Python DataFrames are entering a new era, and how you choose between Pandas and Polars increasingly shapes how well your data workflows hold up.
Pandas 3.0 brings new string types, Copy-on-Write, and real performance gains. Polars takes a different route, running multi-threaded by default with lazy evaluation built for large-scale speed.
This video breaks down what each brings to the table, so you can choose the right tool for your workflow.
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