R-通过合并和超过2个后缀来减少（或：如何合并多个数据框并跟踪列） [英] R - reduce with merge and more than 2 suffixes (or: how to merge multiple dataframes and keep track of columns)
问题描述
我正在尝试基于2列合并4个数据框，但是要跟踪一列源自哪个数据框。我在跟踪列时遇到了问题。
I'm trying to merge 4 dataframes based on 2 columns, but keep track of which dataframe a column originated from. I'm running into an issue at tracking the columns.
（请参阅dput（dfs）的结尾）
(see end of post of dput(dfs))
#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)
这会产生以下警告：
警告消息：
在merge.data.frame（x，y，by = c（ Name， Color），all = TRUE，：
列名'Freq.df1'，'Freq.df2'在结果中重复
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 仅在名称上重复。填充 combo 第三和第四列的值实际上来自 df3 和 df4
df1 and df2 are only repeated in name. The values populating the third and fourth column of combo are actually from df3 and df4 respectively.
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
如何实现？我知道 merge（...，后缀）函数只能处理2的字符向量，但是我不知道应该怎么做。
How can I achieve this? I know the merge(..., suffixes) function can only handle a character vector of 2, but I don't know what the work around should be. Thanks!
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")
推荐答案
使用似乎更容易循环为 Reduce 或 reduce （ purrr ）一次仅获取两个数据集，因此我们在合并中不能有两个以上的后缀
This seems to be easier with a for loop as the Reduce or reduce (purrr) at a time takes only two datasets, so we can't have more than two suffixes in the merge.
在这里，我们创建了一个后缀向量（'sfx'）。使用第一个 list 元素初始化输出数据集。然后循环遍历 list.df的序列，并与 res和 list.df的下一个元素进行顺序的 merge code>，同时在每个步骤中更新 res
Here, we created a vector of suffixes ('sfx'). Initialize an output dataset with the first list element. Then loop through the sequence of 'list.df' and do a sequential merge with the 'res' and the next element of list.df while updating the 'res' in each step
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
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