MOC: DataFrames

Pandas and Polars side-by-side — 10 topics with paired Python and C# notebooks covering every DataFrame operation from loading to testing. Expand any domain to browse its sub-MOC.

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  ((Ingest and Explore))
    (foundations, IO)
    (explore, select, filter)
    (types and interop)

Ingest and Explore

domain-ingest-and-explore

DataFrame foundations, data loading, exploration, selection, filtering, and type interop across Pandas, Polars, and their C# counterparts.

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  ((Transform and Analyze))
    (transforms, expressions)
    (missing, strings, dates)
    (aggregation, reshaping)
    (lazy eval, performance)

Transform and Analyze

domain-transform-and-analyze

Column transforms, expressions, missing data handling, aggregation, reshaping, and lazy evaluation performance across Pandas and Polars.

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  ((Integrate and Validate))
    (visualization)
    (database interface)
    (testing, migration)

Integrate and Validate

domain-integrate-and-validate

Visualization, database connectivity, testing frameworks, and migration guides for DataFrame workflows.

DataFrames Cross-References

• Programming Languages — Python and C# foundations these notebooks build on
• DB Queries — SQL-first approach to the same data operations
• 25_py_functional_pipeline — Production pipeline using Polars DataFrames