如何使用 dplyr 加入多个数据帧？

Question

我要left_join多个数据帧：

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

之所以有效，是因为它们都具有相同的 b 列，但是 Reduce 不允许我指定可以传递给 left_join 的其他参数。是否有解决此类问题的方法？

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

这种工作方式：Reduce(function(...) left_join(..., by = c("b" = "d")), dfs) 但是当 by 不止一个元素时，它会给出此错误：Error: cannot join on columns 'b' x 'd': index out of bounds

Answer 1

这对你有用吗？

jnd.tbl <- df1 %>%
    left_join(df2, by='b') %>%
    left_join(df3, by='d')

Answer 2

我知道已经太迟了....今天我被介绍到未回答的问题部分。抱歉打扰了。

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

Answer 3

另一种解决方案：

library(purrr)
library(dplyr)

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"))
)

purrr::reduce(dfs, dplyr::left_join, by = 'b')

如何使用 dplyr 加入多个数据帧？

How to join multiple data frames using dplyr?

reduce

r

dplyr