Introduction to Pandas
DataFrame operations
Grouping and Aggregation
Joining and Merging
Different Data Types
Advanced Transformations
Writing Data
Alternatives to Pandas
Practice
Assignment
Gotchas & Pitfalls
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3. Grouping and Aggregation
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Suggested Topics
- GroupBy basics: splitting data into groups
- Aggregation functions: sum, mean, count, min, max
- Multiple aggregations: applying different functions to different columns
- Custom aggregation functions: writing your own aggregators
- Named aggregations: giving meaningful names to aggregated columns
- GroupBy with multiple columns: hierarchical grouping
- Filtering groups: selecting groups that meet criteria
- Transformation vs aggregation: preserving vs reducing dimensions
- Performance considerations: avoiding slow apply operations
- Real example: analyzing sales by product category and month
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