To regularize every incidence of the term 'Heb' to "HEB" in pandas df

Question

In a pandas df, trying to regularize every incidence of the term 'Heb' to "HEB"

In a pandas df, trying to regularize every incidence of the term 'Heb' to "HEB" using sidetable, I tried this and it worked. (df['Description'].str.contains('H-E-B', case=False, regex=False), 'HEB'), but then I tried this and it didn't work. (df['Description'].str.contains(['HEB', 'H-E-B', 'Heb online' ], case=False, regex=False), 'HEB'),

Error message reads:"AttributeError: 'list' object has no attribute 'upper'"

Would expect Input:

Description	Amount
HEB	100.00
HEB#123	100.00
HEB online	100.00
H-E-B Gas	100.00
Heb Carwash	100.00

Output:

Description	Amount
HEB	100.00
HEB	100.00
HEB	100.00
HEB	100.00
HEB	100.00

Answer 1

The str.contains() method expects a string and you are giving it a list of strings instead, that's why you are getting the AttributeError.

To replace all descriptions that contain some variation of 'Heb' with 'HEB' you can create a list that contains all expected variations, then loop over the rows of your dataframe and compare the description with your variations:

import pandas as pd

# Sample DataFrame
data = {'Description': ['HEB', 'HEB#123', 'HEB online', 'H-E-B Gas', 'Heb Carwash'],
        'Amount': [100.00, 100.00, 100.00, 100.00, 100.00]}

df = pd.DataFrame(data)
patterns = ['HEB', 'H-E-B', 'Heb' ]


for index, row in df.iterrows():
    for pattern in patterns:
        if pattern in df.at[index, 'Description']:
            df.at[index, 'Description'] = 'HEB'

print(df)