Скачать или смотреть How to Calculate the Difference in Days Between Dates in a Pandas DataFrame

Learn how to easily add a new column in a Pandas DataFrame that calculates the difference in days between today's date and a specified date column. Perfect for tracking date differences!
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This video is based on the question https://stackoverflow.com/q/74080757/ asked by the user 'Giganoob' ( https://stackoverflow.com/u/3365188/ ) and on the answer https://stackoverflow.com/a/74080815/ provided by the user 'Code Different' ( https://stackoverflow.com/u/2538939/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

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Introduction

Managing dates within a DataFrame can often be a challenge, especially when you need to calculate the difference between today's date and a list of dates. For instance, if you have a column filled with timestamps and want to know how many days have passed since each date, you may wonder how to achieve this with Python's Pandas library.

In this guide, we will address this problem and guide you through the process of adding a new column that represents the difference in days between today’s date and a given date column called LastUpdated.

Understanding the Problem

Let's say we have a DataFrame structured like this:

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

Your goal is to create a new column, say Diff, that calculates how many days have passed between the current date and each date listed in the LastUpdated column.

Step-by-Step Solution

Step 1: Ensure the Date Format

First, you need to make sure that the LastUpdated column is in the correct format. More specifically, it should be of type datetime64. If it's not already in this format, you can convert it using the pd.to_datetime() function.

Here’s what the code looks like:

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

Step 2: Calculate the Difference

Next, you can calculate the difference between today’s date and the dates listed in your LastUpdated column. To do this, subtract the LastUpdated dates from the current date and divide the result by a Timedelta object to convert the difference into days.

The following code does just that:

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

Optional: Ignoring the Time Component

If you prefer to strip out the time component and only account for the date, you can normalize the timestamps before performing the calculation. This can be done as follows:

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

Conclusion

With the above steps, you can easily add a new column to your DataFrame that calculates the difference in days between today and the dates in the LastUpdated column. This solution uses core features of the Pandas library, making it straightforward and efficient.

By keeping your date format in check and utilizing Timedelta, you can perform various date calculations to suit your needs, helping to enhance your data analysis further. Happy coding!