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How Can I Efficiently Find Strings Containing Specific Substrings in a Pandas Series?

Dec 06, 2024 am 11:39 AM

How Can I Efficiently Find Strings Containing Specific Substrings in a Pandas Series?

Testing String Substrings in Pandas

In pandas, you may encounter scenarios where you need to determine if a string column contains one of several substrings. This can be achieved using the isin() and str.contains() functions, but a more efficient approach is available.

To find all strings containing any of a list of substrings, you can utilize the regular expression pipe character (|) within str.contains(). For instance, given a series s = ['cat','hat','dog','fog','pet'] and the desired substrings ['og', 'at'], you can execute the following code:

import pandas as pd

searchfor = ['og', 'at']
result = s[s.str.contains('|'.join(searchfor))]
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This operation will create a series with all elements of s that match any of the substrings in searchfor, excluding pet.

It's important to note that special characters with specific meanings in regular expressions, such as $ and ^, should be escaped using re.escape(). This ensures they are treated as literal characters during matching.

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