pandas (original) (raw)

import pandas as pd import numpy as np

ser = pd.Series([1, np.nan, 2], dtype=object)

ser.interpolate() 0 1 1 NaN 2 2 dtype: object

ATM if we have object-dtype, interpolate is incorrectly a no-op. (In the DataFrame case we have a weird check that raises on all-object).

If we disable the check in Block.interpolate if m is None and self.dtype.kind != "f": that short-circuits, then the OP case raises in np.interp when trying to cast to float64.

The viable options I see are:

Raise on object dtype, tell users to do .infer_objects() before calling interpolate.
Check if there the array has any NaNs. if not, short-circuit as in the status quo. Otherwise goto 1).

I lean towards "do 2) immediately and 1) with a deprecation cycle".

(I haven't checked the scipy paths, just the numpy one)