Handling Missing Data in Integer Arrays: Python Solutions with NumPy and Pandas
NumPy: By default, NumPy arrays can't mix integers and NaNs. If you include a NaN in an integer array (int64), it gets automatically converted to a more general data type like object (which can hold various types), losing the efficiency of integer operations