如何用dplyr替换多列中的NA [英] How to replace NAs in multiple columns with dplyr

问题描述

我想使用当前 dplyr将以 v 开头的列中的 NA 替换为 x 列中的值(1.0.2)代码.

I would like to replace NAs in the columns that begin with v with the values in column x using current dplyr (1.0.2) code.

同一问题发布在此处，但

The same question is posted here, but the answer is outdated.

我一栏没问题:

suppressMessages(library(dplyr))
df <- data.frame(v1 = c(NA, 1, 2), v2 = c(3, NA, 4), v3 = c(5, 6, NA), x = c(7, 8, 9))
df %>% mutate(v1 = coalesce(v1, x))
#>   v1 v2 v3 x
#> 1  7  3  5 7
#> 2  1 NA  6 8
#> 3  2  4 NA 9

^由 reprex软件包(v0.3.0)创建于2020-11-03 sup>

^{Created on 2020-11-03 by the reprex package (v0.3.0)}

但无法弄清楚如何使其能够在多列中使用.

but can't figure out how to get it to work across multiple columns.

以下是我尝试不了的一些事情:

Here are a few things I've tried to no avail:

suppressMessages(library(dplyr))
df <- data.frame(v1 = c(NA, 1, 2), v2 = c(3, NA, 4), v3 = c(5, 6, NA), x = c(7, 8, 9))
df %>% mutate(across(starts_with("v")), . = coalesce(., x))
#> Error in list2(...): object 'x' not found

^{由 reprex软件包(v0.3.0)创建于2020-11-03 sup>}

^{Created on 2020-11-03 by the reprex package (v0.3.0)}

suppressMessages(library(dplyr))
df <- data.frame(v1 = c(NA, 1, 2), v2 = c(3, NA, 4), v3 = c(5, 6, NA), x = c(7, 8, 9))
df %>% mutate(across(starts_with("v")), . = coalesce(., df$x))
#> Error: Can't combine `..1` <data.frame> and `..2` <double>.

^{由 reprex软件包(v0.3.0)创建于2020-11-03 sup>}

^{Created on 2020-11-03 by the reprex package (v0.3.0)}

感谢您的帮助.

推荐答案

您与 across()非常接近.您想要的方法是:

You were very close with across(). The approach you want is:

df %>%
  mutate(across(starts_with("v"), coalesce, x))

请注意， coalesce 在 across()内 ，并且 x (可以将 coalesce()作为第三个参数提供.

Notice that the coalesce goes inside the across(), and that x (the second argument to coalesce() can be provided as a third argument. Result:

  v1 v2 v3 x
1  7  3  5 7
2  1  8  6 8
3  2  4  9 9

---

如果您更喜欢使用 coalesce(.，x)的方法，还可以使用〜将其作为匿名函数传递:

---

If you prefer something closer to your approach with coalesce(., x), you can also pass that as an anonymous function with a ~:

df %>%
  mutate(across(starts_with("v"), ~ coalesce(., x)))

在其他情况下，这可以更加灵活(例如，如果.不是该函数的第一个参数).

In other situations, this can be more flexible (for instance, if . is not the first argument to the function).

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