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In this tutorial, we will explore how to union (concatenate) multiple DataFrames using the Python Pandas library. Unioning DataFrames is a common operation when working with tabular data, especially when you have data split across multiple sources or files. We'll cover different scenarios and provide code examples for each.
Make sure you have Python and Pandas installed on your system. If you don't have Pandas installed, you can install it using:
In this scenario, we have multiple DataFrames with the same columns, and we want to stack them vertically.
In this scenario, we have multiple DataFrames with the same rows, and we want to concatenate them horizontally.
If the DataFrames have different columns, Pandas will fill in missing values with NaN during the union.
If DataFrames have common columns but different rows, you can still union them.
Now you have a basic understanding of how to union multiple DataFrames in various scenarios using Pandas. Adjust the code examples based on your specific use case and data structures.
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