多列上的R dplyr过滤字符串条件 [英] R dplyr filter string condition on multiple columns

问题描述

我有一个 df，例如

df <-read.table(text="
v1 v2 v3 v4 v5
1  A  B  X  C
2  A  B  C  X
3  A  C  C  C
4  B  D  V  A
5  B  Z  Z  D", header=T)

如果变量有X"，我如何过滤变量 v2 到 v5.我看过一些使用 filter at 的例子，但这些例子似乎只适用于数字条件.

How can I filter variables v2 to v5 if they have an "X". I've seen some examples using filter at but those seem to work only for numeric conditions.

filter_at(vars(contains("prefix")), all_vars(.>5))

并将 >5 替换为X"不起作用

and replacing >5 for "X" does not work

推荐答案

您可以使用 filter_at 和 any_vars 来选择至少具有一个 值的行X".

You can use filter_at with any_vars to select rows that have at least one value of "X".

library(dplyr)
df %>% filter_at(vars(v2:v5), any_vars(. == 'X'))

#  v1 v2 v3 v4 v5
#1  1  A  B  X  C
#2  2  A  B  C  X

但是，filter_at 已被取代，因此要将其转换为 across，您可以这样做:

However, filter_at has been superseeded so to translate this into across you can do :

df %>% filter(Reduce(`|`, across(v2:v5, ~. == 'X')))

---

在基础 R 中也更容易:

---

It is also easier in base R :

df[rowSums(df[-1] == 'X') > 0, ]

这篇关于多列上的R dplyr过滤字符串条件的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！