r 来自不同长度和不同键的数据帧列表的多个连接

Question

假设我有这个数据框列表：

library(tidyverse)
df_list <- list(data.frame(cheese = c("ex","ok","bd"), 
                          cheese_val = c(3:1), 
                          stringsAsFactors = F),
               data.frame(egg = c("great","good","bad", "eww"), 
                          egg_val = c(4:1),
                          stringsAsFactors = F),
               data.frame(milk = c("good","bad"), 
                          milk_val = c(2:1), 
                          stringsAsFactors = F))

我有这个核心数据集：

core_dat <- data.frame(cheese = c("ex","ok","ok", "bd", "ok"), 
                      egg = c("great", "bad", "bad", "eww", "great"), 
                      milk = c("good", "good", "good", "bad", "good"), 
                      stringsAsFactors = F)

我想让core_dat 与df_list 的每个元素单独连接。

然后我尝试了这个：

for(i in 1:length(df_list)) {
  gg<-core_dat %>% 
    left_join(df_list[[i]], by = names(df_list[[i]][1]), copy = T)
}

它运行但仅将连接应用于milk 列，因此core_dat 中唯一的附加列是milk_val，但我预计也会看到cheese_val 和egg_val。

我怀疑这里有比 for 循环更合适的选项，我正在寻找建议。请注意，我的实际数据集比这个小例子有更多的 df。

我不应该期望生成的数据框，在本例中为 gg，总共包含 6 列（3 个标准名称 + 3 个带有“val”后缀的列），因此它看起来像这样的打印版本：

data.frame(cheese = c("ex","ok","ok", "bd", "ok"), 
                      egg = c("great", "bad", "bad", "eww", "great"), 
                      milk = c("good", "good", "good", "bad", "good"), 
                      chees_val = c(3, 2, 2, 1, 2), 
                      egg_val = c(4, 2, 2, 1, 4), 
                      milk_val = c(2, 2, 2, 1, 2))

我在这里看到了许多“多重连接”的答案，但没有一个与我在这里想要完成的任务完全一致（不同的键列、不同的数据长度）。

Answer 1

您可以使用map 获取已连接数据框的列表，然后使用reduce 将它们全部连接在一起。

map(df_list, right_join, rownames_to_column(core_dat)) %>%
  reduce(full_join)
# Joining, by = "cheese"
# Joining, by = "egg"
# Joining, by = "milk"
# Joining, by = c("cheese", "rowname", "egg", "milk")
# Joining, by = c("cheese", "rowname", "egg", "milk")
#   cheese cheese_val rowname   egg milk egg_val milk_val
# 1     ex          3       1 great good       4        2
# 2     ok          2       2   bad good       2        2
# 3     ok          2       3   bad good       2        2
# 4     bd          1       4   eww  bad       1        1
# 5     ok          2       5 great good       4        2

Answer 2

这应该会给出所需的输出：

Reduce(merge,c(df_list,list(core_dat)))
  cheese   egg milk cheese_val egg_val milk_val
1     bd   eww  bad          1       1        1
2     ex great good          3       4        2
3     ok   bad good          2       2        2
4     ok   bad good          2       2        2
5     ok great good          2       4        2