Pandas for Beginners - Part 2 Advanced Grouping, Aggregations, and Merges - Tutorial in Python

Welcome to "Pandas for Beginners Part 2: Advanced Grouping, Aggregations, and Merges Tutorial in Python"! In this video, we take your pandas skills to the next level by exploring advanced techniques that are essential for data manipulation and analysis.

What You'll Learn:

1. Grouping Data: Master the groupby function to efficiently group data and perform operations on these groups.
2. Aggregation Functions: Learn how to use aggregation functions like sum(), mean(), count(), and more to summarise data.
3. Merging DataFrames: Understand different types of merges (inner, outer, left, right) using the merge() function to combine multiple DataFrames.

Why Watch This Tutorial?
Hands-On Examples: Follow along with practical, real-world examples to solidify your understanding.
Beginner-Friendly: Designed for beginners who have completed Part 1, but still accessible if you're new to these concepts.
Boost Your Skills: Enhance your data analysis capabilities in Python, making you more proficient and efficient.

Don't Miss Part 1!

If you haven't watched "Getting Started with Pandas in Python: Beginner's Guide (Part 1)," make sure to check it out for a solid foundation before diving into advanced topics.

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[Jeff-Zhu]

quite strange, when run the same command in the query: merged.groupby(by='day', as_index=False).sum()
the result contain the item and category columns, untill run below query:
merged.groupby(by='day', as_index=False)['cost'].sum()