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 fashid
		
			fashid
		
		
		
		
		
		
		
		
	
			
		
		
			
					
		Hi Qlik Experts,
I have a scenario with which i need a little help . After several operations on the base data i have created this table which is in the excel file.
From this table i need to fetch those application no's whose computerized tread mill test is issued after the ECG test.
For ECG test i have min_date_1 column and for computerized tread mill test i have min_date_2 column
How do i go about doing this ?
Regards,
Nadeem
 
					
				
		
 jagan
		
			jagan
		
		
		
		
		
		
		
		
	
			
		
		
			
					
		Hi,
Try like this
TEMP:
LOAD APPLICATION_NO_1,
min_date_1,
min_date_2,
REQUIREMENT_DESC_1
FROM
TB12_20160916_204425.csv
(txt, codepage is 1252, embedded labels, delimiter is ',', msq);
Temp1:
LOAD
APPLICATION_NO_1,
Date1,
Date2
WHERE Flag = 1;
LOAD
If(Max(min_date_1) < Min(min_date_2), 1, 0) AS Flag,
APPLICATION_NO_1,
Date(Max(min_date_1)) AS Date1,
Date(Min(min_date_2)) AS Date2
RESIDENT TEMP
GROUP BY APPLICATION_NO_1;
 
					
				
		
 swuehl
		
			swuehl
		
		
		
		
		
		
		
		
	
			
		
		
			
					
		maybe like
| =Aggr(If(Max(min_date_1)<Min(min_date_2), APPLICATION_NO_1),APPLICATION_NO_1) | Date(Max(min_date_1)) | Date(Min(min_date_2)) | 
|---|---|---|
| 17-08-2016 | 26-07-2015 | |
| 1100004495090 | 24-07-2015 | 26-07-2015 | 
| 1100009430804 | 25-09-2015 | 29-09-2015 | 
| 1100009548237 | 29-09-2015 | 08-10-2015 | 
| 1100009587878 | 03-10-2015 | 07-10-2015 | 
| 1100009588049 | 03-10-2015 | 17-10-2015 | 
| 1100009592837 | 03-10-2015 | 20-10-2015 | 
| 1100010473607 | 14-10-2015 | 15-10-2015 | 
| 1100010900650 | 15-10-2015 | 12-12-2015 | 
| 1100011329581 | 18-10-2015 | 08-11-2015 | 
| 1100011410914 | 20-10-2015 | 30-11-2015 | 
| 1100012532770 | 24-10-2015 | 25-10-2015 | 
| 1100017549212 | 05-11-2015 | 06-11-2015 | 
| 1100017586485 | 13-11-2015 | 28-11-2015 | 
| 1100017913585 | 09-11-2015 | 09-01-2016 | 
| 1100019238647 | 16-11-2015 | 14-12-2015 | 
| 1100020697080 | 23-11-2015 | 30-11-2015 | 
| 1100021964284 | 20-11-2015 | 21-11-2015 | 
| 1100022723590 | 23-11-2015 | 26-12-2015 | 
| 1100022954580 | 23-11-2015 | 04-01-2016 | 
| 1100023469087 | 24-11-2015 | 25-11-2015 | 
| 1100023892582 | 25-11-2015 | 30-12-2015 | 
| 1100024721580 | 28-11-2015 | 15-12-2015 | 
| 1100024965080 | 26-11-2015 | 11-01-2016 | 
| 1100024967080 | 26-11-2015 | 27-11-2015 | 
| 1100026766080 | 29-11-2015 | 17-12-2015 | 
| 1100027950080 | 01-12-2015 | 02-12-2015 | 
| 1100027956096 | 01-12-2015 | 19-01-2016 | 
| 1100028008116 | 01-12-2015 | 17-12-2015 | 
| 1100028288615 | 03-12-2015 | 02-01-2016 | 
| 1100028288640 | 03-12-2015 | 13-12-2015 | 
| 1100028452581 | 08-12-2015 | 08-01-2016 | 
| 1100028616086 | 04-12-2015 | 20-01-2016 | 
| 1100029172085 | 07-12-2015 | 08-12-2015 | 
| 1100029277629 | 07-12-2015 | 30-01-2016 | 
| 1100029462890 | 08-12-2015 | 09-12-2015 | 
| 1100030084140 | 09-12-2015 | 26-12-2015 | 
| 1100030191080 | 09-12-2015 | 14-12-2015 | 
| 1100030446583 | 22-12-2015 | 09-01-2016 | 
| 1100030530174 | 10-12-2015 | 04-01-2016 | 
| 1100030618687 | 10-12-2015 | 12-12-2015 | 
| 1100030724080 | 17-12-2015 | 30-12-2015 | 
| 1100031542691 | 14-12-2015 | 28-12-2015 | 
| 1100032545053 | 26-12-2015 | 31-12-2015 | 
| 1100032608268 | 22-12-2015 | 24-12-2015 | 
| 1100033110609 | 21-12-2015 | 22-12-2015 | 
| 1100033111395 | 21-12-2015 | 05-01-2016 | 
| 1100033112317 | 21-12-2015 | 12-01-2016 | 
| 1100033123993 | 22-12-2015 | 24-12-2015 | 
| 1100033145716 | 22-12-2015 | 24-12-2015 | 
| 1100033402222 | 22-12-2015 | 24-12-2015 | 
| 1100033991745 | 23-12-2015 | 26-12-2015 | 
| 1100033995163 | 23-12-2015 | 01-01-2016 | 
| 1100034093380 | 23-12-2015 | 04-01-2016 | 
| 1100034178718 | 24-12-2015 | 28-12-2015 | 
| 1100034203216 | 05-01-2016 | 07-01-2016 | 
| 1100034445731 | 24-12-2015 | 29-12-2015 | 
| 1100035822743 | 28-12-2015 | 29-12-2015 | 
| 1100036228454 | 29-12-2015 | 07-01-2016 | 
| 1100036228795 | 29-12-2015 | 11-01-2016 | 
| 1100036232300 | 29-12-2015 | 31-12-2015 | 
| 1100036305317 | 30-12-2015 | 12-01-2016 | 
| 1100037039339 | 31-12-2015 | 05-01-2016 | 
| 1100038853849 | 05-01-2016 | 08-01-2016 | 
| 1100039172576 | 07-01-2016 | 29-01-2016 | 
| 1100039390243 | 07-01-2016 | 06-02-2016 | 
| 1100039404787 | 09-01-2016 | 11-01-2016 | 
| 1100039412580 | 10-01-2016 | 13-01-2016 | 
| 1100039414837 | 11-01-2016 | 19-02-2016 | 
| 1100039415612 | 11-01-2016 | 13-01-2016 | 
| 1100039415914 | 11-01-2016 | 12-01-2016 | 
| 1100039435459 | 21-01-2016 | 08-02-2016 | 
| 1100039435657 | 14-01-2016 | 15-01-2016 | 
| 1100039436356 | 14-01-2016 | 15-01-2016 | 
| 1100039436530 | 14-01-2016 | 15-01-2016 | 
| 1100039453492 | 19-01-2016 | 20-01-2016 | 
| 1100039456967 | 20-01-2016 | 04-02-2016 | 
| 1100039459852 | 20-01-2016 | 21-01-2016 | 
| 1100039465024 | 21-01-2016 | 22-01-2016 | 
| 1100039469060 | 22-01-2016 | 24-02-2016 | 
| 1100039478086 | 01-02-2016 | 19-02-2016 | 
| 1100039482152 | 25-01-2016 | 04-02-2016 | 
| 1100039495460 | 29-01-2016 | 25-02-2016 | 
| 1100039504817 | 30-01-2016 | 17-02-2016 | 
| 1100039509954 | 01-02-2016 | 05-02-2016 | 
| 1100039510336 | 01-02-2016 | 11-02-2016 | 
| 1100039511250 | 04-02-2016 | 24-03-2016 | 
| 1100039513402 | 04-02-2016 | 16-02-2016 | 
| 1100039521728 | 05-02-2016 | 22-02-2016 | 
| 1100039526646 | 05-02-2016 | 06-02-2016 | 
| 1100039536184 | 08-02-2016 | 09-02-2016 | 
| 1100039536698 | 08-02-2016 | 27-02-2016 | 
| 1100039544117 | 09-02-2016 | 10-02-2016 | 
| 1100039548225 | 16-02-2016 | 19-02-2016 | 
| 1100039550505 | 13-02-2016 | 25-02-2016 | 
| 1100039551838 | 11-02-2016 | 13-02-2016 | 
| 1100039556245 | 12-02-2016 | 13-02-2016 | 
| 1100039558278 | 13-02-2016 | 15-02-2016 | 
| 1100039573606 | 10-03-2016 | 19-03-2016 | 
| 1100039577959 | 20-02-2016 | 23-02-2016 | 
| 1100039583692 | 22-02-2016 | 23-02-2016 | 
| 1100039591095 | 24-02-2016 | 25-02-2016 | 
| 1100039593431 | 24-02-2016 | 28-02-2016 | 
| 1100039597552 | 25-02-2016 | 27-02-2016 | 
| 1100039605140 | 27-02-2016 | 28-02-2016 | 
| 1100039606009 | 27-02-2016 | 03-04-2016 | 
| 1100039608774 | 29-02-2016 | 03-03-2016 | 
| 1100039616643 | 01-03-2016 | 02-03-2016 | 
| 1100039626436 | 09-03-2016 | 21-03-2016 | 
| 1100039631756 | 07-03-2016 | 12-03-2016 | 
| 1100039632596 | 07-03-2016 | 09-03-2016 | 
| 1100039641023 | 12-03-2016 | 15-03-2016 | 
| 1100039659290 | 14-03-2016 | 29-03-2016 | 
| 1100039663651 | 15-03-2016 | 30-03-2016 | 
| 1100039676984 | 18-03-2016 | 05-04-2016 | 
| 1100039682664 | 19-03-2016 | 23-03-2016 | 
| 1100039699476 | 23-03-2016 | 16-04-2016 | 
| 1100039701817 | 24-03-2016 | 28-03-2016 | 
| 1100039703966 | 25-03-2016 | 28-03-2016 | 
| 1100039704284 | 25-03-2016 | 27-03-2016 | 
| 1100039712357 | 30-03-2016 | 18-05-2016 | 
| 1100039713806 | 29-03-2016 | 18-04-2016 | 
| 1100039724484 | 30-03-2016 | 22-04-2016 | 
| 1100039724599 | 30-03-2016 | 01-04-2016 | 
| 1100039731502 | 30-03-2016 | 03-04-2016 | 
| 1100039736235 | 04-04-2016 | 14-05-2016 | 
| 1100039738689 | 31-03-2016 | 04-04-2016 | 
| 1100039742972 | 31-03-2016 | 23-04-2016 | 
| 1100039743961 | 31-03-2016 | 04-04-2016 | 
| 1100039745072 | 31-03-2016 | 04-04-2016 | 
| 1100039776864 | 12-04-2016 | 13-04-2016 | 
| 1100039782127 | 14-04-2016 | 04-05-2016 | 
| 1100039835259 | 02-05-2016 | 03-05-2016 | 
| 1100039837418 | 02-05-2016 | 07-05-2016 | 
| 1100039847966 | 05-05-2016 | 22-07-2016 | 
| 1100039890433 | 18-05-2016 | 19-05-2016 | 
| 1100039891038 | 21-05-2016 | 14-06-2016 | 
| 1100039905039 | 23-05-2016 | 25-05-2016 | 
| 1100039921073 | 30-05-2016 | 31-05-2016 | 
| 1100039927723 | 15-06-2016 | 07-07-2016 | 
| 1100039970956 | 07-06-2016 | 27-06-2016 | 
| 1100039972249 | 07-06-2016 | 08-06-2016 | 
| 1100039976281 | 08-06-2016 | 16-06-2016 | 
| 1100039979679 | 09-06-2016 | 17-06-2016 | 
| 1100039988105 | 17-06-2016 | 26-06-2016 | 
| 1100040086728 | 01-07-2016 | 05-07-2016 | 
| 1100040103420 | 07-07-2016 | 13-07-2016 | 
| 1100040182489 | 18-07-2016 | 21-07-2016 | 
| 1100040189806 | 20-07-2016 | 21-07-2016 | 
| 1100040240093 | 30-07-2016 | 31-07-2016 | 
| 1100040279581 | 05-08-2016 | 06-08-2016 | 
| 1200040072207 | 29-06-2016 | 01-07-2016 | 
| 1200040093815 | 02-07-2016 | 04-07-2016 | 
| 1200040162681 | 14-07-2016 | 15-07-2016 | 
| 1200040181071 | 18-07-2016 | 28-07-2016 | 
| 1200040190439 | 20-07-2016 | 21-07-2016 | 
| 1200040209987 | 25-07-2016 | 28-07-2016 | 
| 1300320615397 | 03-03-2016 | 08-03-2016 | 
| 1300910823357 | 26-07-2016 | 05-08-2016 | 
| 1300940667889 | 11-04-2016 | 26-04-2016 | 
| 1302880814276 | 19-07-2016 | 20-07-2016 | 
| 1303620631485 | 14-03-2016 | 30-03-2016 | 
| 1304210601366 | 22-02-2016 | 25-03-2016 | 
| 1305400692213 | 25-04-2016 | 26-04-2016 | 
| 1306730591604 | 15-02-2016 | 05-03-2016 | 
| 1309970582820 | 09-02-2016 | 23-02-2016 | 
| 1313620637463 | 18-03-2016 | 21-03-2016 | 
| 1314090585568 | 11-02-2016 | 28-02-2016 | 
| 1314260856180 | 17-08-2016 | 30-08-2016 | 
| 1319000656153 | 31-03-2016 | 04-04-2016 | 
| 1319270784409 | 28-06-2016 | 09-07-2016 | 
| 1321830640242 | 20-03-2016 | 22-03-2016 | 
| 1322740647478 | 25-03-2016 | 06-04-2016 | 
| 1323650631656 | 14-03-2016 | 25-03-2016 | 
| 1323750754257 | 08-06-2016 | 09-06-2016 | 
| 1330350637525 | 18-03-2016 | 19-04-2016 | 
| 1332140611799 | 29-02-2016 | 06-04-2016 | 
| 1332770640527 | 20-03-2016 | 03-04-2016 | 
| 1334100625795 | 10-03-2016 | 16-04-2016 | 
| 1337530671976 | 22-04-2016 | 14-05-2016 | 
| 1338110631741 | 14-03-2016 | 29-03-2016 | 
| 1338120608541 | 27-02-2016 | 29-02-2016 | 
| 1338820533802 | 06-01-2016 | 24-02-2016 | 
| 1339980625563 | 10-03-2016 | 11-03-2016 | 
| 1340410692255 | 25-04-2016 | 26-04-2016 | 
| 1340440653502 | 30-03-2016 | 31-03-2016 | 
| 1341280748496 | 03-06-2016 | 04-06-2016 | 
| 1341800611530 | 29-02-2016 | 02-03-2016 | 
| 1341820704620 | 04-05-2016 | 18-05-2016 | 
| 1344330766738 | 16-06-2016 | 17-06-2016 | 
| 1347170587018 | 12-02-2016 | 22-02-2016 | 
| 1348200744202 | 31-05-2016 | 01-06-2016 | 
| 1348330654481 | 30-03-2016 | 21-04-2016 | 
| 1349050745368 | 01-06-2016 | 23-06-2016 | 
| 1350280755588 | 08-06-2016 | 09-06-2016 | 
| 1350560585538 | 11-02-2016 | 12-02-2016 | 
| 1350890651980 | 28-03-2016 | 18-04-2016 | 
| 1356010641464 | 22-03-2016 | 03-04-2016 | 
| 1360380784061 | 28-06-2016 | 29-06-2016 | 
| 1361150575313 | 04-02-2016 | 16-02-2016 | 
| 1364260762628 | 13-06-2016 | 09-07-2016 | 
| 1366140545397 | 14-01-2016 | 25-01-2016 | 
| 1367170654478 | 30-03-2016 | 01-04-2016 | 
| 1368760837484 | 05-08-2016 | 19-08-2016 | 
| 1369560788511 | 01-07-2016 | 19-07-2016 | 
| 1369620787345 | 30-06-2016 | 04-07-2016 | 
| 1370520633316 | 15-03-2016 | 18-03-2016 | 
| 1370740745526 | 01-06-2016 | 02-06-2016 | 
| 1371090651892 | 28-03-2016 | 04-04-2016 | 
| 1375410651802 | 28-03-2016 | 29-03-2016 | 
| 1377430607252 | 26-02-2016 | 28-02-2016 | 
| 1377810736842 | 26-05-2016 | 27-05-2016 | 
| 1379080634298 | 16-03-2016 | 25-04-2016 | 
| 1381930653322 | 29-03-2016 | 30-03-2016 | 
| 1382330654753 | 04-04-2016 | 22-04-2016 | 
| 1383700674831 | 13-04-2016 | 29-04-2016 | 
| 1384240844746 | 09-08-2016 | 23-08-2016 | 
| 1384820611533 | 29-02-2016 | 12-03-2016 | 
| 1385320636015 | 17-03-2016 | 18-03-2016 | 
| 1386610592769 | 16-02-2016 | 17-02-2016 | 
| 1386730661787 | 04-04-2016 | 12-04-2016 | 
| 1386800699447 | 09-05-2016 | 26-05-2016 | 
| 1386960767114 | 16-06-2016 | 17-06-2016 | 
| 1387540743816 | 31-05-2016 | 22-06-2016 | 
| 1388680748690 | 03-06-2016 | 04-06-2016 | 
| 1391980587098 | 13-02-2016 | 27-02-2016 | 
| 1392650580574 | 08-02-2016 | 09-02-2016 | 
| 1392710613035 | 01-03-2016 | 09-03-2016 | 
| 1393830629112 | 14-03-2016 | 30-03-2016 | 
| 1393850542519 | 12-01-2016 | 13-01-2016 | 
| 1394660634673 | 21-03-2016 | 02-04-2016 | 
| 1394780846096 | 10-08-2016 | 12-08-2016 | 
| 1396050716816 | 12-05-2016 | 13-05-2016 | 
| 1397140583645 | 10-02-2016 | 23-02-2016 | 
| 1397150815795 | 20-07-2016 | 22-07-2016 | 
| 1398310576900 | 05-02-2016 | 09-02-2016 | 
 fashid
		
			fashid
		
		
		
		
		
		
		
		
	
			
		
		
			
					
		Hi Stefan,
Thank you for your reply , i am sorry i did not mention that i wanted to do this in the scripting itself and create a table with all those application numbers.
Regards,
Nadeem
 
					
				
		
 jagan
		
			jagan
		
		
		
		
		
		
		
		
	
			
		
		
			
					
		Hi,
Try like this
TEMP:
LOAD APPLICATION_NO_1,
min_date_1,
min_date_2,
REQUIREMENT_DESC_1
FROM
TB12_20160916_204425.csv
(txt, codepage is 1252, embedded labels, delimiter is ',', msq);
Temp1:
LOAD
APPLICATION_NO_1,
Date1,
Date2
WHERE Flag = 1;
LOAD
If(Max(min_date_1) < Min(min_date_2), 1, 0) AS Flag,
APPLICATION_NO_1,
Date(Max(min_date_1)) AS Date1,
Date(Min(min_date_2)) AS Date2
RESIDENT TEMP
GROUP BY APPLICATION_NO_1;
 fashid
		
			fashid
		
		
		
		
		
		
		
		
	
			
		
		
			
					
		Sorry for the late response but both the solutions are excellent and worked fine for me .
wish i could mark both of them correct .
Thanks for all your help. really appreciate.
