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library(tidyverse, warn.conflicts = TRUE)
#> Warning: package 'tidyverse' was built under R version 3.6.3
#> Warning: package 'ggplot2' was built under R version 3.6.3
#> Warning: package 'tidyr' was built under R version 3.6.3
#> Warning: package 'purrr' was built under R version 3.6.3
#> Warning: package 'dplyr' was built under R version 3.6.3
#> Warning: package 'stringr' was built under R version 3.6.3
#> Warning: package 'forcats' was built under R version 3.6.3
df <- tibble(x = 1:10, y = 11:20, z = rep(1:2, each = 5),a = runif(10))
df %>% mutate(across(c(x, a), ~ .x / y))
#> # A tibble: 10 x 4
#>         x     y     z      a
#>     <dbl> <int> <int>  <dbl>
#>  1 0.0909    11     1 0.0885
#>  2 0.167     12     1 0.0464
#>  3 0.231     13     1 0.0586
#>  4 0.286     14     1 0.0590
#>  5 0.333     15     1 0.0111
#>  6 0.375     16     2 0.0595
#>  7 0.412     17     2 0.0320
#>  8 0.444     18     2 0.0311
#>  9 0.474     19     2 0.0386
#> 10 0.5       20     2 0.0236

由reprex 包（v0.3.0）于 2020 年 8 月 1 日创建

从上面的示例中，我想将列 x 和 a 除以 y 行。建议的方法在此页面上单击此处但我必须在跨函数中使用列名作为参数。有什么办法，我可以用列号代替他们的名字吗？如果我可以将这个技巧用于所有实例，我将不胜感激。

4

2 回答 2

2

我们可以用列索引替换未加引号的名称

library(dplyr)
df %>%
      mutate(across(c(1, 4), ~ .x / y))
# A tibble: 10 x 4
#        x     y     z        a
#    <dbl> <int> <int>    <dbl>
# 1 0.0909    11     1 0.0470  
# 2 0.167     12     1 0.000267
# 3 0.231     13     1 0.0453  
# 4 0.286     14     1 0.0327  
# 5 0.333     15     1 0.0382  
# 6 0.375     16     2 0.0453  
# 7 0.412     17     2 0.0105  
# 8 0.444     18     2 0.0329  
# 9 0.474     19     2 0.0396  
#10 0.5       20     2 0.0249
于 2020-08-01T01:42:54.803 回答
0

我们可以使用列名

df2 <- df %>% 
  rowwise() %>% 
  mutate(across(c(x,a), ~ .x/y))
df2
# A tibble: 10 x 4
# Rowwise: 
#   x     y     z         a
# <dbl> <int> <int>     <dbl>
# 1 0.0909    11     1 0.0889   
# 2 0.167     12     1 0.0751   
# 3 0.231     13     1 0.0634   
# 4 0.286     14     1 0.0626   
# 5 0.333     15     1 0.0122   
# 6 0.375     16     2 0.0147   
# 7 0.412     17     2 0.00868  
# 8 0.444     18     2 0.0000776
# 9 0.474     19     2 0.0349   
# 10 0.5      20     2 0.00526
于 2020-08-01T01:51:44.630 回答