How to Use Python Pandas Concat to Combine DataFrames (Step-by-Step)

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Want to combine multiple DataFrames in Pandas with ease? In this tutorial, you’ll learn how to use pandas.concat() step-by-step to stack, join, and merge datasets efficiently. Great for beginners working with real-world data!

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In this Python Pandas tutorial, we dive deep into the concat function and show you exactly how to combine multiple DataFrames efficiently. Whether you need to stack DataFrames vertically like a SQL UNION or add new columns horizontally, concat is your go-to tool. We walk through four practical examples using real runner data, starting with basic row concatenation, then showing you how to reset indexes to avoid duplicates, adding keys to label your source DataFrames, and finally demonstrating column concatenation with axis=1.

You'll learn the critical difference between concat and merge, understand when to use each method, and see why proper index alignment matters when combining data. We cover essential parameters like keys for data labeling and axis for controlling direction, plus important tips about index management that can save you from data quality issues. By the end of this tutorial, you'll confidently know how to concatenate DataFrames in any scenario, whether you're stacking datasets from different sources or adding calculated columns to existing data.

All code from this video is available on our website - link in the description below. Perfect for data analysts, data scientists, and anyone working with Pandas who wants to master DataFrame manipulation.

TIMESTAMPS
00:00 Introduction to Concatenation
00:27 Setup and Importing Pandas
01:02 Creating Ultra Runners DataFrame
02:17 Creating Marathon Runners DataFrame
03:02 Example 1: Basic Concatenation
06:00 Example 2: Resetting Index
08:08 Example 3: Using Keys Parameter
10:00 Example 4: Concatenating Columns
13:00 Concat vs Merge Explained
14:20 Final Review and Best Practices

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Who is Ryan
Ryan is a Data Scientist at a fintech company, where he focuses on fraud prevention in underwriting and risk. Before that, he worked as a Data Analyst at a tax software company. He holds a degree in Electrical Engineering from UCF.

Who is Matt
Matt is the founder of Width.ai, an AI and Machine Learning agency. Before starting his own company, he was a Machine Learning Engineer at Capital One.

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