Why adding multiple 'nan' in python dictionary giving multiple entries?

Question

Example problem:

import numpy as np
dc = dict()
dc[np.float(\'nan\')] = 100
dc[np.float(\'nan\')] = 200

It is creating multiple entries for

Answer 1

For historical reasons explained here, np.float('nan') == np.float('nan') is False. The rule is just that you can't have two dictionary keys which are equal to each other - so you can have two keys equal to np.float('nan').

Of course, this behavior is counterintuitive and surprising - so you should avoid using np.float('nan') as a key.