Скачать или смотреть How to Change Column Headers in a Pandas DataFrame

Learn how to effectively change column headers and restructure your Pandas DataFrame for better readability and analysis. This step-by-step guide is perfect for beginners!
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Changing Column Headers in a Pandas DataFrame: A Simple Guide

Are you working with a Pandas DataFrame and need to change its column headers? You’re not alone! Many data analysts and Python programmers face this common issue, especially when dealing with financial data downloaded from APIs such as Yahoo Finance. In this post, we’ll walk you through how to effectively change column headers in a DataFrame to make it more readable and organized.

The Problem

Let’s say you’ve used Yahoo Finance to download stock prices for a list of companies, and you obtain a DataFrame that looks something like this:

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

This leads to a DataFrame that appears as follows:

DateABEV3.SAALPA4.SAAMER3.SA2023-01-0614.2413.9110.13Now, you want to transpose this table so that the company codes become the index (rows) and the prices become the column. However, the result might be awkward, with incorrect header titles like Date above the company codes and 2023-01-06 above the prices.

The Desired Outcome

You want your DataFrame to resemble the following format:

CodeCloseABEV3.SA14.24ALPA4.SA13.91AMER3.SA10.13The Solution

Changing the column headers in a DataFrame is simpler than it sounds! Here’s how you can achieve the desired outcome in just a few steps.

Step 1: Transpose the DataFrame

First, you need to transpose your DataFrame close to switch its rows and columns. You can do this by calling .T on the DataFrame:

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

Step 2: Rename the Index and Columns

After transposing, you can rename the index (which will now represent your company codes) and the column header for the close prices. You can do this with the rename_axis and rename functions:

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

Final Code Example

Putting it all together, your complete code will look like this:

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

Conclusion

By following these straightforward steps, you can quickly change column headers in a Pandas DataFrame to make your data cleaner and more useful for analysis. Don’t hesitate to customize the names to fit your project requirements! With just a little bit of Pandas magic, your DataFrame can be restructured into a more interpretable format that enhances clarity and efficiency.

We hope this guide has been helpful in addressing your question about changing column headers in a DataFrame. Happy coding!