re.sub erroring with “Expected string or bytes-like object”

I have read multiple posts regarding this error, but I still can’t figure it out. When I try to loop through my function:

def fix_Plan(location):
    letters_only = re.sub("[^a-zA-Z]",  # Search for all non-letters
                          " ",          # Replace all non-letters with spaces
                          location)     # Column and row to search    

    words = letters_only.lower().split()     
    stops = set(stopwords.words("english"))      
    meaningful_words = [w for w in words if not w in stops]      
    return (" ".join(meaningful_words))    

col_Plan = fix_Plan(train["Plan"][0])    
num_responses = train["Plan"].size    
clean_Plan_responses = []

for i in range(0,num_responses):
    clean_Plan_responses.append(fix_Plan(train["Plan"][i]))

Here is the error:

Traceback (most recent call last):
  File "C:/Users/xxxxx/PycharmProjects/tronc/tronc2.py", line 48, in <module>
    clean_Plan_responses.append(fix_Plan(train["Plan"][i]))
  File "C:/Users/xxxxx/PycharmProjects/tronc/tronc2.py", line 22, in fix_Plan
    location)  # Column and row to search
  File "C:UsersxxxxxAppDataLocalProgramsPythonPython36libre.py", line 191, in sub
    return _compile(pattern, flags).sub(repl, string, count)
TypeError: expected string or bytes-like object

3 Answers

As you stated in the comments, some of the values appeared to be floats, not strings. You will need to change it to strings before passing it to re.sub. The simplest way is to change location to str(location) when using re.sub. It wouldn’t hurt to do it anyways even if it’s already a str.

letters_only = re.sub("[^a-zA-Z]",  # Search for all non-letters
                          " ",          # Replace all non-letters with spaces
                          str(location))

The simplest solution is to apply Python str function to the column you are trying to loop through.

If you are using pandas, this can be implemented as:

dataframe['column_name']=dataframe['column_name'].apply(str)

I suppose better would be to use re.match() function. here is an example which may help you.

import re
import nltk
from nltk.tokenize import word_tokenize
nltk.download('punkt')
sentences = word_tokenize("I love to learn NLP n 'a :(")
#for i in range(len(sentences)):
sentences = [word.lower() for word in sentences if re.match('^[a-zA-Z]+', word)]  
sentences

Leave a Reply

Your email address will not be published. Required fields are marked *