r - 在R中使用我自己的函数汇总数据帧中的任意列数

我正在寻找一种方法来汇总R中的大型实验结果。由于我需要汇总任意数量的列(无法预先对这些列进行硬编码)并使用任意定义的汇总功能，因此汇总并非一帆风顺。

例如，我有以下平面表my_table

my_table
   id_1 id_2 rep_id value_1 value_2
1     a    1      1     0.0     0.0
2     a    1      2     0.2     0.2
3     a    1      3     0.3     0.3
4     a    1      4     0.4     0.4
5     a    1      5     0.1     0.1
6     a    2      1     0.5     0.0
7     a    2      2     1.5     1.5
8     a    2      3     2.5     2.5
9     a    2      4     3.5     3.5
10    a    2      5     4.5     4.5

我将my_table汇总到一个表中，例如:

> summary_table
  id_1 id_2 value_1.min value_1.max value_1.mean_plus_sd value_2.min value_2.max value_2.mean_plus_sd
1    a    1         0.0         0.4            0.3581139           0         0.4            0.3581139
2    a    2         0.5         4.5            4.0811388           0         4.5            4.1464249

总结很复杂，因为我想:

指定要分组的变量，例如key_fields = c("id_1","id_2")

指定要汇总的列，例如fields_to_summarize = c("value_1","value_2")

使用我自己的汇总功能(也为新列命名)

这是我目前用于执行所有这三项操作的代码。很好，但是效率也很低。任何改进将不胜感激:

library(plyr)

# create table
my_table = data.frame("id_1"  = c("a","a","a","a","a","a","a","a","a","a")
                    ,"id_2" = c("1","1","1","1","1","2","2","2","2","2")
                    ,"rep_id" = c(1,2,3,4,5,1,2,3,4,5)
                    ,"value_1"= c(0.0,0.2,0.3,0.4,0.1,0.5,1.5,2.5,3.5,4.5)
                    ,"value_2"= c(0.0,0.2,0.3,0.4,0.1,0.0,1.5,2.5,3.5,4.5)
    )

# specify columns to group by / summarize over
key_fields = c("id_1","id_2")
fields_to_summarize = c("value_1","value_2")

# create summary_table
counter = 1;
for (fname in fields_to_summarize){

  summary_function = function(D) data.frame(setNames(list(min(D[[fname]]),
                                                          max(D[[fname]]),
                                                          mean(D[[fname]])+sd(D[[fname]])),
                                                     paste(fname,c("min",
                                                                   "max",
                                                                   "mean_plus_sd"),
                                                           sep=".")
  ))

  tmp = ddply(.data = df,
                 .variable = key_fields,
                 function(D) summary_function(D))

  if (counter == 1){
    summary_table = tmp;
  } else {
    summary_table = join(x=summary_table,y=tmp,by=key_fields,type="left", match="all")
  }
  counter = counter + 1;
}

最佳答案

不是最终的解决方案，但也许是dplyr的一个好的开始

library(dplyr)

mean_plus_sd <- function(x) mean(x) + sd(x)
key_fields = c("id_1","id_2")

my_table %>%
  group_by_(.dots = key_fields) %>%
  summarise_each_(funs(min,max,mean_plus_sd), fields_to_summarize)

关于r - 在R中使用我自己的函数汇总数据帧中的任意列数，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/27770736/