时间戳

首页 > 解决方案 > R - Purrr - 将功能应用于列表中的小标题

r - R - Purrr - 将功能应用于列表中的小标题

问题描述

我需要一些帮助，将函数应用于分别存储在同一列表中的四个小标题。

功能：

status_fun <- function(Status,
                       Escalated,
                       Created,
                       Resolved
                       ){
  if(Escalated == "Yes"){
    return("Escalated")
    } else if(Status == "Closed" && (month(Created) == month(Resolved) || Resolved - Created < 5
              )
    ){
      return("Closed")
    } else {
      return("Not Solved")
    }
}

我有一个列表，里面有 4 个不同大小的小方块。我只是想将上面使用四列的函数应用于每个小标题，但我遇到了各种各样的错误。我已经尽可能多地搜索并阅读了 R4DS 和其他帖子，但我找不到解决方案。


dummy %>%
   map(., status_fun)
Error in .f(.x[[i]], ...) : 
 argument "Escalated" is missing with no default

dummy %>%
   map(~ map(., status_fun))
Error in .f(.x[[i]], ...) : 
  argument "Escalated" is missing with no default

以下返回一个只有一个值的列表，我对此不感兴趣，我想要一个具有与输入相同维度（行）的四个小标题的列表

dummy %>%
   map(., ~ status_fun(Status = 'Status', Escalated = 'Escalated', Created = 'Created', Resolved = 'Resolved'))
[[1]]
[1] "Not Solved"

[[2]]
[1] "Not Solved"

[[3]]
[1] "Not Solved"

[[4]]
[1] "Not Solved"

虚拟列表如下：

[[1]]
# A tibble: 589 x 5
   Created    Resolved   Status      Country    Escalated
   <date>     <date>     <chr>       <chr>      <chr>    
 1 2020-04-03 2020-04-08 Closed      Luxembourg No       
 2 2020-03-31 NA         In Progress France     No       
 3 2020-03-31 NA         In Progress France     No       
 4 2020-03-31 NA         In Progress Luxembourg No       
 5 2020-03-31 NA         In Progress Luxembourg No       
 6 2020-03-30 NA         In Progress France     Yes       
 7 2020-03-27 NA         In Progress Ireland    No       
 8 2020-03-27 2020-04-10 Closed      Luxembourg No       
 9 2020-03-27 NA         In Progress Luxembourg No       
10 2020-03-27 2020-03-30 Closed      Ireland    No       
# ... with 579 more rows

[[2]]
# A tibble: 316 x 5
   Created    Resolved   Status               Country    Escalated
   <date>     <date>     <chr>                <chr>      <chr>    
 1 2020-04-13 NA         Open                 Luxembourg No       
 2 2020-04-13 NA         Open                 Spain      No       
 3 2020-04-07 NA         Open                 France     No       
 4 2020-04-03 NA         In Progress          Luxembourg No       
 5 2020-03-30 NA         Awaiting Information Luxembourg No       
 6 2020-03-30 NA         Awaiting Information France     Yes       
 7 2020-03-30 2020-03-31 Closed               France     No       
 8 2020-03-30 NA         Awaiting Information France     No       
 9 2020-03-30 NA         Awaiting Information Spain      No       
10 2020-03-30 NA         Awaiting Information Sweden     No       
# ... with 306 more rows

[[3]]
# A tibble: 64 x 5
   Created    Resolved   Status               Country Escalated
   <date>     <date>     <chr>                <chr>   <chr>    
 1 2020-04-13 NA         Open                 Chile   No       
 2 2020-04-10 NA         Open                 Mexico  Yes      
 3 2020-04-10 NA         Awaiting Information Mexico  No       
 4 2020-04-09 NA         Open                 Chile   No       
 5 2020-04-03 2020-04-06 Closed               Mexico  Yes       
 6 2020-04-02 2020-04-02 Closed               Mexico  No       
 7 2020-04-01 2020-04-01 Closed               Mexico  No       
 8 2020-03-31 2020-04-01 Closed               Brazil  No       
 9 2020-03-30 2020-03-31 Closed               Mexico  No       
10 2020-03-27 2020-04-06 Closed               Mexico  No       
# ... with 54 more rows

[[4]]
# A tibble: 30 x 5
   Created    Resolved   Status      Country Escalated
   <date>     <date>     <chr>       <chr>   <chr>    
 1 2020-04-13 NA         Open        Chile   No       
 2 2020-04-07 NA         Open        Brazil  No       
 3 2020-03-23 2020-03-25 Closed      Chile   No       
 4 2020-03-17 2020-03-18 Closed      Chile   No       
 5 2020-03-16 NA         Open        Mexico  No       
 6 2020-03-11 2020-03-11 Closed      Brazil  No       
 7 2020-03-11 2020-03-12 Closed      Brazil  No       
 8 2020-03-10 2020-03-10 Closed      Brazil  No       
 9 2020-03-09 NA         In Progress Brazil  No       
10 2020-03-02 2020-03-03 Closed      Brazil  No       
# ... with 20 more rows

我错过了什么？ 我已经尝试了各种 pmap，map_2，此处的说明Code not working using map from purrr package in R 和此处Apply function to nested loop (purrr package?) 但没有成功..提前感谢愿意接受他们的人是时候解决我的问题了。

> version        _                           
platform       x86_64-w64-mingw32          
arch           x86_64                      
os             mingw32                     
system         x86_64, mingw32             
status                                     
major          4                           
minor          0.0                         
year           2020                        
month          04                          
day            24                          
svn rev        78286                       
language       R                           
version.string R version 4.0.0 (2020-04-24)
nickname       Arbor Day  

packageVersion("tidyverse")
[1] ‘1.3.0’

packageVersion("lubridate")
[1] ‘1.7.8’

标签： rdictionarypurrr

解决方案

一个问题是您将单个传递给data.frame需要 4 个参数的函数。要解决此问题，您可以将功能更改为：

new_fx = function (DF) {
Status = DF$Status
Escalated = DF$Escalated
...
}
map(dummy, new_fx)

下一个潜在问题是您使用if ... else.... 因为这不是具有预期输出的可重现示例，所以我假设您想在if ... else...语句中添加一列。您将希望摆脱双重&&，||因为它们将评估为单个逻辑值。

除此之外，切换到 usingifelse或者，因为您在中，您可以使用case_when()将产生预期长度的向量。

推荐阅读