CODEWITHSUNDEEP
pythonpandasdataframe
R_Developer
R_Developer

Reputation: 59

How to replace a certain word in a dataframe only if it's preceded by a number?

I'm trying to search in a dataframe about certain words listed in dictionary values if any exist it will replaced with the key of values.

units_dic= {'grams':['g','Grams'],
                'kg'   :['kilogram','kilograms']}

the problem is some units abbreviations are letters so it will replace all letters also, I want to do the replacement only if it preceded by a number to make sure it's a unit.

Dataframe

    Id | test 
    ---------
    1  |'A small paperclip has a mass of about 111 g'
    2  |'1 kilogram =1000 g'
    3  |'g is the 7th letter in the ISO basic Latin alphabet'

Replacement Loop 

  x = df.copy()
  for k in units_dic:
      for i in range(len(x['test'])):
          for w in units_dic[k]:
              x['test'][i] = str(x['test'][i]).replace(str(w), str(k))

The Output

    Id | test 
    ---------
    1  |'A small paperclip has a mass of about 111 grams'
    2  |'1 kg =1000 grams'
    3  |'grams is the 7th letter in the ISO basic Latin alphabet'

Upvotes: 2

Views: 149

Answers (3)

Erfan
Erfan

Reputation: 42906

We can make use of the lookbehind feature of regex here, which we can specify that it needs to be preceded by a number and optional a whitespace:

for k, v in units_dic.items():
    df['test'] = df['test'].str.replace(f"(?<=[0-9])\s*({'|'.join(v)})\b", f' {k}')

print(df)
   Id                                               test
0   1  'A small paperclip has a mass of about 111 grams'
1   2                                 '1 kg =1000 grams'
2   3  'g is the 7th letter in the ISO basic Latin al...

Explanation
First we use raw + fstring: fr'sometext'

Regular expression:

  • ?<=[0-9] = preceded by a number
  • \s* is a whitespace
  • "|".join(v) gives us the values in your dictionary back delimited by a | which is the or operator in regex

Upvotes: 0

user3483203
user3483203

Reputation: 51155

Regular expressions to the rescue along with flipping the dictionary.

import re

d = {i: k for k, v in units_dic.items() for i in v}
u = r'|'.join(d)
v = fr'(\d+\s?)\b({u})\b'

df.assign(test=[re.sub(v, lambda x: x.group(1) + d[x.group(2)], el) for el in df.test])


   Id                                               test
0   1    A small paperclip has a mass of about 111 grams
1   2                                   1 kg =1000 grams
2   3  g is the 7th letter in the ISO basic Latin alp...

Upvotes: 1

Rajat Jain
Rajat Jain

Reputation: 2032

Try:

for key, val in units_dic.items(): 
    df['test'] = df['test'].replace("\d+[ ]*" + "|".join(val) , key , regex=True)

Upvotes: 1

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