Extracting Substrings from a Pandas DataFrame

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Extracting Substrings from a Pandas DataFrame: A Comprehensive Guide

When working with text data, you may often find yourself needing to extract specific substrings from strings contained within a Pandas DataFrame. This task can be particularly overwhelming when dealing with a large list of concepts. In this guide, we'll explore how to effectively extract substrings from a DataFrame column and overcome common issues you might encounter.

The Problem

Imagine you have a Pandas DataFrame containing two columns: Abstract and Title. Within the Abstract column, you'll find several concepts or keywords that you want to extract. Your goal is to label each record in the DataFrame based on the concepts found within the Abstract text.

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The Solution

Here’s how to implement this solution:

Step 1: Setup Your DataFrame

Assuming you have your concepts defined in a DataFrame named landvoc, and you are prepared to search through the Abstract column, here’s how you might set up your DataFrame:

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Step 2: Create the Regex Pattern

Next, create a regex pattern that reflects the concepts you are searching for:

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Step 3: Extract Substrings

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In this step, findall() will extract all occurrences of the concepts found in the Abstract, and join() will concatenate the results into a single string (separated by commas).

Step 4: View the Output

Finally, you can print your DataFrame to see the results:

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Expected Output:

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Conclusion

Feel free to adapt the above example to your particular use case, ensuring your list of concepts and DataFrame structure aligns with the outlined steps!