就所有目的而言，我是一名Python用户，每天使用Pandas库。在正则表达式中，命名捕获组非常有用。例如，相对容易地提取特定单词或短语的出现次数，并在数据框的新列中生成连接字符串。以下是实现此目的的示例：
import numpy as np
import pandas as pd
import re
myDF = pd.DataFrame(['Here is some text',
'We all love TEXT',
'Where is the TXT or txt textfile',
'Words and words',
'Just a few works',
'See the text',
'both words and text'],columns=['origText'])
print("Original dataframe\n------------------")
print(myDF)
# Define regex to find occurrences of 'text' or 'word' as separate named groups
myRegex = """(?P<textOcc>t[e]?xt)|(?P<wordOcc>word)"""
myCompiledRegex = re.compile(myRegex,flags=re.I|re.X)
# Extract all occurrences of 'text' or 'word'
myMatchesDF = myDF['origText'].str.extractall(myCompiledRegex)
print("\nDataframe of matches (with multi-index)\n--------------------")
print(myMatchesDF)
# Collapse resulting multi-index dataframe into single rows with concatenated fields
myConcatMatchesDF = myMatchesDF.groupby(level = 0).agg(lambda x: '///'.join(x.fillna('')))
myConcatMatchesDF = myConcatMatchesDF.replace(to_replace = "^/+|/+$",value = "",regex = True) # Remove '///' at start and end of strings
print("\nCollapsed and concatenated matches\n----------------------------------")
print(myConcatMatchesDF)
myDF = myDF.join(myConcatMatchesDF)
print("\nFinal joined dataframe\n----------------------")
print(myDF)
这将产生以下输出：
Original dataframe
------------------
origText
0 Here is some text
1 We all love TEXT
2 Where is the TXT or txt textfile
3 Words and words
4 Just a few works
5 See the text
6 both words and text
Dataframe of matches (with multi-index)
--------------------
textOcc wordOcc
match
0 0 text NaN
1 0 TEXT NaN
2 0 TXT NaN
1 txt NaN
2 text NaN
3 0 NaN Word
1 NaN word
5 0 text NaN
6 0 NaN word
1 text NaN
Collapsed and concatenated matches
----------------------------------
textOcc wordOcc
0 text
1 TEXT
2 TXT///txt///text
3 Word///word
5 text
6 text word
Final joined dataframe
----------------------
origText textOcc wordOcc
0 Here is some text text
1 We all love TEXT TEXT
2 Where is the TXT or txt textfile TXT///txt///text
3 Words and words Word///word
4 Just a few works NaN NaN
5 See the text text
6 both words and text text word
我已经打印出每个阶段，以便更容易跟踪。
问题是，我是否可以在R中做类似的事情。我搜索了网络，但找不到任何描述命名组使用的内容（尽管我是R新手，可能正在搜索错误的库或描述性术语）。
我已经能够识别那些包含一个或多个匹配项的项目，但我无法看到如何提取特定的匹配项或如何利用命名组。 我迄今为止的代码（使用与上面Python示例相同的数据框和正则表达式）是：
origText = c('Here is some text','We all love TEXT','Where is the TXT or txt textfile','Words and words','Just a few works','See the text','both words and text')
myDF = data.frame(origText)
myRegex = "(?P<textOcc>t[e]?xt)|(?P<wordOcc>word)"
myMatches = grep(myRegex,myDF$origText,perl=TRUE,value=TRUE,ignore.case=TRUE)
myMatches
[1] "Here is some text" "We all love TEXT" "Where is the TXT or txt textfile" "Words and words"
[5] "See the text" "both words and text"
myMatchesRow = grep(myRegex,myDF$origText,perl=TRUE,value=FALSE,ignore.case=TRUE)
myMatchesRow
[1] 1 2 3 4 6 7
正则表达式似乎在工作，正确的行被标识为包含匹配项（即上面示例中除了第5行的所有行）。然而，我的问题是，我能否产生类似于Python生成的输出，其中特定的匹配项被提取并列在数据帧中以使用正则表达式中包含的组名命名的新列中吗？