left_join两个数据帧并覆盖 [英] left_join two data frames and overwrite

问题描述

我想合并两个数据框，其中 df2 会覆盖 NA 或 df1 。 合并数据框并覆盖值提供了数据。表选项，但是我想知道是否有一种方法可以使用 dplyr 来做到这一点。我已经尝试了所有 _join 选项，但似乎都没有这样做。有没有办法用 dplyr ？

I'd like to merge two data frames where df2 overwrites any values that are NA or present in df1. Merge data frames and overwrite values provides a data.table option, but I'd like to know if there is a way to do this with dplyr. I've tried all of the _join options but none seem to do this. Is there a way to do this with dplyr?

这里是一个例子：

df1 <- data.frame(y = c("A", "B", "C", "D"), x1 = c(1,2,NA, 4)) 
df2 <- data.frame(y = c("A", "B", "C"), x1 = c(5, 6, 7))

所需的输出：

  y x1
1 A  5
2 B  6
3 C  7
4 D  4

推荐答案

我认为您想要的是保持 df2 的值，仅添加 df1 中不存在的 df2 中没有的那些，这就是 anti_join 可以：

I think what you want is to keep the values of df2 and only add the ones in df1 that are not present in df2 which is what anti_join does:

anti_join返回x中的所有行，其中y中没有匹配的值，仅保留x中的列。

"anti_join return all rows from x where there are not matching values in y, keeping just columns from x."

我的解决方案：

df3 <- anti_join(df1, df2, by = "y") %>% bind_rows(df2)

Warning messages:
1: In anti_join_impl(x, y, by$x, by$y) :
  joining factors with different levels, coercing to character vector
2: In rbind_all(x, .id) : Unequal factor levels: coercing to character

> df3
Source: local data frame [4 x 2]

      y    x1
  (chr) (dbl)
1     D     4
2     A     5
3     B     6
4     C     7

此行给出所需的输出（在顺序不同），但是，您应该注意警告消息，在使用数据集时，请确保将 y 读取为字符变量。

this line gives the desired output (in a different order) but, you should pay attention to the warning message, when working with your dataset be sure to read y as a character variable.

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