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Day 12 — Pandas DataFrame Aggregations & Grouping

On Day 12 of my journey, I explored how to summarize and analyze data in Pandas using aggregations and grouping. These operations are at the heart of data analysis and reporting.

✨ What I covered:

Aggregation functions (sum(), mean(), count(), max(), min())

Using .agg() for multiple aggregations

Grouping data with groupby()

Applying different functions to different columns

Multi-level groupby (hierarchical grouping)

Sorting aggregated results

Combining groupby with filtering for deeper insights


With these tools, I can now extract meaningful patterns from large datasets — a critical skill for Data Science & AI.

I’m documenting my path of Learning AI from Scratch step by step 🚀


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