在名称之间放置逗号

我试图找出数据框中是否出现某些模式。

假设我有以下“模式词典”（注意“james”与“jamesj”）：

patterns <- c("john", "jack", "james", "jamesj", "jason")

我的实际数据框（“date_frame”）如下所示：

  id                                              names
1  1                                     johnjack jameS
2  2                             john/james, jasonjames
3  3                                    peter_jackjason
4  4                                   jamesjasonj jack
5  5 jamesjjason, johnjasonjohn , jason-jack sam _ peter

我试图产生的最终结果应该如下所示：

  id                                                         names
1  1                                             john, jack, james
2  2                                     john, james, jason, james
3  3                                            peter, jack, jason
4  4                                          jamesj, asonj,  jack
5  5 jamesj, jason, john, jason, john , jason, jack,  sam ,  peter

我尝试在这里查看这篇文章（R：在输出的每个元素后面插入逗号 https://stackoverflow.com/questions/56103591/r-insert-comma-after-each-element-from-the-output）并尝试了那里提供的答案：

> data_frame$parsed_names = dput(data_frame$names)



  id                                                         names                                                  parsed_names
1  1                                             john, jack, james                                             john, jack, james
2  2                                     john, james, jason, james                                     john, james, jason, james
3  3                                            peter, jack, jason                                            peter, jack, jason
4  4                                          jamesj, asonj,  jack                                          jamesj, asonj,  jack
5  5 jamesj, jason, john, jason, john , jason, jack,  sam ,  peter jamesj, jason, john, jason, john , jason, jack,  sam ,  peter

但这并不符合我想要的。

然后我在这里尝试了这篇文章（在 r 中的某些单词后面的文本字符串中插入逗号 https://stackoverflow.com/questions/54078683/insert-commas-in-text-string-after-certain-words-in-r）并尝试了那里提供的答案：

library(gsubfn)

data_frame$parsed_names = gsubfn("\\w+", as.list(setNames(paste0(patterns, ","), patterns)), 
  format(data_frame$names))

 data_frame
  id                                                         names                                                         parsed_names
1  1                                             john, jack, james     john,, jack,, james,                                            
2  2                                     john, james, jason, james    john,, james,, jason,, james,                                    
3  3                                            peter, jack, jason      peter, jack,, jason,                                           
4  4                                          jamesj, asonj,  jack      jamesj,, asonj,  jack,                                         
5  5 jamesj, jason, john, jason, john , jason, jack,  sam ,  peter jamesj,, jason,, john,, jason,, john, , jason,, jack,,  sam ,  peter

• 有人可以告诉我如何解决这个问题吗？

谢谢你！

这是一个有点临时的答案，但它满足您的要求（没有变化patterns向量）：

library(tidyverse)
patterns <- c("john", "jack", "james", "jamesj", "jason")

data_frame %>% 
  separate_rows(names) %>% 
  mutate(name = str_split(tolower(names), paste0("(?<=(", paste0(patterns, collapse = "|"), "))"))) %>% 
  unnest(name) %>% 
  filter(nzchar(name)) %>% 
  group_by(j = cumsum(!(name == "j"))) %>% 
  summarise(name = paste(name, collapse = ""),
            id = unique(id)) %>% 
  group_by(id) %>% 
  summarise(name = toString(name))

## A tibble: 5 × 2
#     id name                                                     
#  <dbl> <chr>                                                    
#1     1 john, jack, james                                        
#2     2 john, james, jason, james                                
#3     3 peter, jack, jason                                       
#4     4 jamesj, asonj, jack                                      
#5     5 jamesj, jason, john, jason, john, jason, jack, sam, peter

之前的回答：

在模式向量中添加其他可能的名称，并对向量重新排序，以便jamesj优先于james，然后您可以使用str_extract_all.

library(stringr)
library(dplyr)

patterns <- c("john", "jack", "jamesj", "james", "jason", "asonj", "peter", "sam")
patterns <- patterns[order(nchar(patterns), decreasing = T)]

data_frame %>% 
  mutate(names = lapply(str_extract_all(tolower(names), paste(patterns, collapse = "|")), toString))

#  id                                                     names
#1  1                                         john, jack, james
#2  2                                 john, james, jason, james
#3  3                                        peter, jack, jason
#4  4                                       jamesj, asonj, jack
#5  5 jamesj, jason, john, jason, john, jason, jack, sam, peter

data

data_frame <- tribble(
  ~id, ~names,
  1, "johnjack jameS",
  2, "john/james, jasonjames",
  3, "peter_jackjason",
  4, "jamesjasonj jack",
  5, "jamesjjason, johnjasonjohn , jason-jack sam _ peter"
)