trying to utilize the function in this way that states that the variable MEAN is not found. The way around it is simply take the means before and utilize this new data, but it had me thinking if you could utilize these functions in the middle of a Proc step?   I was hoping that someone would be able to explain to me why or why not as I am still trying to learn the intricacies of SAS.   Like always, if you see any problems/inefficiencies in my code, please point it out! I am always trying to learn. Also, thank you in advance! ... View more

Hello!   I was wondering if there is a way to do a pie chart where each slice is a different variable?    The person working on the data before me left a mess and I am trying to make sense of a few things. I have a very large dataset that i subsetted into the variables that I need. Ideally, I would want a piechart grouped by the variable Tricho_1yr (3 rankings) with 14 slices that are the sum of all the numbers in each of the  expenditure values across the rankings. I would replicate this 4 times for 4 different quarters.   The issue is that my data is wide and not long. Below I try to give you a sample of my data, but it is a mess and hard to read.   label STUDYNO="Sample size: 55,144,41,185,191, Total:616" PID="SUBJID#" Day_1826="Day1826" Day_InitialIW="IWInitial" TRICHOT_1YR="RA 273, UR 140, RNA 80, Missing 123" PostResYr_HOUSE_P_Tot="Housing Total/Total Expenditure" PostResYr_CONSUME_P_Tot="Consumab le Goods Total/Total Expenditure" PostResYr_DURABLE_P_Tot="Durable Goods Total/Total Expenditure" PostResYr_TRANS_P_Tot="Transportation Total/Total Expenditure" PostResYr_HEALTH_P_Tot="Health Care Total/Total Expenditure" PostResYr_INSURE_P_Tot="Insurance Total/Total Expenditure" PostResYr_LOAN_P_Tot="Loan Payments Total/Total Expenditure" PostResYr_TAX_P_Tot="Taxes Total/Total Expenditure" PostResYr_EDUCA_P_Tot="Educational Expenses Total/Total Expenditure" PostResYr_GIFT_P_Tot="Gifts or Contributions Tota l/Total Expenditure" PostResYr_ENTER_P_Tot="Entertainment Total/Total Expenditure" PostResYr_RECRE_P_Tot="RECREATION TOTAL/Total Expenditure" PostResYr_FINPLAN_P_Tot="Financial Planning Total/Total Expenditure" PostResYr_LEGALA_P_Tot="LEGAL EXPENSES TOTAL/ Total Expenditure" PostResYr1stQ_HOUSE_P_Tot="Housing Total/Total Expenditure" PostResYr1stQ_CONSUME_P_Tot="Consumable Goods Total/Total Expenditure" PostResYr1stQ_DURABLE_P_Tot="Durable Goods Total/Total Expenditure" PostResYr1stQ_TRANS_P_Tot="Transportat ion Total/Total Expenditure" PostResYr1stQ_HEALTH_P_Tot="Health Care Total/Total Expenditure" PostResYr1stQ_INSURE_P_Tot="Insurance Total/Total Expenditure" PostResYr1stQ_LOAN_P_Tot="Loan Payments Total/Total Expenditure" PostResYr1stQ_TAX_P_Tot="Taxes Tot al/Total Expenditure" PostResYr1stQ_EDUCA_P_Tot="Educational Expenses Total/Total Expenditure" PostResYr1stQ_GIFT_P_Tot="Gifts or Contributions Total/Total Expenditure" PostResYr1stQ_ENTER_P_Tot="Entertainment Total/Total Expenditure" PostResYr1stQ_RECRE_P _Tot="RECREATION TOTAL/Total Expenditure" PostResYr1stQ_FINPLAN_P_Tot="Financial Planning Total/Total Expenditure" PostResYr1stQ_LEGALA_P_Tot="LEGAL EXPENSES TOTAL/Total Expenditure" PostResYr2ndQ_HOUSE_P_Tot="Housing Total/Total Expenditure" PostResYr2ndQ _CONSUME_P_Tot="Consumable Goods Total/Total Expenditure" PostResYr2ndQ_DURABLE_P_Tot="Durable Goods Total/Total Expenditure" PostResYr2ndQ_TRANS_P_Tot="Transportation Total/Total Expenditure" PostResYr2ndQ_HEALTH_P_Tot="Health Care Total/Total Expenditure " PostResYr2ndQ_INSURE_P_Tot="Insurance Total/Total Expenditure" PostResYr2ndQ_LOAN_P_Tot="Loan Payments Total/Total Expenditure" PostResYr2ndQ_TAX_P_Tot="Taxes Total/Total Expenditure" PostResYr2ndQ_EDUCA_P_Tot="Educational Expenses Total/Total Expenditur e" PostResYr2ndQ_GIFT_P_Tot="Gifts or Contributions Total/Total Expenditure" PostResYr2ndQ_ENTER_P_Tot="Entertainment Total/Total Expenditure" PostResYr2ndQ_RECRE_P_Tot="RECREATION TOTAL/Total Expenditure" PostResYr2ndQ_FINPLAN_P_Tot="Financial Planning To tal/Total Expenditure" PostResYr2ndQ_LEGALA_P_Tot="LEGAL EXPENSES TOTAL/Total Expenditure" PostResYr3rdQ_HOUSE_P_Tot="Housing Total/Total Expenditure" PostResYr3rdQ_CONSUME_P_Tot="Consumable Goods Total/Total Expenditure" PostResYr3rdQ_DURABLE_P_Tot="Durab le Goods Total/Total Expenditure" PostResYr3rdQ_TRANS_P_Tot="Transportation Total/Total Expenditure" PostResYr3rdQ_HEALTH_P_Tot="Health Care Total/Total Expenditure" PostResYr3rdQ_INSURE_P_Tot="Insurance Total/Total Expenditure" PostResYr3rdQ_LOAN_P_Tot="L oan Payments Total/Total Expenditure" PostResYr3rdQ_TAX_P_Tot="Taxes Total/Total Expenditure" PostResYr3rdQ_EDUCA_P_Tot="Educational Expenses Total/Total Expenditure" PostResYr3rdQ_GIFT_P_Tot="Gifts or Contributions Total/Total Expenditure" PostResYr3rdQ_E NTER_P_Tot="Entertainment Total/Total Expenditure" PostResYr3rdQ_RECRE_P_Tot="RECREATION TOTAL/Total Expenditure" PostResYr3rdQ_FINPLAN_P_Tot="Financial Planning Total/Total Expenditure" PostResYr3rdQ_LEGALA_P_Tot="LEGAL EXPENSES TOTAL/Total Expenditure" P ostResYr4thQ_HOUSE_P_Tot="Housing Total/Total Expenditure" PostResYr4thQ_CONSUME_P_Tot="Consumable Goods Total/Total Expenditure" PostResYr4thQ_DURABLE_P_Tot="Durable Goods Total/Total Expenditure" PostResYr4thQ_TRANS_P_Tot="Transportation Total/Total Expe nditure" PostResYr4thQ_HEALTH_P_Tot="Health Care Total/Total Expenditure" PostResYr4thQ_INSURE_P_Tot="Insurance Total/Total Expenditure" PostResYr4thQ_LOAN_P_Tot="Loan Payments Total/Total Expenditure" PostResYr4thQ_TAX_P_Tot="Taxes Total/Total Expenditure " PostResYr4thQ_EDUCA_P_Tot="Educational Expenses Total/Total Expenditure" PostResYr4thQ_GIFT_P_Tot="Gifts or Contributions Total/Total Expenditure" PostResYr4thQ_ENTER_P_Tot="Entertainment Total/Total Expenditure" PostResYr4thQ_RECRE_P_Tot="RECREATION TOT AL/Total Expenditure" PostResYr4thQ_FINPLAN_P_Tot="Financial Planning Total/Total Expenditure" PostResYr4thQ_LEGALA_P_Tot="LEGAL EXPENSES TOTAL/Total Expenditure"; datalines; 2 486 30DEC1992 05OCT1993 1 0.2206379704 0.0740041108 . 0.1281328319 0.0582095192 . 0.0592032887 . . 0.3090553333 0.0158580237 0 . 0 0.1460914139 0.0427167877 . 0.166595472 0.0153780436 . 0.0170867151 . . 0.4527979496 0.010252029 0 . 0 0.3930432118 0.1149249157 . 0.0459699663 0.1342323016 . 0.1838798652 . . 0 0.0160894882 0 . 0 0.4021006427 0.1175732873 . 0.0470293149 0.1299576736 . 0.1881172598 . . 0 0.0164602602 0 . 0 0.1716809339 0.0910774185 . 0.1420807729 0.062661264 . 0 . . 0.3658279347 0.0273232256 0 . 0 2 495 05MAR1993 25AUG1993 3 0.2533392991 0.119096185 . 0.0085538696 0.047112082 . 0 . . 0.0131597994 0.0356630565 0 . 0 0.295661769 0.1509959928 . 0.0087113073 0.0290376909 . 0 . . 0 0.0278761833 0 . 0 0.4112680381 0.195732269 . 0.0153515505 0.0107460854 . 0 . . 0 0.0560331593 0 . 0 0.3346513573 0.1482776975 . 0.0114059767 0 . 0 . . 0 0.0570298837 0 . 0 0.1350372802 0.0598324691 . 0.0046024976 0.0902089534 . 0 . . 0.0306833175 0.0230124881 0 . 0 2 496 22JUN1993 30AUG1993 3 0.2596819952 0.0963660052 . 0.0893913669 0.0056213503 . 0.0749513374 . . 0.0159866444 0.0130495632 0.0180240121 . 0.0059485188 0.2595605549 0.0416295231 . 0.1810645004 0.0002392501 . 0.0241164134 . . 0.0083737546 0.0033973519 0 . 0 0.3066371174 0.1429062703 . 0.0378281304 0.001146307 . 0.1155477437 . . 0 0.0137556838 0 . 0 0.2539074859 0.1183319623 . 0.0782762767 0.0210719484 . 0.0956780358 . . 0 0.0223058913 0.0094918686 . 0 0.2298570733 0.1071234211 . 0.0283561997 0.0014321313 . 0.0866153009 . . 0.0515567267 0.015696159 0.0608369375 . 0.0229141008 2 533 21AUG1993 15NOV1993 1 0.2807925044 0.2210618778 . 0.091255124 0 . 0.10833496 . . 0.0094345761 0.065066042 0.0130132084 . 0 0.3424818993 0.2424650615 . 0.0572486951 0 . 0.1212325307 . . 0.0151540663 0.0008418926 0 . 0 0.2162029299 0.1754989677 . 0.1528856553 0 . 0.085537312 . . 0.0196637499 0.0653819683 0 . 0 0.3091087996 0.2509136913 . 0.0639583919 0 . 0.122294068 . . 0 0.0934776497 0 . 0 0.2926537131 0.2375565611 . 0.0605536332 0 . 0.1157838701 . . 0 0.0885014639 0.0532339633 . 0 2 557 15JUN1993 16NOV1993 3 0.1911581952 0.1958830116 . 0.1699949553 0 . 0.0855142544 . . 0.0167337246 0.0032483112 0.0004921684 . 0 0.2398427261 0.5766710354 . 0.0397553517 0 . 0.0884665793 . . 0 0.0170380079 0 . 0 0.2266657042 0.2540965856 . 0.1654515267 0 . 0.0967299502 . . 0.079405183 0.0077961452 0 . 0 0.1483161752 0.1035305066 . 0.1506427034 0 . 0.0697958471 . . 0.0075612168 0 0.0011632641 . 0 0.2135857274 0.1490912137 . 0.2504397353 0 . 0.1005109306 . . 0 0 0 . 0 2 688 17DEC1993 16MAR1994 3 0.2931831752 0.1577749314 . 0.0683423694 0.0776550975 . 0.1172868659 . . 0.006413085 0.0080891058 0 . 0 0.1312013142 0.0986386855 . 0.0160215972 0.0133722999 . 0.0530812008 . . 0.0289948847 0 0 . 0 0.3343801101 0.1705562978 . 0.0822859331 0.1349489304 . 0.132405547 . . 0 0.00615798 0 . 0 0.334203543 0.1751687536 . 0.0814381047 0.0623846614 . 0.1359862692 . . 0 0.0063245139 0 . 0 0.349270049 0.178151166 . 0.0859501239 0.0892318559 . 0.138301563 . . 0 0.0189340309 0 . 0 2 724 31AUG1993 01MAR1994 2 0.3664520868 0.1343249576 . 0.065054087 0.0462156069 . 0.2385203171 . . 0.0170031592 0.0070053016 0.0034006318 . 0 0.3965744416 0.1026635019 . 0.0375455093 0.1173297164 . 0.2740822176 . . 0 0.0023465943 0 . 0 0.269151996 0.0756492297 . 0.0891864602 0.039815384 . 0.1860174742 . . 0.0796307681 0.0238892304 0 . 0 0.3900514326 0.177731112 . 0.0735533371 0.0149061716 . 0.2399370012 . . 0 0.0024608923 0 . 0 0.3913628563 0.1783286762 . 0.0679020729 0 . 0.2407437129 . . 0 0.0024691663 0.0137175905 . 0 2 831 26NOV1993 04APR1994 1 0.361376673 0.073040153 . 0.1077119184 0.1370299554 . 0.1219885277 . . 0.0101975781 0.0136392607 0.0191204589 . 0 0 0.1449459631 . 0.0330578512 0.1830896376 . 0.1048951049 . . 0.0305149396 0.0305149396 0 . 0 0.3441317047 0.1227827934 . 0.0106213489 0.1274561869 . 0.1698353691 . . 0.0424853956 0.009346787 0 . 0 0.4019851117 0.047311828 . 0.2522746071 0.0099255583 . 0.1081885856 . . 0 0.0109181141 0.0496277916 . 0 0.4563380282 0.0537089202 . 0.014084507 0.2685446009 . 0.1228169014 . . 0 0.0123943662 0 . 0 2 885 18NOV1993 26APR1994 1 0.4789861949 0.091220423 . 0.0335486241 0.0875447672 . 0 . . 0.2246778291 0.0015586642 0 . 0 0.6764631628 0.1383394835 . 0.0155628028 0 . 0 . . 0.0121044022 0 0 . 0 0.3808604018 0.067178245 . 0.0445894847 0.1392204434 . 0 . . 0.3504850323 0.002478708 0 . 0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 907 13DEC1993 18MAY1994 2 0.0930468131 0.1841751352 . 0.267917267 0.0441252928 . 0.1741030575 . . 0.0326143469 0.0083454358 0 . 0.0191849099 0.1468605889 0.3263568641 . 0.1780773324 0 . 0.1755941823 . . 0.008868393 0.0223483505 0 . 0 0.0412113162 0.0741210723 . 0.3910627776 0.0177890574 . 0.0978398155 . . 0.0192714788 0.0017789057 0 . 0.0148242145 0.1071566234 0.1927277399 . 0.249775151 0.0693819864 . 0.2544006167 . . 0 0.0046254658 0 . 0.038545548 0.0911575036 0.1639523445 . 0.2124822385 0.1158596568 . 0.2164170948 . . 0.109301563 0.0039348563 0 . 0.0327904689 2 936 28DEC1992 30MAR1994 3 0.1223633706 0.2276914332 . 0.0553024266 0.1386632518 . 0.142556443 . . 0.0373945785 0.0297079151 0.0105951306 . 0 0.0794634836 0.1976736244 . 0.081959031 0.0397317418 . 0.080645585 . . 0.0131344601 0.0288958122 0 . 0 0.1467517074 0.2492897594 . 0.0460950876 0.1903256759 . 0.1766664785 . . 0 0.0310436304 0.0310436304 . 0 0.147228147 0.2500990959 . 0.0673851904 0.1909435814 . 0.1772400385 . . 0 0.0311444157 0.0084939316 . 0 0.1335364914 0.2268408348 . 0.0179760662 0.1731865573 . 0.1607573916 . . 0.136960504 0.028248104 0.0077040284 . 0 2 992 01JAN1993 19MAY1994 1 0.1444450025 0.1221615635 . 0.0785801158 0.0123973484 . 0.0079470182 . . 0.0400529716 0.2762542461 0.2066224728 . 0 0.0982691234 0.0798436628 . 0.0437744277 0.0100502513 . 0 . . 0.0067001675 0.5371300949 0 . 0 0.1268880836 0.1501601339 . 0.0786816938 0 . 0 . . 0 0.421736649 0.2077861631 . 0 0.4304929363 0.3202065363 . 0.1585367 0 . 0 . . 0 0.0407307727 0 . 0 0.1136223619 0.0845138675 . 0.0831907541 0.024808376 . 0.0206736466 . . 0.0992335039 0.0583823781 0.4134729328 . 0 2 1034 07JAN1994 26JUL1994 1 0.2935014118 0.1913426064 . 0.0683742474 0.0577527045 . 0.1813094288 . . 0.0226056162 0.0103738102 0.0131298374 . 0 0.3272611058 0.1980398423 . 0.1065303079 0.0792585491 . 0.189623948 . . 0.0085224246 0.0170448493 0.0034089699 . 0 0.3377146991 0.2080751524 . 0.0686924876 0.0584587088 . 0.2460312565 . . 0.00560755 0.0119160438 0 . 0 0.3174915056 0.178723756 . 0.015575055 0.0161740956 . 0.1803112136 . . 0 0.0077875275 0.0479232461 . 0 0.2164194301 0.1850821012 . 0.0857491643 4 The SAS System 09:44 Tuesday, December 11, 2018 0.0772561086 . 0.1289307243 . . 0.0644653621 0.0066511882 0 . 0 2 1035 16FEB1994 21JUN1994 1 0.3806066891 0.0980036298 . 0.1239305159 0.0474980555 . 0.0534093855 . . 0.0679284418 0.0145190563 0.0194451646 . 0 0.5304518664 0.1452427729 . 0.0294695481 0.0084198709 . 0.2168116756 . . 0 0 0 . 0 0.45875 0.118125 . 0.18625 0.00225 . 0.064375 . . 0 0.0175 0.09375 . 0 0.6119857796 0.1523616049 . 0.093956323 0.0045708481 . 0 . . 0 0.0355510411 0 . 0 0.206135599 0.0513200661 . 0.1439812967 0.0984775047 . 0 . . 0.1493984148 0.0119746821 0 . 0 2 1051 13MAR1994 07JUL1994 1 0.3317276134 0.0363172016 . 0.0779848438 0.0115534003 . 0.3586370028 . . 0.0708709896 0.0081065345 0 . 0 0.5484502691 0 . 0.0307843618 0 . 0.1702401618 . . 0 0.0046273852 0 . 0 0.2258039225 0.0103987508 . 0.054413527 0.015680656 . 0.6165559667 . . 0.0108113997 0.0011554168 0 . 0 0.4282522989 0.0856508135 . 0.1267295981 0.0132654848 . 0.2958574544 . . 0 0.0022993507 0 . 0 0.2773267615 0.062384747 . 0.1080588173 0.0122794111 . 0.1786077711 . . 0.2349104724 0.0227436048 0 . 0 ;;;;   I'm working on something akin to this but can't make sense of how to accomplish this goal as I am very new to graphs/charts in SAS.   proc gchart data=Piecharts(where=(Trichot_1yr="1" or Trichot_1yr="2" or Trichot_1yr="3" )); pie sum(PostResYr1stQ_:) / group=Trichot_1yr across=3 other=0 clockwise value=none slice=outside percent=outside; run; quit; Help would be much appreciated.  ... 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Hi all,   I was wondering if there is any advantage of doing data coding in SAS over excel? It seems to me that the conventions in SAS are roughly the same in this situation as doing a Ctrl + F.    I have a dataset with many variables that are mostly character and am looking to code them into nominal and ordinal variables. I also am looking to code missing values and change variable names as well as label the methodology behind the coding. I was wondering what the advantages of SAS are since it came directly from RedCap (survey much like Qualtrics) and there are few free response answers. I have included a picture of part of the data as a reference. I was reading up and saw that CSV is a better format to import into SAS and plan to use that in the process, but was wondering if anyone had any pros and cons from their experience.    ... View more