Regex named groups in R

For all intents and purposes, I am a Python user and use the Pandas library on a daily basis. The named capture groups in regex is extremely useful. So, for example, it is relatively trivial to extract occurrences of specific words or phrases and to produce concatenated strings of the results in new columns of a dataframe. An example of how this might be achieved is given below:

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)

This produces the following output:

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

I've printed each stage to try to make it easy to follow.

The question is, can I do something similar in R. I've searched the web but can't find anything that describes the use of named groups (although I'm an R-newcomer and so might be searching for the wrong libraries or descriptive terms).

I've been able to identify those items that contain one or more matches but I cannot see how to extract specific matches or how to make use of the named groups. The code I have so far (using the same dataframe and regex as in the Python example above) is:

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

The regex seems to be working and the correct rows are identified as containing a match (i.e. all except row 5 in the above example). However, my question is, can I produce an output that is similar to that produced by Python where the specific matches are extracted and listed in new columns in the dataframe that are named using the group names contained in the regex?

Base R does capture the information about the names but it doesn't have a good helper to extract them by name. I write a wrapper to help called regcapturedmatches. You can use it with

myRegex = "(?<textOcc>t[e]?xt)|(?<wordOcc>word)"
m<-regexpr(myRegex, origText, perl=T, ignore.case=T)
regcapturedmatches(origText,m)

Which returns

     textOcc wordOcc
[1,] "text"  ""     
[2,] "TEXT"  ""     
[3,] "TXT"   ""     
[4,] ""      "Word" 
[5,] ""      ""     
[6,] "text"  ""     
[7,] ""      "word"