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What category theory teaches us about dataframes
Every dataframe library ships with hundreds of operations. pandas alone has over 200 methods on a DataFrame. Is pivot different from melt? Is apply different from map? What about transform, agg, applymap, pipe? Some of these seem like the same operation wearing different hats. Others seem genuinely distinct. Without a framework for telling them apart, you end up memorizing APIs instead of understanding structure.
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