从 df.columns 中的文本中删除非英语单词包含字母和数字

Question

How to removing non English words from text in df.columns words contain letters and numbers

Ex

df['text']

'the interiors nrd studio | happy mothers day ”there is no influence so powerful as that of the mother.” —sara josepha hale... happy mother's day mom & to all the mothers around the world! lots of light natasha
0wet3bxtfl'

'but still missing you every day happy mothers day francis mcclafferty (mccool) 9wlhju7cxf'

from the above 2 rows I need to remove the word '0wet3bxtfl' & '9wlhju7cxf'

Answer 1

The example includes to retain some strings that would not be found in a list of English words ("nrd", "mcclafferty", "mccool") while removing "0wet3bxtfl" and "9wlhju7cxf", so the expected result is probably best achieved by removing any non-whitespace sequences that contain either a letter followed by digit or a digit followed by letter (together with any spaces that follow), without regard to whether words are "English" or not.

The following would do this:

import re

...

filtered = re.sub('[^\s]*(\d[a-zA-Z]|[a-zA-Z]\d)[^\s]* *', '', df['text'])