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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6. Advanced Transformations
Content coming soon...
Suggested Topics
- Pivoting: reshaping data from long to wide format
- Pivot tables: multi-dimensional aggregations
- Melting: reshaping from wide to long format
- Stacking and unstacking: working with multi-level indices
- Mapping: applying functions to columns (map, apply, applymap)
- Lambda functions: inline transformations
- Window functions: rolling means, expanding windows, cumulative sums
- Shift and lag: accessing previous/next rows for calculations
- Vectorization: replacing slow loops with fast array operations
- Performance optimization: when to vectorize vs apply
- Real example: complex data reshaping and time-series analysis
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