使用 dplyr 加入两个数据帧时，我可以替换 NAs 吗? [英] Can I replace NAs when joining two data frames with dplyr?

问题描述

我想加入两个数据框.一些列名称重叠，并且在数据框的重叠列之一中有 NA 条目.这是一个简化的例子:

I would like to join two data frames. Some of the column names overlap, and there are NA entries in one of the data frame's overlapping columns. Here is a simplified example:

df1 <- data.frame(fruit = c('apples','oranges','bananas','grapes'), var1 = c(1,2,3,4), var2 = c(3,NA,6,NA), stringsAsFactors = FALSE)
df2 <- data.frame(fruit = c('oranges','grapes'), var2=c(5,6), var3=c(7,8), stringsAsFactors = FALSE)

我是否可以使用 dplyr 连接函数来连接这些数据框并自动优先处理非NA 条目，以便我获得var2"?列在连接的数据框中没有 NA 条目?现在，如果我调用 left_join，它会保留 NA 条目，如果我调用 full_join，它会复制行.

Can I use dplyr join functions to join these data frames and automatically prioritize the non-NA entry so that I get the "var2" column to have no NA entries in the joined data frame? As it is now, if I call left_join, it keeps the NA entries, and if I call full_join it duplicates the rows.

示例数据

> df1
    fruit var1 var2
1  apples    1    3
2 oranges    2   NA
3 bananas    3    6
4  grapes    4   NA
> df2
    fruit var2 var3
1 oranges    5    7
2  grapes    6    8

推荐答案

coalesce 可能是您需要的.它用来自相应位置的第二个向量的值填充第一个向量的 NA:

coalesce might be something you need. It fills the NA from the first vector with values from the second vector at corresponding positions:

library(dplyr)
df1 %>% 
        left_join(df2, by = "fruit") %>% 
        mutate(var2 = coalesce(var2.x, var2.y)) %>% 
        select(-var2.x, -var2.y)

#     fruit var1 var3 var2
# 1  apples    1   NA    3
# 2 oranges    2    7    5
# 3 bananas    3   NA    6
# 4  grapes    4    8    6

或者使用data.table，它进行就地替换:

Or use data.table, which does in-place replacing:

library(data.table)
setDT(df1)[setDT(df2), on = "fruit", `:=` (var2 = i.var2, var3 = i.var3)]
df1
#      fruit var1 var2 var3
# 1:  apples    1    3   NA
# 2: oranges    2    5    7
# 3: bananas    3    6   NA
# 4:  grapes    4    6    8

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