How to replace a string using a dictionary containing multiple values for a key in python

Question

I have dictionary with Word and its closest related words.

I want to replace the related words in the string with original word. Currently I am able replace words in th

Answer 1

I think you can replace by new dict with regex from this answer:

d = {'Indian': 'India, Ind, ind.',
 'Restaurant': 'Hotel, Restrant, Hotpot',
 'Pub': 'Bar, Baar, Beer',
 '1888': '188, 188., 18'}

d1 = {r'(?<!\S)'+ k.strip() + r'(?!\S)':k1 for k1, v1 in d.items() for k in v1.split(',')}

df['col'] = df['col'].replace(d1, regex=True)
print (df)
                        col
0   North Indian Restaurant
1   South Indian Restaurant
2        Mexican Restaurant
3       Italian  Restaurant
4                  Cafe Pub
5                 Irish Pub
6               Maggiee Pub
7           Jacky Craft Pub
8               Bristo 1888
9               Bristo 1888
10              Bristo 1888

EDIT (Function for the above code):

def replace_words(d, col):
    d1={r'(?<!\S)'+ k.strip() + r'(?!\S)':k1 for k1, v1 in d.items() for k in v1.split(',')}
    df[col] = df[col].replace(d1, regex=True)
    return df[col]

df['col'] = replace_words(d, 'col')

EDIT1:

If get errors like:

regex error- missing ), unterminated subpattern at position 7

is necessary escape regex values in keys:

import re

def replace_words(d, col):
    d1={r'(?<!\S)'+ re.escape(k.strip()) + r'(?!\S)':k1 for k1, v1 in d.items() for k in v1.split(',')}
    df[col] = df[col].replace(d1, regex=True)
    return df[col]

df['col'] = replace_words(d, 'col')