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I have had a cursory search here for an answer but it seems my knowledge of R is very limited and I am hoping someone could help me.

I have a dataframe that I have extracted from a larger data set (shown at the end of this post) and I would like to create a boxplot for each row, specifying the columns to use (Q1, min, max, median) etc.

Does anyone know of a way to do this?

The dataframe looks like this:

    delivered.median delivered.max delivered.min delivered.Q1 delivered.Q3 delivered_int.median delivered_int.max delivered_int.min delivered_int.Q1 delivered_int.Q3 delivered_empt.median delivered_empt.max delivered_empt.min
1              138         39752            47           74          289                  138             39577                47               73           289.00                   138              39752                 47
2              157         13398            53           89          333                  158             13334                54               89           335.00                   157              13398                 53
3              150         12301            55           88          288                  150             12301                55               88           286.00                   150              12241                 55
4              260        262637           101          151          812                  258            262637               101              150           691.00                   260             262605                101
5              201       2410244            92          129          399                  206           2383271                92              131           373.00                   199            2410244                 92
6              988        935154            59          313        37592                  992            934499                62              310         41457.00                   988             935154                 59
7              888       1085949           108          345         8835                  888           1078636               110              345          8550.75                   888            1085949                108
  delivered_empt.Q1 delivered_empt.Q3 delivered_tp.median delivered_tp.max delivered_tp.min delivered_tp.Q1 delivered_tp.Q3 delivered_tn.median delivered_tn.max delivered_tn.min delivered_tn.Q1 delivered_tn.Q3
1                74            290.00                  NA             -Inf              Inf              NA              NA                  NA             -Inf              Inf              NA              NA
2                89            332.00                 158            12749               58              89          336.25                  NA             -Inf              Inf              NA              NA
3                88            288.00                 147             1704               56              88          259.00                  NA             -Inf              Inf              NA              NA
4               152            849.00                 258           262637              101             149          695.25                 261           262605              101             152             849
5               129            410.00                 207            21510               92             132          369.00                 199          2410244               92             129             413
6               314          36215.25                1012           921513               65             327        43372.00                  NA             -Inf              Inf              NA              NA
7               345           8909.00                 891          1078636              111             346         8394.50                 888          1085949              108             345            8960
  delivered_fn.median delivered_fn.max delivered_fn.min delivered_fn.Q1 delivered_fn.Q3 delivered_fp.median delivered_fp.max delivered_fp.min delivered_fp.Q1 delivered_fp.Q3
1                  NA             -Inf              Inf              NA              NA                  NA             -Inf              Inf              NA              NA
2                  NA             -Inf              Inf              NA              NA                  NA             -Inf              Inf              NA              NA
3                  NA             -Inf              Inf              NA              NA                  NA             -Inf              Inf              NA              NA
4                 258           261608              102             151          858.25                 259           262039              102             151          667.25
5                 208            18650               94             132          371.00                 199          2383271               92             128          412.00
6                  NA             -Inf              Inf              NA              NA                  NA             -Inf              Inf              NA              NA
7                 869          1078759              111             339         7663.00                 877          1062541              110             343         9274.50

Thanks in advance!

Christopher Gwilliams
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  • `bxp` is probably the function you are after. http://stackoverflow.com/questions/11952819/is-it-possible-to-plot-a-boxplot-from-previously-calculated-statistics-easily-i – Pewi Mar 21 '15 at 10:08
  • Yep, that does seem to work. I did see the question but disregarded it. Through that, I found this question: http://stackoverflow.com/questions/10628847/geom-boxplot-with-precomputed-values?lq=1 and seems like the ideal way to do it. Thank you. Not sure if I close this or you add your link as an answer and I mark it? – Christopher Gwilliams Mar 21 '15 at 11:08

0 Answers0