r - 我正在尝试使用 stringr，特别是正则表达式，来分割 "MA: Bristol County (25005)"

Question

我正在尝试获取一个变量列并将其分成几列。这些值遵循基本模式，县名称具有多种长度和格式。

State-county :
[1] "MA: Bristol County (25005)"
[2] "LA: St. Tammany Parish (22103)"
[3] "CA: Ventura County (06111)"    
[4] "CA: San Mateo County (06081)" 

我需要一个州、县名称和县代码列，我可以将其添加回 data.frame 中。一直试图弄清楚如何使用 str_extract 来完成任务。理想情况下，这就是我最终的结局，但我会寻求任何可以获得的帮助。

  state:    county:            county code: 
[1] "MA"   Bristol County       25005
[2] "LA"   St. Tammany Parish   22103
[3] "CA"   Ventura County       06111    
[4] "CA:   San Mateo County     06081

我能够使用我找到的代码 str_extract_all( "(?<=\\().+?(?=\\))")对于县代码(感谢 Nettle )，我能到达的最接近的州 abrev 是 'str_extract_all( h,"..:")它很接近，但包含“:”还尝试过:str_extract_all( "(?<=\\:")

抱歉，如果这不是最好的格式，我试图以我所见过的风格表达得非常清晰。

Answer 1

使用str_match_all:

str_match_all(df$State_county, "([A-Z]+): ([^()]+) \\((\\d+)\\)")

as_tibble(df) %>%
 mutate(matches=str_match_all(State_county, "([A-Z]+): ([^()]+) \\((\\d+)\\)")) %>%
  unnest_wider(matches) %>%
   select(-2) %>%
    set_names("State_county", "State", "County", "ZIP")
# A tibble: 4 x 4
  State_county                   State County             ZIP  
  <fct>                          <chr> <chr>              <chr>
1 MA: Bristol County (25005)     MA    Bristol County     25005
2 LA: St. Tammany Parish (22103) LA    St. Tammany Parish 22103
3 CA: Ventura County (06111)     CA    Ventura County     06111
4 CA: San Mateo County (06081)   CA    San Mateo County   06081

### OR with str_match as we're only using a single pattern
## this saves us from the warning caused by unnest_wider
as_tibble(df)  %>%
 mutate(matches=str_match(State_county, "([A-Z]+): ([^()]+) \\((\\d+)\\)"), State=matches[,2], County=matches[,3], ZIP=matches[,4], matches=NULL)
# A tibble: 4 x 4
  State_county                   State County             ZIP  
  <fct>                          <chr> <chr>              <chr>
1 MA: Bristol County (25005)     MA    Bristol County     25005
2 LA: St. Tammany Parish (22103) LA    St. Tammany Parish 22103
3 CA: Ventura County (06111)     CA    Ventura County     06111
4 CA: San Mateo County (06081)   CA    San Mateo County   06081 
### Another way 
str_match(df$State_county, "([A-Z]+): ([^()]+) \\((\\d+)\\)") %>%
 as.data.frame %>% set_names("State_county", "State", "County", "County_code")
                    State_county State             County County_code
1     MA: Bristol County (25005)    MA     Bristol County       25005
2 LA: St. Tammany Parish (22103)    LA St. Tammany Parish       22103
3     CA: Ventura County (06111)    CA     Ventura County       06111
4   CA: San Mateo County (06081)    CA   San Mateo County       06081

说明:

str_match 基本上将返回捕获的组(用非转义括号编写的子模式([A-Z]+))以及与完整模式匹配的完整字符串

• [A-Z]+:匹配状态缩写。
• [^()]+ :匹配非左括号的任何内容。县。
• \\((\\d+)\\) :匹配左括号 \\( 并在使用分组提取数字时关闭一个括号。县代码.

str_match(df$State_county, "([A-Z]+): ([^()]+) \\((\\d+)\\)")
     [,1]                             [,2] [,3]                 [,4]   
[1,] "MA: Bristol County (25005)"     "MA" "Bristol County"     "25005"
[2,] "LA: St. Tammany Parish (22103)" "LA" "St. Tammany Parish" "22103"
[3,] "CA: Ventura County (06111)"     "CA" "Ventura County"     "06111"
[4,] "CA: San Mateo County (06081)"   "CA" "San Mateo County"   "06081"