Скачать или смотреть How to Insert Column in a Dataframe Based on Another Dataframe with Different Shape

Learn how to efficiently add a "Status" column to a DataFrame in Python to indicate the presence of IDs from another DataFrame, even when their shapes differ.
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This video is based on the question https://stackoverflow.com/q/68354676/ asked by the user 'Elthon Daniel Rivas' ( https://stackoverflow.com/u/14847367/ ) and on the answer https://stackoverflow.com/a/68355099/ provided by the user 'ifly6' ( https://stackoverflow.com/u/2741091/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

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Inserting a Column in a DataFrame Based on Another DataFrame with Different Shapes

When working with data in Python, especially using the Pandas library, you may encounter scenarios where you have two DataFrames of different shapes. A common task is to check if elements from one DataFrame exist in another and create a new column to reflect this status. In this guide, we'll explore how to accomplish this efficiently.

The Problem: DataFrames of Different Shapes

Imagine you have two DataFrames:

DF1 with shape (10x3):

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DF2 with shape (5x3):

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

You want to add a Status column to DF1 that indicates whether the ID from DF2 is present in DF1. Your expected result is:

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The Solution: Adding the Status Column

To solve this problem, you will use the isin() method in Pandas, which checks if each ID in DF1 exists in DF2. Here’s how to implement it:

Step 1: Set Up Your DataFrames

First, ensure you have your data in two separate DataFrames:

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Step 2: Create the Status Column

Using the isin() function, you can check if the IDs in DF1 are present in DF2 and map the results to "Y" (Yes) or "N" (No):

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Step 3: View the Result

Once you run the above command, your DF1 will look like this:

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Alternative Method: Using List Comprehensions

If you prefer to use list comprehensions, you can achieve the same result with a slightly different approach:

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This will produce the same output as the previous method.

Conclusion

Adding a column to a DataFrame based on the presence of values from another DataFrame is straightforward in Pandas. By using the isin() method, you can efficiently create a status indicator without getting bogged down by the differences in shapes between DataFrames. This method can be tremendously useful in data analysis and treating datasets more robustly.

Feel free to reach out if you have any questions or encounter issues with your data manipulation tasks! Happy coding!