来自map（）调用的data.frames连接列表

问题描述：

是否存在一种 tidyverse方式来连接data.frames列表（例如 full_join（），但对于> 2个data.frames）？由于有 map（）的调用，我有一个data.frames列表。我以前曾使用 Reduce（）做类似的事情，但想将它们合并为管道的一部分-只是没有找到一种优雅的方法。玩具示例：

Is there a "tidyverse" way to join a list of data.frames (a la full_join(), but for >2 data.frames)? I have a list of data.frames as a result of a call to map(). I've used Reduce() to do something like this before, but would like to merge them as part of a pipeline - just haven't found an elegant way to do that. Toy example:

library(tidyverse)

## Function to make a data.frame with an ID column and a random variable column with mean = df_mean
make.df <- function(df_mean){
  data.frame(id = 1:50,
             x = rnorm(n = 50, mean = df_mean))
}

## What I'd love:
my.dfs <- map(c(5, 10, 15), make.df) #%>%
  # <<some magical function that will full_join() on a list of data frames?>>

## Gives me the result I want, but inelegant
my.dfs.joined <- full_join(my.dfs[[1]], my.dfs[[2]], by = 'id') %>%
  full_join(my.dfs[[3]], by = 'id')

## Kind of what I want, but I want to merge, not bind
my.dfs.bound <- map(c(5, 10, 15), make.df) %>%
  bind_cols()

答

我们可以使用 Reduce

set.seed(1453)
r1 <- map(c(5, 10, 15), make.df)  %>% 
           Reduce(function(...) full_join(..., by = "id"), .)

或者这可以通过 reduce

library(purrr)
set.seed(1453)
r2 <- map(c(5, 10, 15), make.df)  %>%
             reduce(full_join, by = "id")

identical(r1, r2)
#[1] TRUE

来自map（）调用的data.frames连接列表

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