Pandas Fundamentals | Grouping & Aggregation

🎓 Master AI from Zero to Advanced: https://ailearninghub.io ------------------------- In this video, you’ll learn about aggregation and group by methods in pandas, which are essential for summarizing and analyzing data. We cover key concepts such as computing summary statistics, grouping data, and applying various aggregation metrics like mean, median, mode, standard deviation, and variance. You’ll also learn how to group by one or multiple columns, perform advanced aggregations, and use custom functions to calculate specific statistics. This video walks you through practical examples, including creating and analyzing a sample DataFrame, making it easy to follow along and apply these concepts to your own data analysis projects. Table of Contents: 0:00 Introduction to Aggregation and Group By 0:09 What is Aggregation? 0:25 Sample DataFrame Creation 1:21 Describing the DataFrame 1:25 Using describe() for Summary Statistics 2:39 Transposing Summary Statistics 3:28 Calculating Aggregation Metrics: Mean 3:57 Calculating Median 4:16 Calculating Mode 4:52 Calculating Standard Deviation 5:33 Calculating Variance 5:57 Calculating Sum 6:12 Calculating Product 6:20 Introduction to Group By Methods 7:01 Grouping by a Single Column 7:47 Calculating Aggregation Metrics by Groups: Average 9:08 Sum by Group 9:34 Min and Max by Group 11:07 Grouping by Multiple Columns 12:28 Performing Advanced Aggregations 17:35 Applying Custom Functions with apply() 19:33 Join AI Learning Hub for resources and mentorship ------------------------- Social channels: 🐦Twitter: https://twitter.com/dankornas 🌍LinkedIn: https://www.linkedin.com/in/daniel-kornas/ 🕵Facebook: https://www.facebook.com/dankornas 📱Instagram: https://www.instagram.com/dankornas 🧵 Threads: https://www.threads.net/@dankornas ------------------------- 📚 AI Books 📚 Introduction to Generative AI 👉 https://shorturl.at/3dSQz Build a Large Language Model (From Scratch) 👉 https://shorturl.at/EFv4j *I use affiliate links on the products that I recommend. I may earn a purchase commission or a referral bonus from the usage of these links.