Pretty Powerful Pandas - Merging DataFrames: SQL Meets Python
In this episode of Pretty Powerful Pandas, we dive into one of the most essential skills in real-world data analysis: joining tables.
Using the Global Superstore dataset, I walk through how to:
Load multiple sheets from Excel
Merge two real tables (Orders + Returns) using .merge()
Handle column conflicts (like Region_x and Region_y)
Fill in missing values
And most importantly — use that merged data to uncover insights like total profit lost from returns and most frequently returned products.
If you’re used to SQL joins or Excel VLOOKUPs, this is how you bring that logic into your Python workflow — all in one tidy script.
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