A Lesser-Known Feature of the Merge Method in Pandas

When merging two DataFrames, one may want to perform some checks to ensure the integrity of the merge operation.

For instance, if one of the two DataFrames has repeated keys, it will result in duplicated rows.

But this may not be desired.

The good thing is that you can check this with Pandas.

Pandas' merge() method provides a validate parameter, which checks if the merge is of a specified type or not.

• “one_to_one”: Merge keys should be unique in both DataFrames.

• “one_to_many”: Merge keys should be unique in the left DataFrame.

• “many_to_one”: Merge keys should be unique in the right DataFrame.

• “many_to_many”: Merge keys may or may not be unique in both DataFrames.

Pandas raises a Merge Error if the merge operation does not conform to the specified type.

This helps you prevent errors that can often go unnoticed.

Over to you: What are some other hidden treasures you know of in Pandas? Let me know :)

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Find the code for my tips here: GitHub.

I like to explore, experiment and write about data science concepts and tools. You can read my articles on Medium. Also, you can connect with me on LinkedIn and Twitter.