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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4. Joining and Merging
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Suggested Topics
- Types of joins: inner, outer, left, right
- Merge on single key: combining tables on one column
- Merge on multiple keys: compound join keys
- Handling duplicate keys: one-to-many and many-to-many joins
- Indicator column: tracking merge results
- Index-based joins: using row indices instead of columns
- Concatenation: stacking DataFrames vertically or horizontally
- Handling conflicting column names: suffixes and prefixes
- Performance: optimizing large joins
- Real example: joining customer data with purchase history
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