Week 4 - Data Processing with Pandas

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

• Teachers

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10. Gotchas & Pitfalls

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Suggested Topics

• Index misalignment: confusing row labels with positions when joining
• Implicit axis defaults: axis=0 vs axis=1 confusion in operations
• Copy vs view: when df[col] returns a view vs a copy (SettingWithCopyWarning)
• NaN comparison: NaN != NaN, special handling needed
• Type inference: Pandas guessing the wrong type (int vs float, date vs string)
• Memory usage: large DataFrames consuming unexpected amounts of RAM
• Categorical data: performance/memory benefits but requires careful handling
• Timezone-aware datetimes: subtle bugs when mixing naive and aware datetimes
• Sorting stability: understanding stable sort for multi-key sorting
• Apply performance: slow apply can be vectorized for speed
• Index preservation: operations that drop or reset index unexpectedly

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