Скачать или смотреть How to Concat Two DataFrames in Pandas on Matching Columns and Preserve Non-Matching Columns

Discover how to merge two DataFrames in Pandas on matching columns, ensuring that all data is preserved and non-matching entries are filled with NaN values.
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How to Concat Two DataFrames in Pandas on Matching Columns and Preserve Non-Matching Columns

When working with data analysis in Python using Pandas, you often find yourself needing to combine different DataFrames for a comprehensive review of your data. A common scenario is merging two DataFrames based on specific matching columns while ensuring that any non-matching entries are accounted for, typically filled with NaN values. This post walks you through the process step by step.

The Problem

Imagine you have two DataFrames, each containing information about various items, but not all items are in both DataFrames. Let's illustrate this with an example.

Example DataFrames

Consider the following two DataFrames:

DataFrame 1:

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

DataFrame 2:

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

You want to merge these DataFrames based on the CD and REGN columns, while still preserving all entries from the first DataFrame, which may not have a corresponding entry in the second DataFrame.

The desired output should look like this:

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

The Solution

To achieve this, we will use the pd.merge() function from the Pandas library. Below is a detailed guide on how to perform this operation.

Step-by-Step Instructions

Import Pandas

Make sure you have the Pandas library installed and import it into your Python script:

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

Create the DataFrames

Define the two DataFrames as outlined earlier:

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

Merge the DataFrames

Use the pd.merge() function to join the two DataFrames based on the CD and REGN columns. Here, we specify the how parameter as "left" to retain all rows from the first DataFrame:

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

View the Output

You can display the merged DataFrame to see the results:

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

Expected Output

When you run the above code snippets, the output should resemble:

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

Conclusion

Merging DataFrames on matching columns while retaining non-matching entries is a powerful feature of Pandas that enhances our ability to manipulate data effectively. By following the steps outlined in this guide, you can confidently manage and analyze your datasets, ensuring that no valuable information is lost in the process.

Pandas makes it easy to handle complex data merging tasks — happy coding!