Question

(1)
(F) The value NAN/NAT/ None are the same in Pandas.
(a)True
(b)False​

Answer 1

Answer:

Replacing NaT with None (only) also replaces NaN with None.

Replacing NaN with None also replaces NaT with None

Replacing NaT and NaN with None, replaces NaT but leaves the NaN

Linked to previous, calling several times a replacement of NaN or NaT with None, switched between NaN and None for the float columns. An even number of calls will leave NaN, an odd number of calls will leave None.

This is a problem because I'm unable to replace only NaT or only NaN. This is also a problem because if I want to replace both, I intuitively call replace with the dict {pd.NaT: None, np.NaN: None} but end up with NaNs.