Calculating Duration in Minutes Between Two Datetime Values Using Pandas
Автор: vlogize
Загружено: 2025-05-28
Просмотров: 1
Описание:
Learn how to easily calculate the duration in `minutes` between two datetime values in a Pandas DataFrame with this step-by-step guide.
---
This video is based on the question https://stackoverflow.com/q/66752174/ asked by the user 'mike_duaud' ( https://stackoverflow.com/u/15266724/ ) and on the answer https://stackoverflow.com/a/66752283/ provided by the user 'anon01' ( https://stackoverflow.com/u/5032941/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.
Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: How to calculate duration in minutes between two datetimes values
Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l...
The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license.
If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
---
How to Calculate Duration in Minutes Between Two Datetime Values using Pandas
In the realm of data analysis, working with time can often lead to challenges, especially when it comes to calculating durations between two datetime values. If you're utilizing Python's Pandas library, you may find yourself needing to determine this time difference to create insightful metrics or reports. In this guide, we'll explore how to calculate the duration in minutes between two datetime columns in your DataFrame. Let’s dive into the problem and its solution!
The Problem
Imagine you have a DataFrame containing Start date and End date columns, and you want to calculate the difference between these two datetime values in minutes.
Here’s a snippet of what your DataFrame might look like:
[[See Video to Reveal this Text or Code Snippet]]
When you attempt to calculate the difference using the following code:
[[See Video to Reveal this Text or Code Snippet]]
You might encounter results that aren't in the minutes you expect, such as:
[[See Video to Reveal this Text or Code Snippet]]
It's clear that more needs to be done to get the duration in a user-friendly format. So, how do you convert these values into a duration measured in minutes?
The Solution
To successfully compute the difference in minutes between the two datetime values, you’ll want to leverage the pd.to_timedelta method. Here’s how you can do it step by step:
Step 1: Convert Start and End Dates to Datetime
First, ensure that both Start date and End date columns are correctly formatted as datetime objects. This is facilitated by the pd.to_datetime() function.
Step 2: Calculate the Time Difference with pd.to_timedelta
Next, you will find the difference between the two dates, but this time you'll encapsulate that difference using to_timedelta to ensure it calculates the time span correctly.
Step 3: Convert the Difference to Minutes
Finally, extract the number of seconds from the timedelta object and divide by 60 to convert it into minutes.
Here’s how the complete code should look:
[[See Video to Reveal this Text or Code Snippet]]
Explanation of the Code
pd.to_timedelta(...) converts the difference between End date and Start date into a proper timedifference format.
.dt.total_seconds() retrieves the total number of seconds from that timedifference.
Dividing by 60 allows us to convert the seconds into minutes, giving you the exact duration in the desired unit.
Conclusion
By following these steps, you will successfully transform your datetime difference into easily understandable durations measured in minutes. This allows for more intuitive data analysis and sharing insights. Whether you're working with schedules, events, or trip durations, knowing how to handle datetime arithmetic in Pandas can significantly enhance your analysis capabilities. Happy coding!
Повторяем попытку...

Доступные форматы для скачивания:
Скачать видео
-
Информация по загрузке: