yes, I see how the transposing is working with only one repeated variable. But I have a lot which makes it difficult for me to get right    In my case, I have for each patient : - multiple operations - mutilpe types of operations.    So I want outcome to be in this format:  Patient_1     Operation_1       Operation_type_info_1           Operation_2     Operation_type_info_2 Operation_3     Operation_type_info_3_part1 Operation_type_info_3_part2 Patient_2     Operation_1       Operation_type_info_1           Operation_2     Operation_type_info_2   So   data from id_2 -- g_date represents operations (dataset part_1).  And data from id_4 -- i_id (dataset part_2) The id_2 and id_4 is the same number as this represent each patient in different dataset (part_1 and part_2). i_id represents operation code beeing the only operator that connect data from operation and type of operation.  Sorted by the i_date I need eldeste operation to be first in the line and newest operation to be last in the line (already proc sorted i_date in my early step) I showed the expected output earlier with only 2 lines including all information for each patient gathered in one line.    The reason I should get it on one line is to do analysis like time between operation, characterics about percentage of operation type for first, second,... operation. Hope this give a better understanding of my data ?     ... View more

Yea, I guess I hoped to solve my question by divided in  1, merging step  2, making wide step.    My question about long to wide is - as I have multiple events (actually up to 20 for each i_id), how can I convert it to wide ? I was thinking proc transpose, but using it the simple way: proc transpose data=want out=answer; run; I get:  _NAME_ COL1 COL2 COL3 COL4 COL5 COL6 id_2 22222 12345 12345 12345 12345 22222 i_id 57321 62233 62233 78341 95732 97325 i_date 14064 15963 15963 19237 20346 15042 i_prev 0 99 99 99 99 0 i_time 20 30 30 30 30 18 id_3 22222 12344 12344 78341 95732 22222 id_i 57321 62233 62233 62233 62233 97325 g_procedure 8 4 4 4 4 1 g_date 14064 15963 15963 19237 20346 15042 id_4 22222 12345 12345 12345 12345 22222 i_id2 57321 62233 62233 78341 95732 97325 id_l 7777 5481 5482 8921 4841 3901 la 3 2 2 2 2 3 which is not exactly what I want... Mayby I need some by statement? As I have different variable names, seems I cant just use "var" statement 😕  ... View more

Would like to merge on I_ID. Whats called id_2 in data part_1 is equal to id_4 in part_2. However I dont need double of these. Thought I could delete on of the columns after successful merging.    The essential for me is to have all data corresponding to each id_2/4 on ONE row. Thats what I meant about the wide dataset. For 12345 (id_2) I have 3 observations in data part_1 and in data part_2 I have 4 observations for this particular id.  I planned to do this in two steps:  1) merge everything by i_id 2) change the long to wide dataset (i_id 62233) has one row in data part_1 and 2 rows in data part_2. I would like to have them on same row, the second observation eventuel with the suffix: _2 to differ between nr 1 and 2 observaion for that particular i_id.    Now, Im not sure how I get  62233 12345 15/09/2003 99 30 12344 62233 PM 4 15/09/2003 12345 62233 5481 2 ME sprint exp 12345 15/09/2003 99 30 12344 62233 PM 4 15/09/2003 12345 62233 5482 2 ME sprint exp on one line same line.  At last I should end up with two rows corresponding only to two record_ids with all their information on same line like this:   12345 62233 15.09.2003 99 30 12344 62233 PM 4 15-09-2003 12345 78341 01-09-2012 99 30 78341 62233 PM 4 01-09-2012 12345 95732 15-09-2015 99 30 95732 62233 PM 4 15-09-2015 12345 62233 5481 2 ME sprint exp 62233 12345 62233 5482 2 ME sprint exp 62233 12345 78341 8921 2 ME optis exp 78341 12345 95732 4841 2 ME optis active 95732 22222 57321 04-07-1998 0 20 22222 57321 PM 8 04-07-1998 22222 97325 08-03-2001 0 18 22222 97325 PM 1 08-03-2001 22222 57321 7777 3 GA Tip exp 57321 22222 97325 3901 3 GA Tip active 97325   @PaigeMiller were also nice to mention the semicolon in my input statement. I changed it and that worked     This merging step now worked:  data wide; merge part_1 part_2; by i_id; run;   Gave me this output:  Which data- og proc statement can I use to get the output collected? Hope you guys can help my      ... View more

Thanks the colon informat modifier helped to not continuing reading .  ... View more

Ah, so I fixed this by deleting the number after $ for status which species the length of characters.    The new being:  data part_1; input id_2 i_id i_date i_prev i_time id_3 id_i g_type$ g_procedure g_date; informat i_date g_date ddmmyy10. ; format i_date g_date ddmmyy10.; datalines; 12345 62233 15.09.2003 99 30 12344 62233 PM 4 15-09-2003 12345 78341 01-09-2012 99 30 78341 62233 PM 4 01-09-2012 12345 95732 15-09-2015 99 30 95732 62233 PM 4 15-09-2015 22222 57321 04-07-1998 0 20 22222 57321 PM 8 04-07-1998 22222 97325 08-03-2001 0 18 22222 97325 PM 1 08-03-2001 ; run; data part_2; input id_4 i_id2 id_l la ma_2$ mn_2$ status i_id; datalines; 12345 62233 5481 2 ME sprint exp 62233 12345 62233 5482 2 ME sprint exp 62233 12345 78341 8921 2 ME optis exp 78341 12345 95732 4841 2 ME optis active 95732 22222 57321 7777 3 GA Tip exp 57321 22222 97325 3901 3 GA Tip active 97325 ; run; Then tried merging again around i_id, expecting now only 2 lines as output . One for id 12345 and one for 22222.  It sadly gives me 7 lines 22222 57321 04/07/1998 0 20 22222 57321 PM 8 04/07/1998 22222 57321 7777 3 GA Tip . 12345 62233 15/09/2003 99 30 12344 62233 PM 4 15/09/2003 12345 62233 5481 2 ME sprint . 12345 62233 15/09/2003 99 30 12344 62233 PM 4 15/09/2003 12345 62233 5482 2 ME sprint . 12345 78341 01/09/2012 99 30 78341 62233 PM 4 01/09/2012 12345 78341 8921 2 ME optis . 12345 95732 15/09/2015 99 30 95732 62233 PM 4 15/09/2015 12345 95732 4841 2 ME optis . 22222 97325 08/03/2001 0 18 22222 97325 PM 1 08/03/2001 22222 97325 3901 3 GA Tip .   Is it because I shall make a step with new columns and rename them as goes for repeating events - like 1, 2, 3 and so on ? ... View more

I tried using merge datastep as i_id is linking the two datasteps. When I have used merge before it has only been for single observations. In data part_2 however one record_id has same i_id with 2 different observations (12345 62233).  I might think merge step is not suitable for this as my output is:  . 233 . . . . . . . 12345 62233 5481 2 ME sprint exp 62 . 233 . . . . . . . 12345 62233 5482 2 ME sprint exp 62 . 321 . . . . . . . 22222 57321 7777 3 GA Tip exp 57 . 341 . . . . . . . 12345 78341 8921 2 ME optis exp 78 22222 57321 04/07/1998 0 20 22222 57321 PM 8 04/07/1998 . . . . 12345 62233 15/09/2003 99 30 12344 62233 PM 4 15/09/2003 . . . . 12345 78341 01/09/2012 99 30 78341 62233 PM 4 01/09/2012 . . . . 12345 95732 15/09/2015 99 30 95732 62233 PM 4 15/09/2015 12345 95732 4841 2 ME optis active 22222 97325 08/03/2001 0 18 22222 97325 PM 1 08/03/2001 22222 97325 3901 3 GA Tip active   I expected 2 lines and this merging code gave the exact same numbers of lines.  When I go through my log, seems no errors and SAS is doing what its told to do. I think Im have misinterpreted what I can use the merge step for. Log:  The SAS System 1 ;*';*";*/;quit;run; 2 OPTIONS PAGENO=MIN; 3 %LET _CLIENTTASKLABEL='Program (2)'; 4 %LET _CLIENTPROCESSFLOWNAME='Process Flow'; 5 %LET _CLIENTPROJECTPATH=''; 6 %LET _CLIENTPROJECTPATHHOST=''; 7 %LET _CLIENTPROJECTNAME=''; 8 %LET _SASPROGRAMFILE=''; 9 %LET _SASPROGRAMFILEHOST=''; 10 11 ODS _ALL_ CLOSE; 12 OPTIONS DEV=PNG; 13 GOPTIONS XPIXELS=0 YPIXELS=0; 14 FILENAME EGSR TEMP; 15 ODS tagsets.sasreport13(ID=EGSR) FILE=EGSR 16 STYLE=HTMLBlue 17 STYLESHEET=(URL="file:///C:/Program%20Files/SASHomeGrid/SASEnterpriseGuide/7.1/Styles/HTMLBlue.css") 18 NOGTITLE 19 NOGFOOTNOTE 20 GPATH=&sasworklocation 21 ENCODING=UTF8 22 options(rolap="on") 23 ; NOTE: Writing TAGSETS.SASREPORT13(EGSR) Body file: EGSR 24 25 GOPTIONS ACCESSIBLE; 26 27 *Tried; 28 proc sort data=part_1; by i_id; run; NOTE: Input data set is already sorted, no sorting done. NOTE: PROCEDURE SORT used (Total process time): real time 0.00 seconds cpu time 0.00 seconds 29 proc sort data=part_2; by i_id; run; NOTE: Input data set is already sorted, no sorting done. NOTE: PROCEDURE SORT used (Total process time): real time 0.00 seconds cpu time 0.01 seconds 30 31 data wide; 32 merge part_1 part_2; 33 by i_id; 34 run; NOTE: There were 5 observations read from the data set WORK.PART_1. NOTE: There were 6 observations read from the data set WORK.PART_2. NOTE: The data set WORK.WIDE has 9 observations and 17 variables. NOTE: DATA statement used (Total process time): real time 0.00 seconds cpu time 0.00 seconds The SAS System   35 36 GOPTIONS NOACCESSIBLE; 37 %LET _CLIENTTASKLABEL=; 38 %LET _CLIENTPROCESSFLOWNAME=; 39 %LET _CLIENTPROJECTPATH=; 40 %LET _CLIENTPROJECTPATHHOST=; 41 %LET _CLIENTPROJECTNAME=; 42 %LET _SASPROGRAMFILE=; 43 %LET _SASPROGRAMFILEHOST=; 44 45 ;*';*";*/;quit;run; 46 ODS _ALL_ CLOSE; 47 48 49 QUIT; RUN; 50 ... View more