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Editorial Team
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Asked: 2026-06-09T12:57:04+00:00

I have the following problem: I have the following table: > data StartPoint EndPoint

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I have the following problem: I have the following table:

> data
    StartPoint EndPoint timeDiff
1         A91    TX043      258
2         A91    TX048      547
3         A92    TX088      330
4         A91    TX088      289
5         A91    TX043      387
6         A92    TX088      241
7         A91    TX088      213
8         A92    TX043      295
9         A91    TX088      518
10        A92    TX088      414

I would need an aggregation of the following form:

StartPoint  EndPoint  count  mean(timeDiff)
   A91         TX088    3    mean of 289,213 and 518
   A91         TX043    2    mean of 258 and 387
   A91         TX048    1     547
   A92         TX088    3    mean of 330, 241 and 414
   A92         TX043    1     295

count is the number of occurences of same StartPoint and EndPoint pair and mean is the average of the timeDiff of the entries with same StartPoint and EndPoint pair. The result should be sorted on StartPoint, count and EndPoint.

Any help would be greatly appreciated.

Thanks in advance,
Sugi

my data:

data <- structure(list(StartPoint = c("A91", "A91", "A92", "A91", "A91", "A92", "A91", "A92", "A91", "A92"), EndPoint = c("TX043", "TX048", "TX088", "TX088", "TX043", "TX088", "TX088", "TX043", "TX088", "TX088"), timeDiff = c(258, 547, 330, 289, 387, 241, 213, 295, 518, 414)), .Names = c("StartPoint", "EndPoint", "timeDiff"), row.names = c(NA, 10L), class = "data.frame")
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1 Answer

  1. Editorial Team

    You can do this with the base function aggregate:

    aggregate(timeDiff~StartPoint+EndPoint,data,function(x) cbind(length(x),mean(x)))
  StartPoint EndPoint timeDiff.1 timeDiff.2
1        A91    TX043     2.0000   322.5000
2        A92    TX043     1.0000   295.0000
3        A91    TX048     1.0000   547.0000
4        A91    TX088     3.0000   340.0000
5        A92    TX088     3.0000   328.3333

    But the ddply in the plyr package might give more pleasing results:

    library(plyr)
ddply(data,c(.(StartPoint),.(EndPoint)),summarise,count=length(timeDiff),mean=mean(timeDiff))
  StartPoint EndPoint count     mean
1        A91    TX043     2 322.5000
2        A91    TX048     1 547.0000
3        A91    TX088     3 340.0000
4        A92    TX043     1 295.0000
5        A92    TX088     3 328.3333
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