Скачать или смотреть Transform Weekly Data to Daily Data Using Python and Pandas

Learn how to efficiently `transform weekly data into daily data` using Python. This guide provides a step-by-step approach for working with pandas DataFrames.
---
This video is based on the question https://stackoverflow.com/q/64063238/ asked by the user 'Asmir' ( https://stackoverflow.com/u/13525679/ ) and on the answer https://stackoverflow.com/a/64063306/ provided by the user 'jezrael' ( https://stackoverflow.com/u/2901002/ ) 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 transform weekly data to daily for specific columns using Python

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.
---
Transform Weekly Data to Daily Data Using Python and Pandas

As a beginner in Python programming, tackling data transformations might seem daunting at first. However, with the right tools and guidance, you can navigate through and manipulate your datasets with ease. This post will specifically address how to transform weekly data into daily data using the powerful Python library, Pandas.

The Problem

You have a dataset consisting of multiple columns, with some of them containing data on a weekly basis only. Your goal is to convert these weekly values into daily values by distributing the weekly total equally across each day of that particular week. For example, if a column has a value of 14 for a given week, you would want each day that week to reflect a value of 2 (i.e., 14 divided by 7).

Input Dataset Example

Here's how your input dataset might look:

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

Desired Output Dataset

The transformation should yield a dataset that looks like this:

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

The Solution

To solve the problem of converting weekly data to daily data, you can follow these steps using Pandas:

Step 1: Import Required Libraries

First, ensure you have the Pandas library installed. You can install it via pip if you haven’t done so already:

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

Then, you can start by importing it in your script:

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

Step 2: Load Your Dataset

You might import your dataset from a CSV file or create it directly within your script. Here’s an example of creating it directly:

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

Step 3: Transform Weekly Data

Now, we’ll identify the columns that contain missing values and have weekly data. We'll forward-fill these weekly data points and divide them by 7 to allocate the values to each day of the week.

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

Step 4: Output the Result

After executing the code snippet above, your DataFrame df will be transformed, just like the desired output discussed earlier.

Conclusion

Transforming weekly data into daily averages may seem complex at first, but with the Pandas library, you can handle this task efficiently. By using the methods outlined above, you can ensure your datasets are ready for further analysis and insights.

This guide provides a clear, manageable walkthrough for beginners seeking to enhance their data manipulation skills in Python. If you have any questions or comments, feel free to share them below!