Pandas – replace/remove everything after a specified string

My data is formatted like this:

These names are too long, and I would like to shorten them. A common theme with all rows of my data is that all the text before the first occurrence of - ( is what I want to preserve for the product name.

How do I remove all the text that comes after - (, including - ( itself?

>Solution :

pandas’s applymap should do it:

import pandas as pd

def shorten(s):
    return s.split(' - (')[0]
    
df = pd.DataFrame(['abc - (123)', 'def - (456)'])
print(df)
df = df.applymap(shorten)
print(df)

Output:

             0
0  abc - (123)
1  def - (456)
     0
0  abc
1  def

If you want to only modify a specific column, e.g. "product_name", use apply instead:

import pandas as pd

def shorten(s):
    return s.split(' - (')[0]
    
df = pd.DataFrame([['abc - (123)'], ['def - (456)']], columns = ['product_name'])
print(df)
df['product_name'] = df['product_name'].apply(shorten)
print(df)