R - 减少合并和超过 2 个后缀(或 : how to merge multiple dataframes and keep track of columns)

Question

我正在尝试基于 2 列合并 4 个数据帧，但要跟踪列源自哪个数据帧。我在跟踪列时遇到了问题。

(见 dput(dfs) 帖子的结尾)

#df example (df1)
Name    Color    Freq
banana  yellow   3
apple   red      1
apple   green    4
plum    purple   8


#create list of dataframes
list.df <- list(df1, df2, df3, df4)

#merge dfs on column "Name" and "Color"
combo.df <- Reduce(function(x,y) merge(x,y, by = c("Name", "Color"), all = TRUE, accumulate=FALSE, suffixes = c(".df1", ".df2", ".df3", ".df4")), list.df)

这给出了以下警告:

Warning message: In merge.data.frame(x, y, by = c("Name", "Color"), all = TRUE, : column names ‘Freq.df1’, ‘Freq.df2’ are duplicated in the result

并输出此数据帧:

#combo df example
Name    Color    Freq.df1   Freq.df2  Freq.df1  Freq.df2
banana  yellow   3          3         7         NA
apple   red      1          2         9         1
apple   green    4          NA        8         2
plum    purple   8          1         NA        6

df1和 df2只是名字重复。填充 combo 的第三和第四列的值实际上来自 df3和 df4分别。

我真正想要的是:

Name    Color    Freq.df1   Freq.df2  Freq.df3  Freq.df4
banana  yellow   3          3         7         NA
apple   red      1          2         9         1
apple   green    4          NA        8         2
plum    purple   8          1         NA        6

我怎样才能做到这一点？我知道 merge(..., suffixes) function 只能处理 2 的字符向量，但我不知道解决方法应该是什么。谢谢!

df1 <- 
structure(list(Name = structure(c(2L, 1L, 1L, 3L), .Label = c("apple", 
"banana", "plum"), class = "factor"), Color = structure(c(4L, 
3L, 1L, 2L), .Label = c("green", "purple", "red", "yellow"), class = "factor"), 
    Freq = c(3, 1, 4, 8)), .Names = c("Name", "Color", "Freq"
), row.names = c(NA, -4L), class = "data.frame")

df2 <-
structure(list(Name = structure(c(2L, 1L, 3L), .Label = c("apple", 
"banana", "plum"), class = "factor"), Color = structure(c(3L, 
2L, 1L), .Label = c("purple", "red", "yellow"), class = "factor"), 
    Freq = c(3, 2, 1)), .Names = c("Name", "Color", "Freq"), row.names = c(NA, 
-3L), class = "data.frame")

df3 <-
structure(list(Name = structure(c(2L, 1L, 1L), .Label = c("apple", 
"banana"), class = "factor"), Color = structure(c(3L, 2L, 1L), .Label = c("green", 
"red", "yellow"), class = "factor"), Freq = c(7, 9, 8)), .Names = c("Name", 
"Color", "Freq"), row.names = c(NA, -3L), class = "data.frame")

df4 <-
structure(list(Name = structure(c(1L, 1L, 2L), .Label = c("apple", 
"plum"), class = "factor"), Color = structure(c(3L, 1L, 2L), .Label = c("green", 
"purple", "red"), class = "factor"), Freq = c(1, 2, 6)), .Names = c("Name", 
"Color", "Freq"), row.names = c(NA, -3L), class = "data.frame")

Answer 1

这似乎更容易使用 for循环为 Reduce或 reduce ( purrr ) 一次只需要两个数据集，所以我们不能有超过两个 suffixes在 merge .

在这里，我们创建了一个后缀向量 ('sfx')。使用第一个 list 初始化输出数据集元素。然后遍历'list.df'的序列并执行顺序merge 'res' 和 list.df 的下一个元素在每一步更新“res”时

sfx <- c(".df1", ".df2", ".df3", ".df4")
res <- list.df[[1]]
for(i in head(seq_along(list.df), -1)) {

 res <- merge(res, list.df[[i+1]], all = TRUE, 
                 suffixes = sfx[i:(i+1)], by = c("Name", "Color"))
  }

res
#    Name  Color Freq.df1 Freq.df2 Freq.df3 Freq.df4
#1  apple  green        4       NA        8        2
#2  apple    red        1        2        9        1
#3 banana yellow        3        3        7       NA
#4   plum purple        8        1       NA        6