R 在多个数据框中搜索包含的特定文本，并在新列中返回这些值（多次出现）

在另一个数据框的列（文本体）中搜索一个数据框中的多个特定单词，然后将这些值拉到一个新列中，是否需要一些帮助

进一步解释：

• 首先，我有一个数据框架，包括14个国家的大量文本摘要列表
• 其次，我有第二个数据框架，其中包含所有行政级别（lvl_2）的名称，如省、村等
• 基本上，我想从大型摘要中提取提及这些特定adm2省/村名称的内容，并创建一个新的列，其中每个词都以较长的轴为中心

下面是一些示例数据，您可以使用它们来重新创建我的问题，其中包含两个数据框：（1）

test\u admin

用于我要搜索的管理级别列表，以及（2）

test\u dataset$Summary

，这是我要运行搜索的列。（您可以忽略其他_变量的值，这些变量在真实数据集中填充了大量值）

我尝试了一些mutate和grepl函数，但没有成功。我发现的其他示例似乎只针对精确值或单个搜索进行了这项工作。谢谢你的帮助

---

#首选tidyverse解决方案这里有一种方法：

library(tidyverse)

map_df(seq(nrow(test_dataset)), function(i) {
  inds <- str_detect(test_dataset$Summary[i], test_admin$adm1_name) | 
             str_detect(test_dataset$Summary[i], test_admin$adm2_name)
  if(any(inds)) tibble(test_dataset[i, ], Locations = test_admin$adm2_name[inds])
    else tibble(test_dataset[i, ], Locations = NA)
})

#  Summary                                 Other_Variable_1 Other_Variable_2 Locations      
#   <chr>                                              <int>            <int> <chr>          
# 1 In Cox's Bazar, this and that happened.                1                1 NA             
# 2 In Yangon, something else happened                     2                2 NA             
# 3 In Central Karachi, this happened                      3                3 Central Karachi
# 4 In Sindh, this happened                                4                4 Central Karachi
# 5 In Sindh, this happened                                4                4 Dadu           
# 6 In Sindh, this happened                                4                4 East Karachi   
# 7 In Sindh, this happened                                4                4 Ghotki         
# 8 In Sindh, this happened                                4                4 Sujawal        
# 9 In Sindh, this happened                                4                4 Sukkur         
#10 In Dadu AND East Karachi, this happened                5                5 Dadu           
#11 In Dadu AND East Karachi, this happened                5                5 East Karachi   

库（tidyverse）
map_df（序列（nrow（测试数据集）），函数（i）{
非常好，非常感谢！它工作得非常好。
                                   Summary Other_Variable_1 Other_Variable_2       Locations
1  In Cox's Bazar, this and that happened.                1                1            <NA>
2       In Yangon, something else happened                2                2            <NA>
3        In Central Karachi, this happened                3                3 Central Karachi
4                  In Sindh, this happened                4                4 Central Karachi
5                  In Sindh, this happened                4                4            Dadu
6                  In Sindh, this happened                4                4    East Karachi
7                  In Sindh, this happened                4                4          Ghotki
8                  In Sindh, this happened                4                4         Sujawal
9                  In Sindh, this happened                4                4          Sukkur
10 In Dadu AND East Karachi, this happened                5                5            Dadu
11 In Dadu AND East Karachi, this happened                5                5    East Karachi

library(tidyverse)

map_df(seq(nrow(test_dataset)), function(i) {
  inds <- str_detect(test_dataset$Summary[i], test_admin$adm1_name) | 
             str_detect(test_dataset$Summary[i], test_admin$adm2_name)
  if(any(inds)) tibble(test_dataset[i, ], Locations = test_admin$adm2_name[inds])
    else tibble(test_dataset[i, ], Locations = NA)
})

#  Summary                                 Other_Variable_1 Other_Variable_2 Locations      
#   <chr>                                              <int>            <int> <chr>          
# 1 In Cox's Bazar, this and that happened.                1                1 NA             
# 2 In Yangon, something else happened                     2                2 NA             
# 3 In Central Karachi, this happened                      3                3 Central Karachi
# 4 In Sindh, this happened                                4                4 Central Karachi
# 5 In Sindh, this happened                                4                4 Dadu           
# 6 In Sindh, this happened                                4                4 East Karachi   
# 7 In Sindh, this happened                                4                4 Ghotki         
# 8 In Sindh, this happened                                4                4 Sujawal        
# 9 In Sindh, this happened                                4                4 Sukkur         
#10 In Dadu AND East Karachi, this happened                5                5 Dadu           
#11 In Dadu AND East Karachi, this happened                5                5 East Karachi