Скачать или смотреть Convert EST to CT with Daylight Saving Time in Python Using Pandas

Learn how to parse and convert datetime objects from Eastern Standard Time (EST) to Central Time (CT) with Daylight Saving Time adjustments using Pandas in Python.
---
This video is based on the question https://stackoverflow.com/q/62621797/ asked by the user 'apocalypsis' ( https://stackoverflow.com/u/5870333/ ) and on the answer https://stackoverflow.com/a/62626202/ provided by the user 'FObersteiner' ( https://stackoverflow.com/u/10197418/ ) 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: parse time zone and convert to daylight saving time

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.
---
Understanding the Challenge of Time Zone Conversion

When dealing with datetime objects in Python, especially with the Pandas library, understanding the intricacies of time zones and daylight saving time (DST) is crucial. This guide explores a common problem: converting datetimes from Eastern Standard Time (EST) to Central Time (CT) while correctly accounting for Daylight Saving Time.

You may find yourself with a DataFrame containing datetime entries that do not recognize DST adjustments, leading to potential errors in time calculations. Let’s explore how to accurately perform these conversions step by step.

Problem Overview

Suppose we have a Pandas DataFrame with a Datetime column, all set in Eastern Standard Time without any adjustments for daylight saving. The goal is to convert these datetimes to Central Time, ensuring that we account for DST correctly where necessary.

Here’s an example of how a portion of your data may appear:

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

Solution Breakdown

To resolve this time zone conversion issue, let's break down the solution into two main steps:

Step 1: Localize to UTC

First, we need to inform Python that the data is in EST (UTC-4). By localizing the naive datetime objects to UTC, we need to adjust for the 4-hour difference from UTC.

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

Step 2: Convert to Central Time (CT)

After converting to UTC, the next task is to switch from UTC to Central Time. Central Time is typically UTC-6 but switches to UTC-5 for Daylight Saving Time.

The conversion can be performed as follows:

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

Example Output

The resulting DataFrame would look like this after the conversions:

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

Note: The datetimes might include times that don't exist during the transition (like 2:00 AM on March 10, 2019, during DST).

Conclusion

Converting datetime objects from one time zone to another, especially when considering Daylight Saving Time, can be tricky. However, using the Pandas library provides a straightforward method to handle these changes by localizing to UTC and then converting to the desired time zone.

Next time you're faced with the challenge of time zone reconciling in your Pandas DataFrames, remember this process for accurate results.