如何计算R中数据帧中每组的均值/中位数 [英] how to calculate mean/median per group in a dataframe in r

问题描述

我有一个数据帧，详细记录了客户的花费，如下所示:

I have a dataframe recording how much money a costomer spend in detail like the following:

custid, value
1,  1
1,  3
1,  2
1,  5
1,  4
1,  1
2,  1
2,  10
3,  1
3,  2
3,  5

如何使用均值，最大值，中位数，标准等来计算特征?使用一些套用功能吗?以及如何?

How to calcuate the charicteristics using mean,max,median,std, etc like the following? Use some apply function? And how?

custid, mean, max,min,median,std
1,  ....
2,....
3,....

推荐答案

要添加到替代方案中，请参见"doBy"包中的summaryBy，您可以在其中指定要应用的函数的list.

To add to the alternatives, here's summaryBy from the "doBy" package, with which you can specify a list of functions to apply.

library(doBy)
summaryBy(value ~ custid, data = mydf, 
          FUN = list(mean, max, min, median, sd))
#   custid value.mean value.max value.min value.median value.sd
# 1      1   2.666667         5         1          2.5 1.632993
# 2      2   5.500000        10         1          5.5 6.363961
# 3      3   2.666667         5         1          2.0 2.081666

---

当然，您也可以坚持使用R:

---

Of course, you can also stick with base R:

myFun <- function(x) {
  c(min = min(x), max = max(x), 
    mean = mean(x), median = median(x), 
    std = sd(x))
}

tapply(mydf$value, mydf$custid, myFun)
# $`1`
#      min      max     mean   median      std 
# 1.000000 5.000000 2.666667 2.500000 1.632993 
# 
# $`2`
#       min       max      mean    median       std 
#  1.000000 10.000000  5.500000  5.500000  6.363961 
# 
# $`3`
#      min      max     mean   median      std 
# 1.000000 5.000000 2.666667 2.000000 2.081666 

cbind(custid = unique(mydf$custid), 
      do.call(rbind, tapply(mydf$value, mydf$custid, myFun)))
#   custid min max     mean median      std
# 1      1   1   5 2.666667    2.5 1.632993
# 2      2   1  10 5.500000    5.5 6.363961
# 3      3   1   5 2.666667    2.0 2.081666

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