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Learn how to efficiently calculate the difference in months between two dates in Python using the Polars library, replicating Excel's behavior.
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How to Compute the Difference of Months Between Two Dates Using Python and Polars

When working with dates in data analysis, it's common to encounter the need to calculate the difference between two dates. While many tools and libraries can produce differences in days, obtaining the difference in months can be a bit trickier. This guide will guide you through how to achieve this in Python using the powerful Polars library.

The Problem Statement

Suppose you have two date columns in your DataFrame, dt_start and dt_end. You want to subtract these two columns and find the difference in months instead of the default difference in days provided by most date processing functions. You may have already tried various methods, but they either produce incorrect results or provide the difference in days rather than months.

Here's a snippet of the DataFrame in question:

[[See Video to Reveal this Text or Code Snippet]]

Initial Attempts

Initially, you might try the straightforward subtraction like this:

[[See Video to Reveal this Text or Code Snippet]]

However, this produces a difference in duration (days).

Subsequent attempts using transformations based on year and month calculations have also yielded inconsistent or incorrect outputs:

[[See Video to Reveal this Text or Code Snippet]]

The output does not match your expectations or those from Excel.

The Solution

To correctly calculate the difference in months, we need to build upon the earlier attempts but refine them. The essential part of the solution is to consider the day component of the dates and adjust for it. Here's how:

The Correct Formula

The correct code snippet should look like this, ensuring that we account for days:

[[See Video to Reveal this Text or Code Snippet]]

Breakdown of the Code

Calculate Year Difference:

Subtract the years from each other and multiply by 12 to get the total months.

Calculate Month Difference:

Subtract the month values directly.

Adjust for Days:

If the day of dt_end is less than the day of dt_start, we decrement the total by one month. This adjustment ensures that we only count full months.

Example Output

Using the correct formula, you now obtain a DataFrame that reflects the month differences accurately. For instance:

[[See Video to Reveal this Text or Code Snippet]]

Conclusion

Calculating the difference in months between two dates in Polars requires careful consideration of year, month, and day components. By following the structured approach outlined in this post, you should now be able to replicate the months difference calculation akin to Excel's, arming you with the tools needed for effective date manipulation in your data analysis projects.

With the above solution, you can confidently work with date calculations in Polars and produce results that meet your analytical needs.