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r - （提取/分离/匹配）任意顺序的组

问题描述

# Sample Data Frame
df  <- data.frame(Column_A 
                  =c("1011 Red Cat", 
                     "Mouse 2011 is in the House 3001", "Yellow on Blue Dog walked around Park"))

我有一列手动输入的数据，我正在尝试清理这些数据。 

  Column_A 
1|1011 Red Cat                         |
2|Mouse 2011 is in the House 3001      |
2|Yellow on Blue Dog walked around Park|

我想将每个特征分成它自己的列，但仍然保持 A 列以便稍后提取其他特征。

  Colour               Code           Column_A
1|Red                 |1001          |Cat
2|NA                  |2001 3001     |Mouse is in the House
3|Yellow on Blue      |NA            |Dog walked around Park

迄今为止，我一直在使用 gsub 和捕获组重新排序它们，然后使用 Tidyr::extract 将它们分开。

library(dplyr)
library(tidyr)
library(stringr)

df1 <- df %>% 

  # Reorders the Colours
  mutate(Column_A = gsub("(.*?)?(Yellow|Blue|Red)(.*)?", "\\2 \\1\\3", 
                         Column_A, perl = TRUE)) %>%
  # Removes Whitespaces 
  mutate(Column_A =str_squish(Column_A)) %>%
  # Extracts the Colours 
  extract(Column_A, c("Colour", "Column_A"), "(Red|Yellow|Blue)?(.*)") %>%

  # Repeats the Prececding Steps for Codes
  mutate(Column_A = gsub("(.*?)?(\\b\\d{1,}\\b)(.*)?", "\\2 \\1\\3", 
                         Column_A, perl = TRUE)) %>%
  mutate(Column_A =str_squish(Column_A)) %>%
  extract(Column_A, c("Code", "Column_A"), "(\\b\\d{1,}\\b)?(.*)") %>%
  mutate(Column_A = str_squish(Column_A))

结果如下：

Colour      Code    Column_A
|Red        |1011   |Cat
|Yellow     |NA     |on Blue Dog walked around Park
|NA         |1011   |Mouse is in the House 1001

这适用于第一行，但不适用于前面的空格和单词分隔的空格，我随后一直在提取和合并它们。这样做的更优雅的方式是什么？

标签： rregextidyversetidyrstringr

解决方案

这是一个结合stringr和的解决方案gsub，使用 R 中提供的颜色列表：

library(dplyr)
library(stringr)

# list of colours from R colors()
cols <- as.character(colors())

apply(df,
      1,
      function(x)

        tibble(
          # Exctract CSV of colours
          Color = cols[cols %in% str_split(tolower(x), " ", simplify = T)] %>%
            paste0(collapse = ","),

          # Extract CSV of sequential lists of digits
          Code = str_extract_all(x, regex("\\d+"), simplify = T) %>%
            paste0(collapse = ","),

          # Remove colours and digits from Column_A
          Column_A = gsub(paste0("(\\d+|",
                                 paste0(cols, collapse = "|"),
                                 ")"), "", x, ignore.case = T) %>% trimws())) %>%
  bind_rows()

# A tibble: 3 x 3
  Color       Code      Column_A                  
  <chr>       <chr>     <chr>                     
1 red         1011      Cat                       
2 ""          2011,3001 Mouse  is in the House    
3 blue,yellow ""        on  Dog walked around Park

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