What is the best way to get Index of NANs in a pandas data Series

Question

Suppose we've got some data series:

0  'one'
1  'two'
2   NAN
3   'three'
4   NAN
5   NAN

Now I would like to get the indecies of all the NAN elements. So using python's pandas lib I would do something like that:

import pandas as pd
import numpy as np


data = pd.Series(['one', 'two', np.nan, 'three', np.nan, np.nan])
nan_index = data.index.difference(data.dropna().index)

However, I'm getting the feeling that it's not a pandonic way of doing it.

Answer 1

By using isnull

data[data.isnull()].index
Out[739]: Int64Index([2, 4, 5], dtype='int64')

Or

data.isnull().nonzero()

Answer 2

In [11]: data.index[data.isnull()]
Out[11]: Int64Index([2, 4, 5], dtype='int64')

or

In [12]: np.where(data.isnull())[0]
Out[12]: array([2, 4, 5], dtype=int64)