How to Merge DataFrames in Pandas – merge(), join(), append(), concat() and update()
Introduction
Pandas provides a huge range of methods and functions to manipulate data, including merging DataFrames. Merging DataFrames allows you to both create a new DataFrame without modifying the original data source or alter the original data source.
If you are familiar with the SQL or a similar type of tabular data, you probably are familiar with the term join, which means combining DataFrames to form a new DataFrame. If you are a beginner it can be hard to fully grasp the join types (inner, outer, left, right). In this tutorial we’ll go over by join types with examples.
Our main focus would be on using the merge() and concat() functions. However, we will discuss other merging methods to give you as many practical alternatives as possible.
For this tutorial, we are using Pandas version 1.1.4 and NumPy version 1.19.4.
For your convenience, here’s the table of contents: