Pandas Merging 101

Michael Zippo

👻 Check our latest review to choose the best laptop for Machine Learning engineers and Deep learning tasks!

How can I perform a (INNER| (LEFT|RIGHT|FULL) OUTER) JOIN with pandas?
How do I add NaNs for missing rows after a merge?
How do I get rid of NaNs after merging?
Can I merge on the index?
How do I merge multiple DataFrames?
Cross join with pandas
merge? join? concat? update? Who? What? Why?!

... and more. I"ve seen these recurring questions asking about various facets of the pandas merge functionality. Most of the information regarding merge and its various use cases today is fragmented across dozens of badly worded, unsearchable posts. The aim here is to collate some of the more important points for posterity.

This Q&A is meant to be the next installment in a series of helpful user guides on common pandas idioms (see this post on pivoting, and this post on concatenation, which I will be touching on, later).

Please note that this post is not meant to be a replacement for the documentation, so please read that as well! Some of the examples are taken from there.

_{For ease of access.}

Merging basics - basic types of joins (read this first)
Index-based joins
Generalizing to multiple DataFrames
Cross join

👻 Read also: what is the best laptop for engineering students?

We hope this article has helped you to resolve the problem. Apart from Pandas Merging 101, check other code Python module-related topics.

Want to excel in Python? See our review of the best Python online courses 2023. If you are interested in Data Science, check also how to learn programming in R.

By the way, this material is also available in other languages: