I tried to run following attachment for biplot analysis. it didn't work. please help me.
Post the code or log as text in your reply, not as an attachment. Code should be posted into the window that appears when you click on the "little running man" icon. Log should be posted into the window that appears when you click on the </> icon.
data chili;
input Acc $6. StC NA SP PGH BH LC LS LP NFA FP CC AC SE MS CP CM AS FCI FCM FS FSPA NBF FSBE FBEA FC FSr SC NSF GU PH MLL MLW PHF CWF FL FW FWt FT FPP DFt DFl DFF TSWt FPK Yd;
datalines;
000210 2 5 7 7 3 3 3 5 1 5 1 3 7 0 0 2 0 3 8 1 2 0 1 1 3 2 1 3 2 42.7 5.8 1.6 28.9 18.1 5.8 1.1 49.3 0.1 23.1 74.0 33.0 44.0 3.9 500.0 23.0
000557 2 3 5 7 5 3 3 5 1 5 1 3 7 0 0 2 0 3 8 3 3 0 4 1 5 2 1 2 2 41.0 5.5 1.8 26.5 18.3 66.7 2.0 108.5 0.2 22.1 65.0 27.0 34.0 2.7 200.0 22.0
000692 2 5 3 7 7 3 3 3 1 5 1 3 7 0 0 2 0 2 8 1 2 0 1 1 3 2 1 2 2 39.2 5.9 1.9 28.6 16.4 8.6 1.0 124.0 0.1 50.7 33.0 39.0 65.0 3.1 413.0 51.0
001301 2 7 5 5 5 3 3 3 2 5 1 3 7 0 0 2 0 3 8 1 2 0 1 1 5 2 1 3 2 46.5 5.9 2.0 28.1 19.0 7.4 0.9 147.0 0.1 60.9 32.0 40.0 74.0 8.4 350.0 61.0
001785 2 7 5 5 7 3 2 5 1 5 1 5 7 0 0 3 0 3 9 3 3 0 1 1 5 2 1 3 2 50.8 5.0 1.6 27.9 22.5 9.0 2.4 247.5 0.1 47.0 29.0 35.0 6.0 3.6 100.0 47.0
008149 2 5 7 7 7 3 3 3 1 5 1 3 7 0 0 2 0 3 9 1 1 0 1 1 3 2 1 2 2 40.7 5.4 2.0 27.6 18.7 6.2 0.7 98.8 0.1 80.0 29.0 38.0 74.0 2.4 810.0 80.0
008220 2 5 3 7 3 3 2 3 1 5 1 3 7 0 0 2 0 3 9 1 2 0 1 1 5 2 1 3 2 46.0 6.2 2.3 26.0 17.5 10.0 1.1 115.5 0.1 32.6 33.0 40.0 66.0 4.2 280.0 33.0
008228 2 7 3 7 7 4 3 3 1 7 1 3 7 0 0 2 0 3 9 1 3 0 1 1 3 2 1 3 2 53.3 10.2 5.5 32.5 24.8 9.6 2.9 244.5 0.3 22.5 27.0 34.0 55.0 8.1 60.0 23.0
008230 2 5 7 5 7 3 3 7 1 5 1 3 7 0 0 2 0 3 9 1 2 0 1 1 3 2 1 3 2 37.3 5.6 1.8 23.3 18.5 6.9 0.9 114.8 0.1 48.2 29.0 38.0 74.0 4.3 419.0 48.0
001674 2 7 5 7 7 3 3 3 1 7 1 5 7 0 0 2 0 2 8 1 1 0 1 1 7 3 1 2 2 34.3 4.5 1.7 29.0 17.5 9.7 0.7 143.5 0.1 66.4 32.0 38.0 74.0 5.9 460.0 66.0
005867 2 3 5 7 5 3 3 5 1 5 1 3 7 0 0 2 0 3 8 1 2 0 1 1 7 2 1 3 2 37.2 4.1 1.8 28.8 18.0 7.7 0.8 86.8 0.1 39.5 32.0 39.0 74.0 4.0 455.0 40.0
016132 1 1 5 7 5 3 2 7 2 7 4 3 7 0 0 3 0 2 8 1 2 0 1 1 5 2 1 1 2 35.8 5.0 2.3 21.9 16.5 3.2 0.8 51.9 0.1 42.3 55.0 60.0 100.0 5.8 815.0 42.0
016395 2 5 5 7 5 4 3 5 1 3 1 5 7 0 0 2 1 2 6 3 5 0 3 1 5 2 1 3 3 33.9 5.2 2.2 26.7 20.6 8.3 3.7 211.5 0.3 16.3 29.0 34.0 55.0 3.8 55.0 16.0
016396 2 5 7 7 5 4 1 7 1 3 1 5 7 0 0 2 0 2 6 3 4 0 2 1 5 2 1 3 2 40.9 4.9 2.1 28.3 21.1 9.6 4.0 267.5 0.3 13.7 26.0 34.0 55.0 6.1 40.0 14.0
016400 2 7 5 7 7 3 2 3 1 5 1 3 7 0 0 2 0 3 8 3 3 0 1 1 5 2 1 2 2 33.1 5.5 2.0 25.3 19.0 4.8 0.9 75.0 0.1 36.9 29.0 35.0 74.0 6.3 528.0 37.0
016560 2 7 5 7 7 3 3 3 1 5 1 3 7 0 0 2 0 3 8 1 2 0 1 1 3 2 1 3 2 34.3 5.1 1.8 25.0 19.0 8.4 0.9 126.5 0.1 48.2 20.0 34.0 65.0 4.1 384.0 48.0
016586 1 1 5 7 5 3 2 3 1 7 4 4 7 0 0 2 0 2 8 4 3 0 1 1 7 3 1 2 3 40.4 5.0 2.1 22.0 22.3 4.3 2.0 135.2 0.2 49.8 32.0 48.0 74.0 3.9 368.0 50.0
016588 2 7 7 7 5 3 3 5 1 5 1 3 7 0 0 3 0 4 9 5 4 0 3 1 7 3 1 2 2 35.1 5.6 2.0 28.9 21.7 4.6 1.8 90.8 0.1 27.8 36.0 44.0 74.0 5.1 306.0 28.0
016596 2 5 5 7 5 3 1 7 2 5 4 5 7 0 0 3 1 3 8 3 2 0 1 1 5 3 1 2 2 40.4 5.9 2.1 23.3 20.8 4.6 1.2 67.5 0.1 33.5 49.0 60.0 82.0 3.0 490.0 34.0
016597 1 1 3 7 5 3 2 3 3 5 4 5 7 0 0 3 0 4 8 4 4 0 4 1 7 3 1 3 2 36.0 7.1 2.7 26.7 21.1 4.0 2.0 66.1 0.2 30.5 50.0 54.0 82.0 4.5 461.0 31.0
016599 1 1 5 7 5 3 2 7 2 7 4 3 7 0 0 2 0 2 9 3 3 0 1 1 5 2 1 1 2 54.5 5.4 2.4 35.6 20.8 2.5 0.8 30.1 0.1 55.5 48.0 60.0 114.0 4.2 1500.0 56.0
016600 2 5 7 5 7 3 3 7 1 5 1 3 7 0 0 2 0 3 8 1 2 1 4 1 5 3 1 3 2 41.3 6.5 2.3 24.3 19.8 14.2 1.7 179.0 0.1 76.0 16.0 34.0 55.0 6.7 420.0 76.0
016601 2 7 3 7 7 3 3 3 2 5 1 5 7 0 0 3 0 3 9 3 3 0 1 1 3 2 1 3 2 47.8 5.9 2.0 27.9 19.6 5.5 1.8 131.0 0.1 46.5 29.0 34.0 65.0 6.6 380.0 47.0
016603 3 3 5 7 5 7 2 3 2 7 4 5 7 0 0 2 1 3 8 4 2 0 1 1 7 3 1 1 2 53.2 8.8 4.4 32.5 27.2 5.6 1.7 96.2 0.1 40.3 41.0 51.0 74.0 4.1 418.0 40.0
016604 2 7 7 5 7 3 3 5 1 5 1 3 7 0 0 2 0 3 9 1 2 0 1 1 3 2 1 3 2 56.5 5.9 2.0 367.0 27.8 7.6 1.6 161.9 0.1 36.5 34.0 44.0 65.0 2.0 225.0 36.0
016609 2 3 5 5 7 3 3 3 2 3 1 5 7 0 0 3 0 3 8 1 1 1 3 1 3 2 1 3 2 65.5 7.4 2.8 38.1 21.6 9.0 0.8 153.0 0.1 48.6 34.0 38.0 65.0 4.7 317.0 49.0
0000c1 2 7 7 7 5 7 3 7 2 7 5 5 7 0 1 3 1 7 9 1 2 1 1 1 3 2 1 3 2 65.4 8.9 3.1 44.7 27.7 9.1 1.5 147.5 0.1 39.1 36.0 44.0 72.0 4.2 265.0 39.0
0000c2 2 7 5 7 5 3 2 3 1 7 4 3 7 0 0 2 0 3 9 4 4 0 4 1 7 3 1 2 2 38.0 6.4 2.1 30.3 27.6 4.4 2.2 94.2 0.1 35.2 55.0 59.0 79.0 3.2 373.0 35.0
0000c3 1 1 5 5 5 3 2 7 2 7 2 3 7 0 0 2 0 3 8 1 2 0 1 1 5 2 1 1 2 40.9 5.7 2.3 25.9 21.1 3.4 0.8 43.0 0.1 46.0 42.0 59.0 114.0 5.9 820.0 46.0
0000c4 2 7 7 7 3 7 1 7 1 5 8 5 7 0 0 2 1 6 9 5 3 0 4 1 3 2 1 3 2 70.7 7.5 2.8 35.7 19.2 6.4 2.1 85.0 0.2 19.3 39.0 45.0 72.0 2.9 227.0 19.0
0000c5 2 7 5 5 7 4 1 5 2 5 2 3 7 0 0 2 0 4 8 1 2 0 1 1 3 2 1 1 2 35.1 5.7 2.0 26.6 24.6 4.8 1.4 45.1 0.2 24.8 38.0 51.0 79.0 2.9 550.0 25.0
0000c6 2 7 7 7 5 7 3 7 1 7 5 5 7 0 0 3 1 6 9 1 2 0 1 1 3 2 1 3 2 60.4 7.2 2.6 32.3 18.2 7.6 1.3 169.0 0.1 70.3 34.0 39.0 72.0 2.9 415.0 70.0
0000c7 2 5 3 5 7 3 1 3 3 7 4 3 7 0 0 2 0 3 8 5 4 0 3 1 7 2 1 2 2 37.1 7.2 3.1 24.3 24.0 3.7 2.4 77.0 0.2 28.8 39.0 51.0 79.0 6.6 374.0 29.0
0000c8 2 1 3 7 3 3 1 3 1 5 4 5 7 0 0 2 0 3 8 4 3 0 3 1 7 3 1 2 2 38.9 10.0 4.0 26.3 25.4 3.9 1.7 87.3 0.1 39.1 36.0 60.0 114.0 5.2 400.0 39.0
0013c7 2 7 5 7 7 3 3 5 1 7 1 3 7 0 0 2 0 3 8 1 2 0 1 1 3 2 1 3 2 50.4 6.3 2.1 33.2 18.8 8.3 1.4 152.0 0.1 40.8 17.0 27.0 55.0 8.0 249.0 41.0
0017c8 2 7 7 7 5 3 2 7 1 5 1 5 7 0 0 2 0 2 6 1 3 0 1 1 5 3 1 3 2 42.8 6.2 2.0 28.6 17.6 10.8 2.0 178.0 0.2 23.2 32.0 38.0 55.0 2.3 100.0 23.0
0058c0 2 7 5 7 7 3 2 3 2 5 1 5 7 0 0 1 0 3 8 5 2 0 4 1 5 2 1 2 2 44.7 10.3 3.7 33.7 21.7 9.0 1.4 166.7 0.2 33.0 36.0 40.0 66.0 4.2 198.0 33.0
0058c6 2 7 5 5 5 3 1 7 1 5 9 2 3 0 0 3 0 3 6 4 3 0 4 1 7 3 1 3 2 53.0 6.2 2.8 32.0 23.7 5.8 2.8 78.3 0.2 8.0 36.0 40.0 66.0 5.0 102.0 8.0
;
How I use Friendly's biplot macro for above data set?
Friendly's %BIPLOT macro
Show us the code you have tried so far. If there are errors in the log, show us the log too. Do not attach files. Show us code and log as text, as explained above.
Please run the code below and view the log. You'll see an error regarding a missing value and warnings of division by zero.
data reaction;
input Task $6. Topic1 Topic2 Topic3 Topic4;
datalines;
Easy 2.43 3.12 3.68 4.04
Medium 3.41 3.91 4.07 5.10
Hard 4.21 4.65 5.87 5.69
;
run;
%biplot(var=topic1-topic4, id=task);
data reaction2;
input Task $6. Topic1 Topic2 Topic3 Topic4;
datalines;
Easy 0 3.12 3.68 0
Medium 3.41 3.91 4.07 0
Hard 4.21 4.65 5.87 0
;
run;
%biplot(var=topic1-topic4, id=task);
I suppose that is similar to what you get with the chili dataset. The chili dataset has a single column with only '0's and several columns with '0's as values for the variable.
data chili;
input Acc $6. StC NA SP PGH BH LC LS LP NFA FP CC AC SE MS CP CM AS FCI FCM FS FSPA NBF FSBE FBEA FC FSr SC NSF GU PH MLL MLW PHF CWF FL FW FWt FT FPP DFt DFl DFF TSWt FPK Yd;
datalines;
000210 2 5 7 7 3 3 3 5 1 5 1 3 7 0 0 2 0 3 8 1 2 0 1 1 3 2 1 3 2 42.7 5.8 1.6 28.9 18.1 5.8 1.1 49.3 0.1 23.1 74.0 33.0 44.0 3.9 500.0 23.0
000557 2 3 5 7 5 3 3 5 1 5 1 3 7 0 0 2 0 3 8 3 3 0 4 1 5 2 1 2 2 41.0 5.5 1.8 26.5 18.3 66.7 2.0 108.5 0.2 22.1 65.0 27.0 34.0 2.7 200.0 22.0
000692 2 5 3 7 7 3 3 3 1 5 1 3 7 0 0 2 0 2 8 1 2 0 1 1 3 2 1 2 2 39.2 5.9 1.9 28.6 16.4 8.6 1.0 124.0 0.1 50.7 33.0 39.0 65.0 3.1 413.0 51.0
001301 2 7 5 5 5 3 3 3 2 5 1 3 7 0 0 2 0 3 8 1 2 0 1 1 5 2 1 3 2 46.5 5.9 2.0 28.1 19.0 7.4 0.9 147.0 0.1 60.9 32.0 40.0 74.0 8.4 350.0 61.0
001785 2 7 5 5 7 3 2 5 1 5 1 5 7 0 0 3 0 3 9 3 3 0 1 1 5 2 1 3 2 50.8 5.0 1.6 27.9 22.5 9.0 2.4 247.5 0.1 47.0 29.0 35.0 6.0 3.6 100.0 47.0
008149 2 5 7 7 7 3 3 3 1 5 1 3 7 0 0 2 0 3 9 1 1 0 1 1 3 2 1 2 2 40.7 5.4 2.0 27.6 18.7 6.2 0.7 98.8 0.1 80.0 29.0 38.0 74.0 2.4 810.0 80.0
008220 2 5 3 7 3 3 2 3 1 5 1 3 7 0 0 2 0 3 9 1 2 0 1 1 5 2 1 3 2 46.0 6.2 2.3 26.0 17.5 10.0 1.1 115.5 0.1 32.6 33.0 40.0 66.0 4.2 280.0 33.0
008228 2 7 3 7 7 4 3 3 1 7 1 3 7 0 0 2 0 3 9 1 3 0 1 1 3 2 1 3 2 53.3 10.2 5.5 32.5 24.8 9.6 2.9 244.5 0.3 22.5 27.0 34.0 55.0 8.1 60.0 23.0
008230 2 5 7 5 7 3 3 7 1 5 1 3 7 0 0 2 0 3 9 1 2 0 1 1 3 2 1 3 2 37.3 5.6 1.8 23.3 18.5 6.9 0.9 114.8 0.1 48.2 29.0 38.0 74.0 4.3 419.0 48.0
001674 2 7 5 7 7 3 3 3 1 7 1 5 7 0 0 2 0 2 8 1 1 0 1 1 7 3 1 2 2 34.3 4.5 1.7 29.0 17.5 9.7 0.7 143.5 0.1 66.4 32.0 38.0 74.0 5.9 460.0 66.0
005867 2 3 5 7 5 3 3 5 1 5 1 3 7 0 0 2 0 3 8 1 2 0 1 1 7 2 1 3 2 37.2 4.1 1.8 28.8 18.0 7.7 0.8 86.8 0.1 39.5 32.0 39.0 74.0 4.0 455.0 40.0
016132 1 1 5 7 5 3 2 7 2 7 4 3 7 0 0 3 0 2 8 1 2 0 1 1 5 2 1 1 2 35.8 5.0 2.3 21.9 16.5 3.2 0.8 51.9 0.1 42.3 55.0 60.0 100.0 5.8 815.0 42.0
016395 2 5 5 7 5 4 3 5 1 3 1 5 7 0 0 2 1 2 6 3 5 0 3 1 5 2 1 3 3 33.9 5.2 2.2 26.7 20.6 8.3 3.7 211.5 0.3 16.3 29.0 34.0 55.0 3.8 55.0 16.0
016396 2 5 7 7 5 4 1 7 1 3 1 5 7 0 0 2 0 2 6 3 4 0 2 1 5 2 1 3 2 40.9 4.9 2.1 28.3 21.1 9.6 4.0 267.5 0.3 13.7 26.0 34.0 55.0 6.1 40.0 14.0
016400 2 7 5 7 7 3 2 3 1 5 1 3 7 0 0 2 0 3 8 3 3 0 1 1 5 2 1 2 2 33.1 5.5 2.0 25.3 19.0 4.8 0.9 75.0 0.1 36.9 29.0 35.0 74.0 6.3 528.0 37.0
016560 2 7 5 7 7 3 3 3 1 5 1 3 7 0 0 2 0 3 8 1 2 0 1 1 3 2 1 3 2 34.3 5.1 1.8 25.0 19.0 8.4 0.9 126.5 0.1 48.2 20.0 34.0 65.0 4.1 384.0 48.0
016586 1 1 5 7 5 3 2 3 1 7 4 4 7 0 0 2 0 2 8 4 3 0 1 1 7 3 1 2 3 40.4 5.0 2.1 22.0 22.3 4.3 2.0 135.2 0.2 49.8 32.0 48.0 74.0 3.9 368.0 50.0
016588 2 7 7 7 5 3 3 5 1 5 1 3 7 0 0 3 0 4 9 5 4 0 3 1 7 3 1 2 2 35.1 5.6 2.0 28.9 21.7 4.6 1.8 90.8 0.1 27.8 36.0 44.0 74.0 5.1 306.0 28.0
016596 2 5 5 7 5 3 1 7 2 5 4 5 7 0 0 3 1 3 8 3 2 0 1 1 5 3 1 2 2 40.4 5.9 2.1 23.3 20.8 4.6 1.2 67.5 0.1 33.5 49.0 60.0 82.0 3.0 490.0 34.0
016597 1 1 3 7 5 3 2 3 3 5 4 5 7 0 0 3 0 4 8 4 4 0 4 1 7 3 1 3 2 36.0 7.1 2.7 26.7 21.1 4.0 2.0 66.1 0.2 30.5 50.0 54.0 82.0 4.5 461.0 31.0
016599 1 1 5 7 5 3 2 7 2 7 4 3 7 0 0 2 0 2 9 3 3 0 1 1 5 2 1 1 2 54.5 5.4 2.4 35.6 20.8 2.5 0.8 30.1 0.1 55.5 48.0 60.0 114.0 4.2 1500.0 56.0
016600 2 5 7 5 7 3 3 7 1 5 1 3 7 0 0 2 0 3 8 1 2 1 4 1 5 3 1 3 2 41.3 6.5 2.3 24.3 19.8 14.2 1.7 179.0 0.1 76.0 16.0 34.0 55.0 6.7 420.0 76.0
016601 2 7 3 7 7 3 3 3 2 5 1 5 7 0 0 3 0 3 9 3 3 0 1 1 3 2 1 3 2 47.8 5.9 2.0 27.9 19.6 5.5 1.8 131.0 0.1 46.5 29.0 34.0 65.0 6.6 380.0 47.0
016603 3 3 5 7 5 7 2 3 2 7 4 5 7 0 0 2 1 3 8 4 2 0 1 1 7 3 1 1 2 53.2 8.8 4.4 32.5 27.2 5.6 1.7 96.2 0.1 40.3 41.0 51.0 74.0 4.1 418.0 40.0
016604 2 7 7 5 7 3 3 5 1 5 1 3 7 0 0 2 0 3 9 1 2 0 1 1 3 2 1 3 2 56.5 5.9 2.0 367.0 27.8 7.6 1.6 161.9 0.1 36.5 34.0 44.0 65.0 2.0 225.0 36.0
016609 2 3 5 5 7 3 3 3 2 3 1 5 7 0 0 3 0 3 8 1 1 1 3 1 3 2 1 3 2 65.5 7.4 2.8 38.1 21.6 9.0 0.8 153.0 0.1 48.6 34.0 38.0 65.0 4.7 317.0 49.0
0000c1 2 7 7 7 5 7 3 7 2 7 5 5 7 0 1 3 1 7 9 1 2 1 1 1 3 2 1 3 2 65.4 8.9 3.1 44.7 27.7 9.1 1.5 147.5 0.1 39.1 36.0 44.0 72.0 4.2 265.0 39.0
0000c2 2 7 5 7 5 3 2 3 1 7 4 3 7 0 0 2 0 3 9 4 4 0 4 1 7 3 1 2 2 38.0 6.4 2.1 30.3 27.6 4.4 2.2 94.2 0.1 35.2 55.0 59.0 79.0 3.2 373.0 35.0
0000c3 1 1 5 5 5 3 2 7 2 7 2 3 7 0 0 2 0 3 8 1 2 0 1 1 5 2 1 1 2 40.9 5.7 2.3 25.9 21.1 3.4 0.8 43.0 0.1 46.0 42.0 59.0 114.0 5.9 820.0 46.0
0000c4 2 7 7 7 3 7 1 7 1 5 8 5 7 0 0 2 1 6 9 5 3 0 4 1 3 2 1 3 2 70.7 7.5 2.8 35.7 19.2 6.4 2.1 85.0 0.2 19.3 39.0 45.0 72.0 2.9 227.0 19.0
0000c5 2 7 5 5 7 4 1 5 2 5 2 3 7 0 0 2 0 4 8 1 2 0 1 1 3 2 1 1 2 35.1 5.7 2.0 26.6 24.6 4.8 1.4 45.1 0.2 24.8 38.0 51.0 79.0 2.9 550.0 25.0
0000c6 2 7 7 7 5 7 3 7 1 7 5 5 7 0 0 3 1 6 9 1 2 0 1 1 3 2 1 3 2 60.4 7.2 2.6 32.3 18.2 7.6 1.3 169.0 0.1 70.3 34.0 39.0 72.0 2.9 415.0 70.0
0000c7 2 5 3 5 7 3 1 3 3 7 4 3 7 0 0 2 0 3 8 5 4 0 3 1 7 2 1 2 2 37.1 7.2 3.1 24.3 24.0 3.7 2.4 77.0 0.2 28.8 39.0 51.0 79.0 6.6 374.0 29.0
0000c8 2 1 3 7 3 3 1 3 1 5 4 5 7 0 0 2 0 3 8 4 3 0 3 1 7 3 1 2 2 38.9 10.0 4.0 26.3 25.4 3.9 1.7 87.3 0.1 39.1 36.0 60.0 114.0 5.2 400.0 39.0
0013c7 2 7 5 7 7 3 3 5 1 7 1 3 7 0 0 2 0 3 8 1 2 0 1 1 3 2 1 3 2 50.4 6.3 2.1 33.2 18.8 8.3 1.4 152.0 0.1 40.8 17.0 27.0 55.0 8.0 249.0 41.0
0017c8 2 7 7 7 5 3 2 7 1 5 1 5 7 0 0 2 0 2 6 1 3 0 1 1 5 3 1 3 2 42.8 6.2 2.0 28.6 17.6 10.8 2.0 178.0 0.2 23.2 32.0 38.0 55.0 2.3 100.0 23.0
0058c0 2 7 5 7 7 3 2 3 2 5 1 5 7 0 0 1 0 3 8 5 2 0 4 1 5 2 1 2 2 44.7 10.3 3.7 33.7 21.7 9.0 1.4 166.7 0.2 33.0 36.0 40.0 66.0 4.2 198.0 33.0
0058c6 2 7 5 5 5 3 1 7 1 5 9 2 3 0 0 3 0 3 6 4 3 0 4 1 7 3 1 3 2 53.0 6.2 2.8 32.0 23.7 5.8 2.8 78.3 0.2 8.0 36.0 40.0 66.0 5.0 102.0 8.0
;
/* A. Use %BIPLOT macro, which uses SAS/IML to compute the biplot coordinates.
Use the OUT= option to get the coordinates for the markers and vectors.
B. Transpose the data from long to wide form.
C. Use PROC SGPLOT to create the biplot
*/
%let FACTYPE = SYM; /* options are GH, COV, JK, SYM */
title "Biplot: &FACTYPE, STD";
%biplot(data=chili,
var=StC NA SP PGH BH LC LS LP NFA FP CC AC SE MS CP CM AS FCI FCM FS FSPA NBF FSBE FBEA FC FSr SC NSF GU PH MLL MLW PHF CWF FL FW FWt FT FPP DFt DFl DFF TSWt FPK Yd,
id=Acc,
factype=&FACTYPE, /* GH, COV, JK, SYM */
std=std, /* NONE, MEAN, STD */
scale=1, /* if you do not specify SCALE=1, vectors are auto-scaled */
out=biplotFriendly,/* write SAS data set with results */
symbols=circle dot, inc=1);
/* transpose from long to wide */
data Biplot;
set biplotFriendly(where=(_TYPE_='OBS') rename=(dim1=Prin1 dim2=Prin2 _Name_=_ID_))
biplotFriendly(where=(_TYPE_='VAR') rename=(dim1=vx dim2=vy _Name_=_Variable_));
run;
proc sgplot data=Biplot aspect=1 noautolegend;
refline 0 / axis=x; refline 0 / axis=y;
scatter x=Prin1 y=Prin2 / datalabel=_ID_;
vector x=vx y=vy / datalabel=_Variable_
lineattrs=GraphData2 datalabelattrs=GraphData2;
xaxis grid offsetmin=0.1 offsetmax=0.2;
yaxis grid;
run;
This is what I tried.
data chili;
input Acc $6. StC NA SP PGH BH LC LS LP NFA FP CC AC SE MS CP CM AS FCI FCM FS FSPA NBF FSBE FBEA FC FSr SC NSF GU PH MLL MLW PHF CWF FL FW FWt FT FPP DFt DFl DFF TSWt FPK Yd;
datalines;
000210 2 5 7 7 3 3 3 5 1 5 1 3 7 0 0 2 0 3 8 1 2 0 1 1 3 2 1 3 2 42.7 5.8 1.6 28.9 18.1 5.8 1.1 49.3 0.1 23.1 74.0 33.0 44.0 3.9 500.0 23.0
000557 2 3 5 7 5 3 3 5 1 5 1 3 7 0 0 2 0 3 8 3 3 0 4 1 5 2 1 2 2 41.0 5.5 1.8 26.5 18.3 66.7 2.0 108.5 0.2 22.1 65.0 27.0 34.0 2.7 200.0 22.0
000692 2 5 3 7 7 3 3 3 1 5 1 3 7 0 0 2 0 2 8 1 2 0 1 1 3 2 1 2 2 39.2 5.9 1.9 28.6 16.4 8.6 1.0 124.0 0.1 50.7 33.0 39.0 65.0 3.1 413.0 51.0
001301 2 7 5 5 5 3 3 3 2 5 1 3 7 0 0 2 0 3 8 1 2 0 1 1 5 2 1 3 2 46.5 5.9 2.0 28.1 19.0 7.4 0.9 147.0 0.1 60.9 32.0 40.0 74.0 8.4 350.0 61.0
001785 2 7 5 5 7 3 2 5 1 5 1 5 7 0 0 3 0 3 9 3 3 0 1 1 5 2 1 3 2 50.8 5.0 1.6 27.9 22.5 9.0 2.4 247.5 0.1 47.0 29.0 35.0 6.0 3.6 100.0 47.0
008149 2 5 7 7 7 3 3 3 1 5 1 3 7 0 0 2 0 3 9 1 1 0 1 1 3 2 1 2 2 40.7 5.4 2.0 27.6 18.7 6.2 0.7 98.8 0.1 80.0 29.0 38.0 74.0 2.4 810.0 80.0
008220 2 5 3 7 3 3 2 3 1 5 1 3 7 0 0 2 0 3 9 1 2 0 1 1 5 2 1 3 2 46.0 6.2 2.3 26.0 17.5 10.0 1.1 115.5 0.1 32.6 33.0 40.0 66.0 4.2 280.0 33.0
008228 2 7 3 7 7 4 3 3 1 7 1 3 7 0 0 2 0 3 9 1 3 0 1 1 3 2 1 3 2 53.3 10.2 5.5 32.5 24.8 9.6 2.9 244.5 0.3 22.5 27.0 34.0 55.0 8.1 60.0 23.0
008230 2 5 7 5 7 3 3 7 1 5 1 3 7 0 0 2 0 3 9 1 2 0 1 1 3 2 1 3 2 37.3 5.6 1.8 23.3 18.5 6.9 0.9 114.8 0.1 48.2 29.0 38.0 74.0 4.3 419.0 48.0
001674 2 7 5 7 7 3 3 3 1 7 1 5 7 0 0 2 0 2 8 1 1 0 1 1 7 3 1 2 2 34.3 4.5 1.7 29.0 17.5 9.7 0.7 143.5 0.1 66.4 32.0 38.0 74.0 5.9 460.0 66.0
005867 2 3 5 7 5 3 3 5 1 5 1 3 7 0 0 2 0 3 8 1 2 0 1 1 7 2 1 3 2 37.2 4.1 1.8 28.8 18.0 7.7 0.8 86.8 0.1 39.5 32.0 39.0 74.0 4.0 455.0 40.0
016132 1 1 5 7 5 3 2 7 2 7 4 3 7 0 0 3 0 2 8 1 2 0 1 1 5 2 1 1 2 35.8 5.0 2.3 21.9 16.5 3.2 0.8 51.9 0.1 42.3 55.0 60.0 100.0 5.8 815.0 42.0
016395 2 5 5 7 5 4 3 5 1 3 1 5 7 0 0 2 1 2 6 3 5 0 3 1 5 2 1 3 3 33.9 5.2 2.2 26.7 20.6 8.3 3.7 211.5 0.3 16.3 29.0 34.0 55.0 3.8 55.0 16.0
016396 2 5 7 7 5 4 1 7 1 3 1 5 7 0 0 2 0 2 6 3 4 0 2 1 5 2 1 3 2 40.9 4.9 2.1 28.3 21.1 9.6 4.0 267.5 0.3 13.7 26.0 34.0 55.0 6.1 40.0 14.0
016400 2 7 5 7 7 3 2 3 1 5 1 3 7 0 0 2 0 3 8 3 3 0 1 1 5 2 1 2 2 33.1 5.5 2.0 25.3 19.0 4.8 0.9 75.0 0.1 36.9 29.0 35.0 74.0 6.3 528.0 37.0
016560 2 7 5 7 7 3 3 3 1 5 1 3 7 0 0 2 0 3 8 1 2 0 1 1 3 2 1 3 2 34.3 5.1 1.8 25.0 19.0 8.4 0.9 126.5 0.1 48.2 20.0 34.0 65.0 4.1 384.0 48.0
016586 1 1 5 7 5 3 2 3 1 7 4 4 7 0 0 2 0 2 8 4 3 0 1 1 7 3 1 2 3 40.4 5.0 2.1 22.0 22.3 4.3 2.0 135.2 0.2 49.8 32.0 48.0 74.0 3.9 368.0 50.0
016588 2 7 7 7 5 3 3 5 1 5 1 3 7 0 0 3 0 4 9 5 4 0 3 1 7 3 1 2 2 35.1 5.6 2.0 28.9 21.7 4.6 1.8 90.8 0.1 27.8 36.0 44.0 74.0 5.1 306.0 28.0
016596 2 5 5 7 5 3 1 7 2 5 4 5 7 0 0 3 1 3 8 3 2 0 1 1 5 3 1 2 2 40.4 5.9 2.1 23.3 20.8 4.6 1.2 67.5 0.1 33.5 49.0 60.0 82.0 3.0 490.0 34.0
016597 1 1 3 7 5 3 2 3 3 5 4 5 7 0 0 3 0 4 8 4 4 0 4 1 7 3 1 3 2 36.0 7.1 2.7 26.7 21.1 4.0 2.0 66.1 0.2 30.5 50.0 54.0 82.0 4.5 461.0 31.0
016599 1 1 5 7 5 3 2 7 2 7 4 3 7 0 0 2 0 2 9 3 3 0 1 1 5 2 1 1 2 54.5 5.4 2.4 35.6 20.8 2.5 0.8 30.1 0.1 55.5 48.0 60.0 114.0 4.2 1500.0 56.0
016600 2 5 7 5 7 3 3 7 1 5 1 3 7 0 0 2 0 3 8 1 2 1 4 1 5 3 1 3 2 41.3 6.5 2.3 24.3 19.8 14.2 1.7 179.0 0.1 76.0 16.0 34.0 55.0 6.7 420.0 76.0
016601 2 7 3 7 7 3 3 3 2 5 1 5 7 0 0 3 0 3 9 3 3 0 1 1 3 2 1 3 2 47.8 5.9 2.0 27.9 19.6 5.5 1.8 131.0 0.1 46.5 29.0 34.0 65.0 6.6 380.0 47.0
016603 3 3 5 7 5 7 2 3 2 7 4 5 7 0 0 2 1 3 8 4 2 0 1 1 7 3 1 1 2 53.2 8.8 4.4 32.5 27.2 5.6 1.7 96.2 0.1 40.3 41.0 51.0 74.0 4.1 418.0 40.0
016604 2 7 7 5 7 3 3 5 1 5 1 3 7 0 0 2 0 3 9 1 2 0 1 1 3 2 1 3 2 56.5 5.9 2.0 367.0 27.8 7.6 1.6 161.9 0.1 36.5 34.0 44.0 65.0 2.0 225.0 36.0
016609 2 3 5 5 7 3 3 3 2 3 1 5 7 0 0 3 0 3 8 1 1 1 3 1 3 2 1 3 2 65.5 7.4 2.8 38.1 21.6 9.0 0.8 153.0 0.1 48.6 34.0 38.0 65.0 4.7 317.0 49.0
0000c1 2 7 7 7 5 7 3 7 2 7 5 5 7 0 1 3 1 7 9 1 2 1 1 1 3 2 1 3 2 65.4 8.9 3.1 44.7 27.7 9.1 1.5 147.5 0.1 39.1 36.0 44.0 72.0 4.2 265.0 39.0
0000c2 2 7 5 7 5 3 2 3 1 7 4 3 7 0 0 2 0 3 9 4 4 0 4 1 7 3 1 2 2 38.0 6.4 2.1 30.3 27.6 4.4 2.2 94.2 0.1 35.2 55.0 59.0 79.0 3.2 373.0 35.0
0000c3 1 1 5 5 5 3 2 7 2 7 2 3 7 0 0 2 0 3 8 1 2 0 1 1 5 2 1 1 2 40.9 5.7 2.3 25.9 21.1 3.4 0.8 43.0 0.1 46.0 42.0 59.0 114.0 5.9 820.0 46.0
0000c4 2 7 7 7 3 7 1 7 1 5 8 5 7 0 0 2 1 6 9 5 3 0 4 1 3 2 1 3 2 70.7 7.5 2.8 35.7 19.2 6.4 2.1 85.0 0.2 19.3 39.0 45.0 72.0 2.9 227.0 19.0
0000c5 2 7 5 5 7 4 1 5 2 5 2 3 7 0 0 2 0 4 8 1 2 0 1 1 3 2 1 1 2 35.1 5.7 2.0 26.6 24.6 4.8 1.4 45.1 0.2 24.8 38.0 51.0 79.0 2.9 550.0 25.0
0000c6 2 7 7 7 5 7 3 7 1 7 5 5 7 0 0 3 1 6 9 1 2 0 1 1 3 2 1 3 2 60.4 7.2 2.6 32.3 18.2 7.6 1.3 169.0 0.1 70.3 34.0 39.0 72.0 2.9 415.0 70.0
0000c7 2 5 3 5 7 3 1 3 3 7 4 3 7 0 0 2 0 3 8 5 4 0 3 1 7 2 1 2 2 37.1 7.2 3.1 24.3 24.0 3.7 2.4 77.0 0.2 28.8 39.0 51.0 79.0 6.6 374.0 29.0
0000c8 2 1 3 7 3 3 1 3 1 5 4 5 7 0 0 2 0 3 8 4 3 0 3 1 7 3 1 2 2 38.9 10.0 4.0 26.3 25.4 3.9 1.7 87.3 0.1 39.1 36.0 60.0 114.0 5.2 400.0 39.0
0013c7 2 7 5 7 7 3 3 5 1 7 1 3 7 0 0 2 0 3 8 1 2 0 1 1 3 2 1 3 2 50.4 6.3 2.1 33.2 18.8 8.3 1.4 152.0 0.1 40.8 17.0 27.0 55.0 8.0 249.0 41.0
0017c8 2 7 7 7 5 3 2 7 1 5 1 5 7 0 0 2 0 2 6 1 3 0 1 1 5 3 1 3 2 42.8 6.2 2.0 28.6 17.6 10.8 2.0 178.0 0.2 23.2 32.0 38.0 55.0 2.3 100.0 23.0
0058c0 2 7 5 7 7 3 2 3 2 5 1 5 7 0 0 1 0 3 8 5 2 0 4 1 5 2 1 2 2 44.7 10.3 3.7 33.7 21.7 9.0 1.4 166.7 0.2 33.0 36.0 40.0 66.0 4.2 198.0 33.0
0058c6 2 7 5 5 5 3 1 7 1 5 9 2 3 0 0 3 0 3 6 4 3 0 4 1 7 3 1 3 2 53.0 6.2 2.8 32.0 23.7 5.8 2.8 78.3 0.2 8.0 36.0 40.0 66.0 5.0 102.0 8.0
;
/* A. Use %BIPLOT macro, which uses SAS/IML to compute the biplot coordinates.
Use the OUT= option to get the coordinates for the markers and vectors.
B. Transpose the data from long to wide form.
C. Use PROC SGPLOT to create the biplot
*/
%let FACTYPE = SYM; /* options are GH, COV, JK, SYM */
title "Biplot: &FACTYPE, STD";
%biplot(data=chili,
var=StC NA SP PGH BH LC LS LP NFA FP CC AC SE MS CP CM AS FCI FCM FS FSPA NBF FSBE FBEA FC FSr SC NSF GU PH MLL MLW PHF CWF FL FW FWt FT FPP DFt DFl DFF TSWt FPK Yd,
id=Acc,
factype=&FACTYPE, /* GH, COV, JK, SYM */
std=std, /* NONE, MEAN, STD */
scale=1, /* if you do not specify SCALE=1, vectors are auto-scaled */
out=biplotFriendly,/* write SAS data set with results */
symbols=circle dot, inc=1);
/* transpose from long to wide */
data Biplot;
set biplotFriendly(where=(_TYPE_='OBS') rename=(dim1=Prin1 dim2=Prin2 _Name_=_ID_))
biplotFriendly(where=(_TYPE_='VAR') rename=(dim1=vx dim2=vy _Name_=_Variable_));
run;
proc sgplot data=Biplot aspect=1 noautolegend;
refline 0 / axis=x; refline 0 / axis=y;
scatter x=Prin1 y=Prin2 / datalabel=_ID_;
vector x=vx y=vy / datalabel=_Variable_
lineattrs=GraphData2 datalabelattrs=GraphData2;
xaxis grid offsetmin=0.1 offsetmax=0.2;
yaxis grid;
run;
What is wrong with this code?
The warning and error that lead to halting og proc iml in the biplot macro
1093 title "Biplot: &FACTYPE, STD";
1094
1095
1096 %biplot(data = chili,
1097 var = StC NA SP PGH BH LC LS LP NFA FP CC AC SE
1098 CM FCI FCM FS FSPA FSBE FBEA
1099 FC FSr SC NSF GU PH MLL MLW PHF CWF FL FW
1100 FWt FT FPP DFt DFl DFF TSWt FPK Yd,
1101 /* removed MS CP AS NBF since these result in division by zero error */
1102 id = Acc,
1103 factype = &FACTYPE, /* GH, COV, JK, SYM */
1104 std = std, /* NONE, MEAN, STD */
1105 scale = 1, /* if you do not specify SCALE=1, vectors are auto-scaled */
1106 out = biplotFriendly,/* write SAS data set with results */
1107 symbols = circle dot, inc = 1);
NOTE: IML Ready
NOTE: Module BIPLOT defined.
NOTE: Module POWER defined.
NOTE: Module STR2VEC defined.
NOTE: Module READTAB defined.
NOTE: Module READLAB defined.
NOTE: Module CELLNAME defined.
NOTE: Module NOMISS defined.
WARNING: Division by zero, result set to missing value.
count : number of occurrences is 2
operation : / at line 5035 column 115
operands : *LIT1004, S
*LIT1004 1 row 1 col (numeric)
1
S 1 row 41 cols (numeric)
statement : ASSIGN at line 5035 column 99
traceback : module BIPLOT at line 5035 column 99
ERROR: (execution) Invalid argument or operand; contains missing values.
See my previous post for an example that is easier to analyze.
A few thoughts:
1. It appears that you copied the code from https://blogs.sas.com/content/iml/2019/11/13/create-biplots-sas.html It is always helpful if you cite references so that others can see where the code came from and read the accompanying discussion.
2. Your first mistake is that you didn't add an ID variable to your data set. Re-read the blog post to see how to add an ID variable.
3. The second problem is that three of your variables are constant. Freidnly's %BIPLOT macro does not handle constant variables, so you must remove them from the analysis.
%let VarNames = StC NA SP PGH BH LC LS LP NFA FP CC AC SE MS
CP CM AS FCI FCM FS FSPA NBF FSBE FBEA
FC FSr SC
NSF GU PH MLL MLW PHF CWF FL FW FWt FT FPP
DFt DFl DFF TSWt FPK Yd;
proc means data=chili;
var &VarNames;
run;
/* Note that the MS, FBEA, and SC variables are constant.
You need to exclude those variables.
*/
%let VarNames = StC NA SP PGH BH LC LS LP NFA FP CC AC SE
CP CM AS FCI FCM FS FSPA NBF FSBE
FC FSr
NSF GU PH MLL MLW PHF CWF FL FW FWt FT FPP
DFt DFl DFF TSWt FPK Yd;
%let FACTYPE = SYM; /* options are GH, COV, JK, SYM */
title "Biplot: &FACTYPE, STD";
%biplot(data=chili,
var=&VarNames,
id=id,
factype=&FACTYPE, /* GH, COV, JK, SYM */
std=std, /* NONE, MEAN, STD */
scale=1, /* if you do not specify SCALE=1, vectors are auto-scaled */
out=biplotFriendly,/* write SAS data set with results */
symbols=circle dot, inc=1);
/* transpose from long to wide */
data Biplot;
set biplotFriendly(where=(_TYPE_='OBS') rename=(dim1=Prin1 dim2=Prin2 _Name_=_ID_))
biplotFriendly(where=(_TYPE_='VAR') rename=(dim1=vx dim2=vy _Name_=_Variable_));
run;
proc sgplot data=Biplot aspect=1 noautolegend;
refline 0 / axis=x; refline 0 / axis=y;
scatter x=Prin1 y=Prin2 / datalabel=_ID_;
vector x=vx y=vy / datalabel=_Variable_
lineattrs=GraphData2 datalabelattrs=GraphData2;
xaxis grid offsetmin=0.1 offsetmax=0.2;
yaxis grid;
run;
data chili;
input Acc $6. StC NA SP PGH BH LC LS LP NFA FP CC AC SE MS CP CM AS FCI FCM FS FSPA NBF FSBE FBEA FC FSr SC NSF GU PH MLL MLW PHF CWF FL FW FWt FT FPP DFt DFl DFF TSWt FPK Yd;
datalines;
000210 2 5 7 7 3 3 3 5 1 5 1 3 7 0 0 2 0 3 8 1 2 0 1 1 3 2 1 3 2 42.7 5.8 1.6 28.9 18.1 5.8 1.1 49.3 0.1 23.1 74.0 33.0 44.0 3.9 500.0 23.0
000557 2 3 5 7 5 3 3 5 1 5 1 3 7 0 0 2 0 3 8 3 3 0 4 1 5 2 1 2 2 41.0 5.5 1.8 26.5 18.3 66.7 2.0 108.5 0.2 22.1 65.0 27.0 34.0 2.7 200.0 22.0
000692 2 5 3 7 7 3 3 3 1 5 1 3 7 0 0 2 0 2 8 1 2 0 1 1 3 2 1 2 2 39.2 5.9 1.9 28.6 16.4 8.6 1.0 124.0 0.1 50.7 33.0 39.0 65.0 3.1 413.0 51.0
001301 2 7 5 5 5 3 3 3 2 5 1 3 7 0 0 2 0 3 8 1 2 0 1 1 5 2 1 3 2 46.5 5.9 2.0 28.1 19.0 7.4 0.9 147.0 0.1 60.9 32.0 40.0 74.0 8.4 350.0 61.0
001785 2 7 5 5 7 3 2 5 1 5 1 5 7 0 0 3 0 3 9 3 3 0 1 1 5 2 1 3 2 50.8 5.0 1.6 27.9 22.5 9.0 2.4 247.5 0.1 47.0 29.0 35.0 6.0 3.6 100.0 47.0
008149 2 5 7 7 7 3 3 3 1 5 1 3 7 0 0 2 0 3 9 1 1 0 1 1 3 2 1 2 2 40.7 5.4 2.0 27.6 18.7 6.2 0.7 98.8 0.1 80.0 29.0 38.0 74.0 2.4 810.0 80.0
008220 2 5 3 7 3 3 2 3 1 5 1 3 7 0 0 2 0 3 9 1 2 0 1 1 5 2 1 3 2 46.0 6.2 2.3 26.0 17.5 10.0 1.1 115.5 0.1 32.6 33.0 40.0 66.0 4.2 280.0 33.0
008228 2 7 3 7 7 4 3 3 1 7 1 3 7 0 0 2 0 3 9 1 3 0 1 1 3 2 1 3 2 53.3 10.2 5.5 32.5 24.8 9.6 2.9 244.5 0.3 22.5 27.0 34.0 55.0 8.1 60.0 23.0
008230 2 5 7 5 7 3 3 7 1 5 1 3 7 0 0 2 0 3 9 1 2 0 1 1 3 2 1 3 2 37.3 5.6 1.8 23.3 18.5 6.9 0.9 114.8 0.1 48.2 29.0 38.0 74.0 4.3 419.0 48.0
001674 2 7 5 7 7 3 3 3 1 7 1 5 7 0 0 2 0 2 8 1 1 0 1 1 7 3 1 2 2 34.3 4.5 1.7 29.0 17.5 9.7 0.7 143.5 0.1 66.4 32.0 38.0 74.0 5.9 460.0 66.0
005867 2 3 5 7 5 3 3 5 1 5 1 3 7 0 0 2 0 3 8 1 2 0 1 1 7 2 1 3 2 37.2 4.1 1.8 28.8 18.0 7.7 0.8 86.8 0.1 39.5 32.0 39.0 74.0 4.0 455.0 40.0
016132 1 1 5 7 5 3 2 7 2 7 4 3 7 0 0 3 0 2 8 1 2 0 1 1 5 2 1 1 2 35.8 5.0 2.3 21.9 16.5 3.2 0.8 51.9 0.1 42.3 55.0 60.0 100.0 5.8 815.0 42.0
016395 2 5 5 7 5 4 3 5 1 3 1 5 7 0 0 2 1 2 6 3 5 0 3 1 5 2 1 3 3 33.9 5.2 2.2 26.7 20.6 8.3 3.7 211.5 0.3 16.3 29.0 34.0 55.0 3.8 55.0 16.0
016396 2 5 7 7 5 4 1 7 1 3 1 5 7 0 0 2 0 2 6 3 4 0 2 1 5 2 1 3 2 40.9 4.9 2.1 28.3 21.1 9.6 4.0 267.5 0.3 13.7 26.0 34.0 55.0 6.1 40.0 14.0
016400 2 7 5 7 7 3 2 3 1 5 1 3 7 0 0 2 0 3 8 3 3 0 1 1 5 2 1 2 2 33.1 5.5 2.0 25.3 19.0 4.8 0.9 75.0 0.1 36.9 29.0 35.0 74.0 6.3 528.0 37.0
016560 2 7 5 7 7 3 3 3 1 5 1 3 7 0 0 2 0 3 8 1 2 0 1 1 3 2 1 3 2 34.3 5.1 1.8 25.0 19.0 8.4 0.9 126.5 0.1 48.2 20.0 34.0 65.0 4.1 384.0 48.0
016586 1 1 5 7 5 3 2 3 1 7 4 4 7 0 0 2 0 2 8 4 3 0 1 1 7 3 1 2 3 40.4 5.0 2.1 22.0 22.3 4.3 2.0 135.2 0.2 49.8 32.0 48.0 74.0 3.9 368.0 50.0
016588 2 7 7 7 5 3 3 5 1 5 1 3 7 0 0 3 0 4 9 5 4 0 3 1 7 3 1 2 2 35.1 5.6 2.0 28.9 21.7 4.6 1.8 90.8 0.1 27.8 36.0 44.0 74.0 5.1 306.0 28.0
016596 2 5 5 7 5 3 1 7 2 5 4 5 7 0 0 3 1 3 8 3 2 0 1 1 5 3 1 2 2 40.4 5.9 2.1 23.3 20.8 4.6 1.2 67.5 0.1 33.5 49.0 60.0 82.0 3.0 490.0 34.0
016597 1 1 3 7 5 3 2 3 3 5 4 5 7 0 0 3 0 4 8 4 4 0 4 1 7 3 1 3 2 36.0 7.1 2.7 26.7 21.1 4.0 2.0 66.1 0.2 30.5 50.0 54.0 82.0 4.5 461.0 31.0
016599 1 1 5 7 5 3 2 7 2 7 4 3 7 0 0 2 0 2 9 3 3 0 1 1 5 2 1 1 2 54.5 5.4 2.4 35.6 20.8 2.5 0.8 30.1 0.1 55.5 48.0 60.0 114.0 4.2 1500.0 56.0
016600 2 5 7 5 7 3 3 7 1 5 1 3 7 0 0 2 0 3 8 1 2 1 4 1 5 3 1 3 2 41.3 6.5 2.3 24.3 19.8 14.2 1.7 179.0 0.1 76.0 16.0 34.0 55.0 6.7 420.0 76.0
016601 2 7 3 7 7 3 3 3 2 5 1 5 7 0 0 3 0 3 9 3 3 0 1 1 3 2 1 3 2 47.8 5.9 2.0 27.9 19.6 5.5 1.8 131.0 0.1 46.5 29.0 34.0 65.0 6.6 380.0 47.0
016603 3 3 5 7 5 7 2 3 2 7 4 5 7 0 0 2 1 3 8 4 2 0 1 1 7 3 1 1 2 53.2 8.8 4.4 32.5 27.2 5.6 1.7 96.2 0.1 40.3 41.0 51.0 74.0 4.1 418.0 40.0
016604 2 7 7 5 7 3 3 5 1 5 1 3 7 0 0 2 0 3 9 1 2 0 1 1 3 2 1 3 2 56.5 5.9 2.0 367.0 27.8 7.6 1.6 161.9 0.1 36.5 34.0 44.0 65.0 2.0 225.0 36.0
016609 2 3 5 5 7 3 3 3 2 3 1 5 7 0 0 3 0 3 8 1 1 1 3 1 3 2 1 3 2 65.5 7.4 2.8 38.1 21.6 9.0 0.8 153.0 0.1 48.6 34.0 38.0 65.0 4.7 317.0 49.0
0000c1 2 7 7 7 5 7 3 7 2 7 5 5 7 0 1 3 1 7 9 1 2 1 1 1 3 2 1 3 2 65.4 8.9 3.1 44.7 27.7 9.1 1.5 147.5 0.1 39.1 36.0 44.0 72.0 4.2 265.0 39.0
0000c2 2 7 5 7 5 3 2 3 1 7 4 3 7 0 0 2 0 3 9 4 4 0 4 1 7 3 1 2 2 38.0 6.4 2.1 30.3 27.6 4.4 2.2 94.2 0.1 35.2 55.0 59.0 79.0 3.2 373.0 35.0
0000c3 1 1 5 5 5 3 2 7 2 7 2 3 7 0 0 2 0 3 8 1 2 0 1 1 5 2 1 1 2 40.9 5.7 2.3 25.9 21.1 3.4 0.8 43.0 0.1 46.0 42.0 59.0 114.0 5.9 820.0 46.0
0000c4 2 7 7 7 3 7 1 7 1 5 8 5 7 0 0 2 1 6 9 5 3 0 4 1 3 2 1 3 2 70.7 7.5 2.8 35.7 19.2 6.4 2.1 85.0 0.2 19.3 39.0 45.0 72.0 2.9 227.0 19.0
0000c5 2 7 5 5 7 4 1 5 2 5 2 3 7 0 0 2 0 4 8 1 2 0 1 1 3 2 1 1 2 35.1 5.7 2.0 26.6 24.6 4.8 1.4 45.1 0.2 24.8 38.0 51.0 79.0 2.9 550.0 25.0
0000c6 2 7 7 7 5 7 3 7 1 7 5 5 7 0 0 3 1 6 9 1 2 0 1 1 3 2 1 3 2 60.4 7.2 2.6 32.3 18.2 7.6 1.3 169.0 0.1 70.3 34.0 39.0 72.0 2.9 415.0 70.0
0000c7 2 5 3 5 7 3 1 3 3 7 4 3 7 0 0 2 0 3 8 5 4 0 3 1 7 2 1 2 2 37.1 7.2 3.1 24.3 24.0 3.7 2.4 77.0 0.2 28.8 39.0 51.0 79.0 6.6 374.0 29.0
0000c8 2 1 3 7 3 3 1 3 1 5 4 5 7 0 0 2 0 3 8 4 3 0 3 1 7 3 1 2 2 38.9 10.0 4.0 26.3 25.4 3.9 1.7 87.3 0.1 39.1 36.0 60.0 114.0 5.2 400.0 39.0
0013c7 2 7 5 7 7 3 3 5 1 7 1 3 7 0 0 2 0 3 8 1 2 0 1 1 3 2 1 3 2 50.4 6.3 2.1 33.2 18.8 8.3 1.4 152.0 0.1 40.8 17.0 27.0 55.0 8.0 249.0 41.0
0017c8 2 7 7 7 5 3 2 7 1 5 1 5 7 0 0 2 0 2 6 1 3 0 1 1 5 3 1 3 2 42.8 6.2 2.0 28.6 17.6 10.8 2.0 178.0 0.2 23.2 32.0 38.0 55.0 2.3 100.0 23.0
0058c0 2 7 5 7 7 3 2 3 2 5 1 5 7 0 0 1 0 3 8 5 2 0 4 1 5 2 1 2 2 44.7 10.3 3.7 33.7 21.7 9.0 1.4 166.7 0.2 33.0 36.0 40.0 66.0 4.2 198.0 33.0
0058c6 2 7 5 5 5 3 1 7 1 5 9 2 3 0 0 3 0 3 6 4 3 0 4 1 7 3 1 3 2 53.0 6.2 2.8 32.0 23.7 5.8 2.8 78.3 0.2 8.0 36.0 40.0 66.0 5.0 102.0 8.0
;
%let VarNames = StC NA SP PGH BH LC LS LP NFA FP CC AC SE MS
CP CM AS FCI FCM FS FSPA NBF FSBE FBEA
FC FSr SC
NSF GU PH MLL MLW PHF CWF FL FW FWt FT FPP
DFt DFl DFF TSWt FPK Yd;
proc means data=chili;
var &VarNames;
run;
/* Note that the MS, FBEA, and SC variables are constant.
You need to exclude those variables.
*/
%let VarNames = StC NA SP PGH BH LC LS LP NFA FP CC AC SE
CP CM AS FCI FCM FS FSPA NBF FSBE
FC FSr
NSF GU PH MLL MLW PHF CWF FL FW FWt FT FPP
DFt DFl DFF TSWt FPK Yd;
%let FACTYPE = SYM; /* options are GH, COV, JK, SYM */
title "Biplot: &FACTYPE, STD";
%biplot(data=chili,
var=&VarNames,
id=id,
factype=&FACTYPE, /* GH, COV, JK, SYM */
std=std, /* NONE, MEAN, STD */
scale=1, /* if you do not specify SCALE=1, vectors are auto-scaled */
out=biplotFriendly,/* write SAS data set with results */
symbols=circle dot, inc=1);
/* transpose from long to wide */
data Biplot;
set biplotFriendly(where=(_TYPE_='OBS') rename=(dim1=Prin1 dim2=Prin2 _Name_=_ID_))
biplotFriendly(where=(_TYPE_='VAR') rename=(dim1=vx dim2=vy _Name_=_Variable_));
run;
proc sgplot data=Biplot aspect=1 noautolegend;
refline 0 / axis=x; refline 0 / axis=y;
scatter x=Prin1 y=Prin2 / datalabel=_ID_;
vector x=vx y=vy / datalabel=_Variable_
lineattrs=GraphData2 datalabelattrs=GraphData2;
xaxis grid offsetmin=0.1 offsetmax=0.2;
yaxis grid;
run;
Sir, I tried with your codes. Still I couldn't get the results. Could you please check what's wrong with It?
You did not follow my instructions. You need to add an ID variable, which is not currently in your data set. Alternatively, use ID=Acc, if that is your ID variable.
%biplot(data=chili,
var=&VarNames,
id=Acc,
factype=&FACTYPE, /* GH, COV, JK, SYM */
std=std, /* NONE, MEAN, STD */
scale=1, /* if you do not specify SCALE=1, vectors are auto-scaled */
out=biplotFriendly,/* write SAS data set with results */
symbols=circle dot, inc=1);
Thank you Sir. I got it. thanks again.
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