seniorPandas
How does Pandas handle missing data internally (NaN representation)?
Updated May 17, 2026
Short answer
Pandas uses NaN (NumPy float) and nullable dtypes for missing data.
Deep explanation
Historically, Pandas relied on NaN which forces float dtype. Modern Pandas introduces nullable types like Int64 and BooleanDtype to better represent missing values without coercion.
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