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Discover how to effectively split a column in Pandas by specific words, retaining the delimiters in your DataFrame.
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Splitting a Pandas Column by Specific Words While Retaining Delimiters

When working with data in Python using Pandas, you might encounter situations where you need to split a column based on specific strings or delimiters. However, you may also want to keep these delimiters in your resulting DataFrame, which can sometimes be a challenge. In this guide, we'll explore a practical solution to achieve this efficiently.

The Problem

Imagine you have a column containing strings where you want to split the data by specific keywords, such as "and" and "or". Here's an example of such data found in a CSV file (test.csv):

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When trying to split the column using the typical str.split() function in Pandas, you might get unexpected results. For example, if you run the following code:

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This will produce the following output:

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As you can see, the delimiter "and" and "or" are not included in the resulting columns, which is not the desired outcome.

The Desired Result

What we really want is to maintain those delimiters in the output. Here's what we aim for:

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The Solution: Using Regex with Lookbehind

To achieve this, we can use a more advanced approach involving regular expressions (regex). Specifically, we'll take advantage of lookbehind assertions to split the strings while keeping the delimiters. Here’s how to do this step-by-step:

Step 1: Import Required Libraries

First, ensure that you have Pandas imported so we can work with DataFrames.

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Step 2: Prepare Your Data

Next, create your DataFrame. You might be reading data from a CSV file, but for the sake of simplicity, we’ll define it directly as follows:

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Step 3: Split the Column Using Regex

Now, instead of using str.split(), utilize str.split() with a regex pattern that employs lookbehind. Here’s the line of code you should add:

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Explanation of the Regex

(?<=and): This is a lookbehind assertion which means "split after 'and' but include 'and' in the result".

(?<=or): Similarly, this means "split after 'or' but include 'or' in the result".

Final Output

Finally, when you print the DataFrame, you will see the desired output:

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This will yield:

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Conclusion

With the regex approach, you can easily split a Pandas column by specific delimiters while keeping those delimiters in the resulting DataFrame. This solution is not only efficient but also enhances your ability to manipulate and analyze data as needed. Feel free to experiment with different patterns to cater to your data-processing requirements. Happy coding!