I realize arrays are used to group data when you want to do process it all in one data step and it needs an array, do, end statement. I was instructed to transpose this data so that time and concentration would be variables and they would all show in relation to the subjects (observations). I was able to accomplish this by transposing each of the variables individually and then merging them. Now I am trying to find the maximum value of T and C for each observation using an array statement, but I just keep getting a bunch of errors. I am then supposed to find the mean, min and max which I know I can use the PROC MEANS statement, which I have done. When I do this final step, no errors show, but I am not getting any table to check the result. Below I've put the code I have come up with followed by the errors. Any guidance as to where I went wrong or what I am misunderstanding would be greatly appreciated. I am VERY new to SAS as you can probably tell.     proc import out=Project2_F17 datafile='C:\Users\savanahb\Downloads\Project2_f17.xlsx' DBMS=EXCEL2000 REPLACE; getnames=yes; run; data one; set Project2_F17 (keep=subject time concentration); run; proc sort data=one; by subject; run; proc transpose data=one out=two prefix=T; by subject; var time; run; proc transpose data=one out=three prefix=C; by subject; var concentration; run; data transposed; merge final final2; by subject; run; proc print data=transposed; title 'Transposed Data'; run; data transposed; array max[13] T1-T13; maximum=max(of Time[*]); array max[13] C1-C13; maximum=max(of Concentration[*]); do n=i to 13; if max[i]=maximum then max=i; end; drop i; run; data Maximum; set transposed; run; proc print data=Maximum; title 'Maximum Values'; run; proc means data=transposed; var T1-T13 C1-C13; run; data MMM; set transposed; run; proc print data=MMM; title 'Min Max Mean';     1523 proc import out=Project2_F17 1524 datafile= 'C:\Users\savanahb\Downloads\Project2_f17.xlsx' 1525 DBMS= EXCEL2000 REPLACE; 1526 getnames=yes; 1527 run; NOTE: WORK.PROJECT2_F17 data set was successfully created. NOTE: The data set WORK.PROJECT2_F17 has 91 observations and 3 variables. NOTE: PROCEDURE IMPORT used (Total process time): real time 0.31 seconds cpu time 0.18 seconds 1528 1529 data one; 1530 set Project2_F17 (keep = subject time concentration); 1531 run; NOTE: There were 91 observations read from the data set WORK.PROJECT2_F17. NOTE: The data set WORK.ONE has 91 observations and 3 variables. NOTE: DATA statement used (Total process time): real time 0.01 seconds cpu time 0.01 seconds 1532 proc sort data=one; 1533 by subject; 1534 run; NOTE: There were 91 observations read from the data set WORK.ONE. NOTE: The data set WORK.ONE has 91 observations and 3 variables. NOTE: PROCEDURE SORT used (Total process time): real time 0.01 seconds cpu time 0.03 seconds 1535 1536 proc transpose data=one out=two prefix = T; 1537 by subject; 1538 var time; 1539 run; NOTE: There were 91 observations read from the data set WORK.ONE. NOTE: The data set WORK.TWO has 7 observations and 16 variables. NOTE: PROCEDURE TRANSPOSE used (Total process time): real time 0.02 seconds cpu time 0.00 seconds 1540 1541 proc transpose data=one out=three prefix=C; 1542 by subject; 1543 var concentration; 1544 run; NOTE: There were 91 observations read from the data set WORK.ONE. NOTE: The data set WORK.THREE has 7 observations and 16 variables. NOTE: PROCEDURE TRANSPOSE used (Total process time): real time 0.03 seconds cpu time 0.03 seconds 1545 1546 data transposed; 1547 merge final final2; 1548 by subject; 1549 run; NOTE: There were 7 observations read from the data set WORK.FINAL. NOTE: There were 7 observations read from the data set WORK.FINAL2. NOTE: The data set WORK.TRANSPOSED has 7 observations and 27 variables. NOTE: DATA statement used (Total process time): real time 0.01 seconds cpu time 0.00 seconds 1550 1551 proc print data=transposed; 1552 title 'Transposed Data'; 1553 run; NOTE: There were 7 observations read from the data set WORK.TRANSPOSED. NOTE: PROCEDURE PRINT used (Total process time): real time 0.03 seconds cpu time 0.03 seconds 1554 1555 data transposed; 1556 array max[13] T1-T13; 1557 maximum=max(of Time[*]); NOTE: The array max has the same name as a SAS-supplied or user-defined function. Parentheses following this name are treated as array references and not function references. ERROR: Undeclared array referenced: Time. ERROR: The ARRAYNAME[*] specification requires an array. 1558 array max[13] C1-C13; --- 124 ERROR 124-185: The variable max has already been defined. 1559 maximum=max(of Concentration[*]); ERROR: Undeclared array referenced: Concentration. ERROR: The ARRAYNAME[*] specification requires an array. 1560 do n = i to 13; 1561 if max[i]=maximum then max=i; ERROR: Illegal reference to the array max. 1562 end; 1563 drop i; 1564 run ; NOTE: The SAS System stopped processing this step because of errors. WARNING: The data set WORK.TRANSPOSED may be incomplete. When this step was stopped there were 0 observations and 28 variables. WARNING: Data set WORK.TRANSPOSED was not replaced because this step was stopped. NOTE: DATA statement used (Total process time): real time 0.01 seconds cpu time 0.00 seconds 1565 1566 data Maximum; 1567 set transposed; 1568 run; NOTE: There were 7 observations read from the data set WORK.TRANSPOSED. NOTE: The data set WORK.MAXIMUM has 7 observations and 27 variables. NOTE: DATA statement used (Total process time): real time 0.01 seconds cpu time 0.01 seconds 1569 1570 proc print data=Maximum; 1571 title 'Maximum Values'; 1572 run; NOTE: There were 7 observations read from the data set WORK.MAXIMUM. NOTE: PROCEDURE PRINT used (Total process time): real time 0.02 seconds cpu time 0.01 seconds 1573 1574 proc means data=transposed; 1575 var T1-T13 C1-C13; 1576 run; NOTE: There were 7 observations read from the data set WORK.TRANSPOSED. NOTE: PROCEDURE MEANS used (Total process time): real time 0.16 seconds cpu time 0.07 seconds 1577 1578 data MMM; 1579 set transposed; 1580 run; NOTE: There were 7 observations read from the data set WORK.TRANSPOSED. NOTE: The data set WORK.MMM has 7 observations and 27 variables. NOTE: DATA statement used (Total process time): real time 0.01 seconds cpu time 0.01 seconds 1581 1582 proc print data=MMM; 1583 title 'Min Max Mean'; 1584 run; NOTE: There were 7 observations read from the data set WORK.MMM. NOTE: PROCEDURE PRINT used (Total process time): real time 0.02 seconds cpu time 0.01 seconds ... View more

I am currently taking an intro to SAS class and was instructed to complete the same thing this code does using Macro statements.    proc import out=datafile1 datafile= 'C:\Users\savanahb\Downloads\datafile1-2.xlsx' DBMS= EXCEL2000 REPLACE; getnames=yes; run; proc import out=datafile2 datafile= 'C:\Users\savanahb\Downloads\datafile2-2.xlsx' DBMS= EXCEL2000 REPLACE; getnames=yes; run; proc import out=datafile3 datafile= 'C:\Users\savanahb\Downloads\datafile3-2.xlsx' DBMS= EXCEL2000 REPLACE; getnames=yes; run; data datafile123; merge datafile1 datafile2 datafile3; by id; run; data datafile123; merge datafile1 (in=a) datafile2; by id; if a; run; data datafile123; merge datafile2 (in=a) datafile3; by ID; if a; run; data datafile123; merge datafile1 datafile3 (in=a); by ID; if a; run; data datafile123; merge datafile1 (in=a) datafile2 (in=b) datafile3 (in=c); by ID; if a and b and c; run; proc print data=datafile123; title 'Tabulation of data from merged dataset Datafile123'; run;   Unfortunately, I am stuck trying to figure out how to only show the variables that have the same ID in all three datasets. Here is what I have come up with:   %let u=datafile1; %let v=datafile1-3.xlsx; proc import out= &u datafile= "C:\Users\savanahb\Downloads\&v" dbms=xlsx replace; getnames=yes; run; %let w=datafile2; %let x=datafile3-3.xlsx; proc import out= &w datafile= "C:\Users\savanahb\Downloads\&x" dbms=xlsx replace; getnames=yes; run; %let y=datafile3; %let z=datafile3-3.xlsx; proc import out= &y datafile= "C:\Users\savanahb\Downloads\&z" dbms=xlsx replace; getnames=yes; run; %macro combine(u,w,y); data datafile123; merge &u &w &y; by id; data datafile123 match merge &u &y; by ID; data datafile123 merge &w(in=a) &y; by ID; if a; data datafile123 merge &u(in=a) &w(in=b) &y(in=c); by ID; if a and b and c; run; %mend combine; proc print data=datafile123; run;   Any suggestions? Thank you! ... View more

I had this assignment last week for an intro to SAS class that I am taking involving and we are working with arrays. I was supposed to present this data in a chart as described in the excel sheet I am attaching. I have managed to get everything to work except for labeling the agegroups (1-4) with different names (>30, 31-45, 46-60, 60+). It was suggested to continue using the else-if statements or to use proc format. Below is what I have, but it is just creating a new variable 'i'. Does anyone have any suggestions? data HW4_F17; length Profession $ 9 Housingtype $ 11 tenure $ 5 Response $ 3; array c condo1-condo4; array t town1 - town4; do profession = 'Physician','Professor','Engineer'; do tenure ='Rent','Own','Lease'; do response='Yes','No'; input condo1-condo4 Town1-Town4; do agegroup=1 to 4; Housingtype='Condominium'; Number = c[agegroup]; output; end; do agegroup=1 to 4; Housingtype='Townhomes'; Number = t[agegroup]; output; end; do agegroup=1 to 4; if i=1 then agegroup='>30'; else if i=2 then agegroup='31-45'; else if i=3 then agegroup='46-60'; else if i=4 then agegroup='60+'; end; end; end; end; drop condo: town:; datalines; 18 15 6 8 34 10 2 3 15 13 9 10 28 4 6 9 5 3 1 2 56 56 35 45 1 1 1 3 12 21 8 15 16 18 6 17 37 11 3 22 12 10 3 9 23 9 1 14 17 10 15 13 29 3 7 8 34 17 19 23 44 13 16 15 2 0 3 1 23 52 49 25 3 2 0 2 9 31 51 19 15 18 6 8 32 11 3 7 14 9 3 10 23 11 1 5 30 23 21 18 22 13 11 10 25 19 40 30 25 16 12 16 8 5 1 6 54 191 102 95 4 2 2 3 19 76 61 54 10 21 8 11 29 10 4 11 11 9 4 7 21 9 2 13 ; proc print data=HW4_F17; title 'Tabulation of data from HW4_F17 data set'; run; ... View more