NumPy or Pandas: Keeping array type as integer while having a NaN value

Question

Is there a preferred way to keep the data type of a numpy array fixed as int (or int64 or whatever), while still having an element ins

Answer 1

This is now possible, since pandas v 0.24.0

pandas 0.24.x release notes Quote: "Pandas has gained the ability to hold integer dtypes with missing values.