CODEWITHSUNDEEP
pythonpandasregexnlpabbreviation
Adelore Similoluwa Gloria
Adelore Similoluwa Gloria

Reputation: 45

Identify abbreviations in a string column

Given the following data frame for instance (mind you the original data for this column is a dtype('0'))

df = pd.DataFrame({'product_description': ["CUTLERY HVY DUTY FORKS", "XYZ DISP LQD SOAP", "ABCD FOOD STRG CNTNR"]})

How can I effectively identify and separate the abbreviations and produce a result like

product_description            abbreviations
0  CUTLERY HVY DUTY FORKS        [HVY]

1  XYZ DISP LQD SOAP             [XYZ,DISP,LQD]

2  ABCD FOOD STRG CNTNR          [ABCD,STRG,CNTNR]

So i convert the abbreviations into full words.

i have tried this:

import pandas as pd
import re

df = pd.DataFrame({'product_description': ["CUTLERY HVY DUTY FORKS", "XYZ DISP LQD SOAP", "ABCD FOOD STRG CNTNR"]})

def extract_abbreviations(description):
    abbreviation_pattern = r'\b[A-Z]{2,}(?![a-z])'  # Updated regular expression pattern to match abbreviations
    abbreviations = re.findall(abbreviation_pattern, description)
    return abbreviations

df['abbreviations'] = df['product_description'].apply(extract_abbreviations)
print(df)

but this is what i get :

product_description            abbreviations
0  CUTLERY HVY DUTY FORKS        [CUTLERY,HVY,DUTY,FORKS]

1  XYZ DISP LQD SOAP             [XYZ,DISP,LQD,SOAP]

2  ABCD FOOD STRG CNTNR          [ABCD,FOOD,STRG,CNTNR]

Your help is much appreciated. Thank you

Upvotes: 0

Views: 99

Answers (1)

mad_
mad_

Reputation: 8273

Given you have a list of abb ['XYZ', 'DISP', 'LQD', 'ABCD', 'STRG', 'CNTNR', 'HVY', 'SOAP'] You should be able the apply the below logic to obtain the desired result

abb=['XYZ', 'DISP', 'LQD', 'ABCD', 'STRG', 'CNTNR', 'HVY', 'SOAP']
def return_abb(row):
    return list(set(row.split(" ")) & set(abb))
df['abbreviations']=df['product_description'].apply(return_abb)

Upvotes: 0

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