如何使用dplyr加入多个数据帧？ [英] How to join multiple data frames using dplyr?

问题描述

我想要 left_join 多个数据框：

dfs <- list(
  df1 = data.frame(a = 1:3, b = c("a", "b", "c")),
  df2 = data.frame(c = 4:6, b = c("a", "c", "d")),
  df3 = data.frame(d = 7:9, b = c("b", "c", "e"))
)
Reduce(left_join, dfs)
#   a b  c  d
# 1 1 a  4 NA
# 2 2 b NA  7
# 3 3 c  5  8

这是因为它们都有相同的 b 列，但减少不允许我指定我可以传递给 left_join 。有这样的事情吗？

This works because they all have the same b column, but Reduce doesn't let me specify additional arguments that I can pass to left_join. Is there a work around for something like this?

dfs <- list(
  df1 = data.frame(a = 1:3, b = c("a", "b", "c")),
  df2 = data.frame(c = 4:6, d = c("a", "c", "d")),
  df3 = data.frame(d = 7:9, b = c("b", "c", "e"))
)

更新

的作品： Reduce（function（...）left_join（...，by = c（b=d）），dfs） c $ c> by 是一个以上的元素给出了这个错误：错误：不能加入列'b'x'd'：索引出边界

This kind of works: Reduce(function(...) left_join(..., by = c("b" = "d")), dfs) but when by is more than one element it gives this error: Error: cannot join on columns 'b' x 'd': index out of bounds

推荐答案

现在已经太晚了...今天我介绍了未回答的问题部分。很抱歉打扰

It's been too late i know....today I got introduced to the unanswered questions section. Sorry to bother.

使用 left_join（）

dfs <- list(
              df1 = data.frame(b = c("a", "b", "c"), a = 1:3),
              df2 = data.frame(d = c("a", "c", "d"), c = 4:6),
              df3 = data.frame(b = c("b", "c", "e"), d = 7:9)
         )

func <- function(...){
  df1 = list(...)[[1]]
  df2 = list(...)[[2]]
  col1 = colnames(df1)[1]
  col2 = colnames(df2)[1]
  xxx = left_join(..., by = setNames(col2,col1))
  return(xxx)
}
Reduce( func, dfs)
#  b a  c  d
#1 a 1  4 NA
#2 b 2 NA  7
#3 c 3  5  8

使用 merge（）：

func <- function(...){
  df1 = list(...)[[1]]
  df2 = list(...)[[2]]
  col1 = colnames(df1)[1]
  col2 = colnames(df2)[1]
  xxx=merge(..., by.x = col1, by.y = col2, , all.x = T)
  return(xxx)
}

Reduce( func, dfs)
#  b a  c  d
#1 a 1  4 NA
#2 b 2 NA  7
#3 c 3  5  8

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