Column transforms, expressions, missing data handling, aggregation, reshaping, and lazy evaluation performance across Pandas and Polars.
mindmap
((Transform and Analyze))
(transforms, expressions)
(missing, strings, dates)
(aggregation, reshaping)
(lazy eval, performance)
Transforms and Expressions
- Column creation with assign and with_columns — py · cs
- Polars expression system — py · cs
- Type casting — py · cs
- Method chaining and window expressions — py · cs
- Apply, map, and UDFs — py · cs
Missing Data, Strings, and DateTime
- Null representations and detection — py · cs
- Filling and dropping nulls — py · cs
- String operations and pattern matching — py · cs
- Date parsing and dt accessor — py · cs
- Rolling windows and resampling — py · cs
Aggregation and Reshaping
- Group-by and multiple aggregations — py · cs
- Window functions and rolling — py · cs
- Joins — py · cs
- Concatenation — py · cs
- Pivot, melt, and explode — py · cs
Lazy Evaluation and Performance
- Eager vs lazy execution — py · cs
- Query optimization and pushdown — py · cs
- Pandas vs Polars benchmarks — py · cs
- Vectorized vs loop performance — py · cs
- Memory usage and profiling — py · cs