How Can I Efficiently Check for Multiple Substring Inclusions in Pandas?

Testing String Substring Inclusion Using Pandas

In pandas, the need arises to determine whether a string contains any of the substrings present in a list. To address this, a combination of df.isin() and df[col].str.contains() could be employed. However, this approach is considered cumbersome.

An Improved Solution

A more refined approach involves leveraging the | (pipe) character in regular expressions to match multiple substrings simultaneously. This technique entails concatenating the substrings in the list using '|'.join():

searchfor = ['og', 'at']
s[s.str.contains('|'.join(searchfor))]

This approach efficiently identifies strings that match any of the specified substrings, resulting in a refined outcome:

0    cat
1    hat
2    dog
3    fog
dtype: object

Handling Special Characters

It is important to exercise caution when dealing with substrings containing special characters such as $ and ^ that have specific meanings in regular expressions. To ensure literal matching, utilize re.escape() to escape these characters:

import re
matches = ['$money', 'x^y']
safe_matches = [re.escape(m) for m in matches]

s[s.str.contains('|'.join(safe_matches))]

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