Edward Edward - 2 months ago 117
Python Question

TypeError: expected string or bytes-like object pandas variable

I have dataset like this

import pandas as pd
df = pd.DataFrame({'word': ['abs e learning ', 'abs e-learning', 'abs e&learning', 'abs elearning']})


I want to get

word
0 abs elearning
1 abs elearning
2 abs elearning
3 abs elearning


I do as bellow

re_map = {r'\be learning\b': 'elearning', r'\be-learning\b': 'elearning', r'\be&learning\b': 'elearning'}
import re
for r, map in re_map.items():
df['word'] = re.sub(r, map, df['word'])


and error

TypeError Traceback (most recent call last)
<ipython-input-42-fbf00d9a0cba> in <module>()
3 s = df['word']
4 for r, map in re_map.items():
----> 5 df['word'] = re.sub(r, map, df['word'])

C:\Users\Edward\Anaconda3\lib\re.py in sub(pattern, repl, string, count, flags)
180 a callable, it's passed the match object and must return
181 a replacement string to be used."""
--> 182 return _compile(pattern, flags).sub(repl, string, count)
183
184 def subn(pattern, repl, string, count=0, flags=0):

TypeError: expected string or bytes-like object


I can apply str like this

for r, map in re_map.items():
df['word'] = re.sub(r, map, str(df['word']))


There is no mistake but i cann't get pd.dataFrame as i wish

word
0 0 0 0 abs elearning \n1 abs elearning\...\n1 0 0 abs elearning \n1 abs elearning\...\n2 0 0 abs elearning \n1 abs ele...
1 0 0 0 abs elearning \n1 abs elearning\...\n1 0 0 abs elearning \n1 abs elearning\...\n2 0 0 abs elearning \n1 abs ele...
2 0 0 0 abs elearning \n1 abs elearning\...\n1 0 0 abs elearning \n1 abs elearning\...\n2 0 0 abs elearning \n1 abs ele...
3 0 0 0 abs elearning \n1 abs elearning\...\n1 0 0 abs elearning \n1 abs elearning\...\n2 0 0 abs elearning \n1 abs ele...


how to improve it?

Answer

df['word'] is a list. Converting to string just destroys your list.

You need to apply regex on each member:

for r, map in re_map.items():
    df['word'] = [re.sub(r, map, e) for e in df['word']]:

classical alternate method without list comprehension:

 for r, map in re_map.items():
     d = df['word']
     for i,e in enumerate(d):
         d[i] = re.sub(r, map, e)