Python Pandas Pivot Made Easy! Simple Guide with Tons of Examples

Video Description

🧠 Don’t miss out! Get FREE access to my Skool community — packed with resources, tools, and support to help you with Data, Machine Learning, and AI Automations! 📈 https://www.skool.com/data-and-ai-automations-4579 Struggling to reshape your data in Python? Learn how to use pivot() and pivot_table() in Pandas with this beginner-friendly tutorial packed with practical examples! Whether you're analyzing sales data, building reports, or prepping for a data science interview—this guide makes pivoting effortless. Code: https://ryanandmattdatascience.com/pandas-pivot/ 🚀 Hire me for Data Work: https://ryanandmattdatascience.com/data-freelancing/ 👨‍💻 Mentorships: https://ryanandmattdatascience.com/mentorship/ 📧 Email: [email protected] 🌐 Website & Blog: https://ryanandmattdatascience.com/ 🖥️ Discord: https://discord.com/invite/F7dxbvHUhg 📚 *Practice SQL & Python Interview Questions: https://stratascratch.com/?via=ryan 📖 *SQL and Python Courses: https://datacamp.pxf.io/XYD7Qg 🍿 WATCH NEXT Python Pandas Playlist: https://www.youtube.com/playlist?list=PLcQVY5V2UY4KvHRJ-awaxAPzFGdZ8yN6D Python Pandas Melt: https://youtu.be/XsYT6TD8nJc Python Pandas Filter Multiple Conditions: https://youtu.be/2P--rjal30Y Python Pandas Apply: https://youtu.be/unthMgpKDsc Learn how to use pivot tables in Python Pandas to reorganize and summarize data efficiently. This comprehensive tutorial walks you through six practical examples of using the pivot function, from basic pivots to advanced multi-level aggregations with null value handling. We start with simple pivot operations, showing you how to transform rows into columns and reorganize your DataFrame structure. You'll learn the difference between pivot and pivot_table, and when to use each method. I demonstrate how to add totals and margins to your pivot tables, making it easy to see summary statistics at a glance. Next, we explore multiple aggregate functions, allowing you to calculate sum, mean, max, and min values simultaneously. The video covers multi-level pivots with hierarchical indexes, perfect for analyzing complex datasets with multiple dimensions. You'll also learn how to handle null values by filling them with custom text or default values. Throughout the tutorial, I use real-world marathon race data to make the concepts practical and relatable. Each example builds on the previous one, gradually increasing in complexity. I explain every line of code so you can understand exactly what's happening and apply these techniques to your own data analysis projects. All code from this video is available on our website for easy copy-paste access. Whether you're analyzing sales data, sports statistics, or any tabular information, mastering pivot tables will save you hours of manual data manipulation. TIMESTAMPS 00:00 Introduction to Pivot in Pandas 01:40 Setting Up Data and Imports 02:55 Example 1: Basic Pivot 05:17 Example 2: Adding Totals to Pivot Tables 07:32 Example 3: Multiple Aggregate Functions 09:53 Example 4: Multi-Level Pivots 13:32 Reordering Pivot Table Columns 15:17 Example 5: Working with Null Values 17:32 Example 6: Handling Multiple Values with Pivot Table 19:56 Recap and Final Tips OTHER SOCIALS: Ryan’s LinkedIn: https://www.linkedin.com/in/ryan-p-nolan/ Matt’s LinkedIn: https://www.linkedin.com/in/matt-payne-ceo/ Twitter/X: https://x.com/RyanMattDS 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. *This is an affiliate program. We receive a small portion of the final sale at no extra cost to you.