使用 pmap 将不同的正则表达式应用于 tibble 中的不同变量? [英] Using pmap to apply different regular expressions to different variables in a tibble?

问题描述

我正在尝试将不同的正则表达式应用于小标题中的不同变量.例如，我制作了一个 tibble 列表 1) 我要修改的变量名称，2) 我要匹配的正则表达式，以及 3) 替换字符串.我想将正则表达式/替换应用于不同数据框中的变量.

I'm trying to apply different regular expressions to different variables in a tibble. For example, I've made a tibble listing 1) the variable name I want to modify, 2) the regex I want to match, and 3) the replacement string. I'd like to apply the regex/replacement to the variable in a different data frame.

所以我的配置"标题如下所示:

So my "configuration" tibble looks like this:

test_config <-  dplyr::tibble(
  string_col = c("col1", "col2", "col3", "col4"),
  pattern = c("^\\.$", "^NA$", "^NULL$", "^$"),
  replacement = c("","","", "")
)

我想将此应用于目标小标题:

I'd like to apply this to a target tibble:

test_target <- dplyr::tibble(
  col1 = c("Foo", "bar", ".", "NA", "NULL"),
  col2 = c("Foo", "bar", ".", "NA", "NULL"),
  col3 = c("Foo", "bar", ".", "NA", "NULL"),
  col4 = c("NULL", "NA", "Foo", ".", "bar")
)

所以目标是在 test_target 的每一列/变量中用空字符串替换不同的字符串.

So the goal is to replace a different string with an empty string in each column/variable of the test_target.

结果应该是这样的:

result <- dplyr::tibble(
  col1 = c("Foo", "bar", "", "NA", "NULL"),
  col2 = c("Foo", "bar", ".", "", "NULL"),
  col3 = c("Foo", "bar", ".", "NA", ""),
  col4 = c("NULL", "NA", "Foo", ".", "bar")
)

我可以用 for 循环做我想做的事，就像这样:

I can do what I want with a for loop, like this:

for (i in seq(nrow(test_config))) {
  test_target <- dplyr::mutate_at(test_target,
                   .vars = dplyr::vars(
                     tidyselect::matches(test_config$string_col[[i]])),
                   .funs = dplyr::funs(
                     stringr::str_replace_all(
                       ., test_config$pattern[[i]], 
                       test_config$replacement[[i]]))
  )
}

相反，有没有更整洁的方式来做我想做的事?到目前为止，我认为 purrr::pmap 是完成这项工作的工具，我制作了一个函数，它接受一个数据框、变量名、正则表达式和替换值，并返回数据框修改了单个变量.它的行为符合预期:

Instead, is there a more tidy way to do what I want? So far, thinking that purrr::pmap was the tool for the job, I've made a function that takes a data frame, variable name, regular expression, and replacement value and returns the data frame with a single variable modified. It behaves as expected:

testFun <- function(df, colName, regex, repVal){
  colName <- dplyr::enquo(colName)
  df <- dplyr::mutate_at(df,
                         .vars = dplyr::vars(
                           tidyselect::matches(!!colName)),
                         .funs = dplyr::funs(
                           stringr::str_replace_all(., regex, repVal))
  )
}

# try with example
out <- testFun(test_target, 
               test_config$string_col[[1]], 
               test_config$pattern[[1]], 
               "")

然而，当我尝试在 pmap 中使用该函数时，我遇到了几个问题:1) 有没有比这更好的方法来为 pmap 调用构建列表?

However, when I try to use that function with pmap, I run into a couple problems: 1) is there a better way to build the list for the pmap call than this?

purrr::pmap(
    list(test_target, 
         test_config$string_col, 
         test_config$pattern, 
         test_config$replacement),
    testFun
)

2) 当我调用 pmap 时，出现错误:

2) When I call pmap, I get an error:

Error in UseMethod("tbl_vars") : 
  no applicable method for 'tbl_vars' applied to an object of class "character"
Called from: tbl_vars(tbl)

你们中的任何人都可以建议一种使用 pmap 来做我想做的事情的方法，或者是否有不同或更好的 tidyverse 方法来解决这个问题?

Can any of you suggest a way to use pmap to do what I want, or is there a different or better tidyverse approach to the problem?

谢谢！

推荐答案

你不需要创建函数(你的函数实际上是问题的根源):你可以直接使用str_replace_all.

You don't need to create a function (your function is actually the source of the problem): you can use str_replace_all directly.

pmap_dfr(
  list(test_target,
       test_config$pattern,
       test_config$replacement),
  str_replace_all
)

# A tibble: 5 x 4
  col1  col2  col3  col4 
  <chr> <chr> <chr> <chr>
1 Foo   Foo   Foo   NULL 
2 bar   bar   bar   NA   
3 ""    .     .     Foo  
4 NA    ""    NA    .    
5 NULL  NULL  ""    bar  

这篇关于使用 pmap 将不同的正则表达式应用于 tibble 中的不同变量?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！