Getting a list of indices where pandas boolean series is True

Question

I have a pandas series with boolean entries. I would like to get a list of indices where the values are True.

For example the input pd.Series([True, False, True, True, False, False, False, True])

should yield the output [0,2,3,7].

I can do it with a list comprehension, but is there something cleaner or faster?

Answer 1

Using Boolean Indexing

>>> s = pd.Series([True, False, True, True, False, False, False, True])
>>> s[s].index
Int64Index([0, 2, 3, 7], dtype='int64')

If need a np.array object, get the .values

>>> s[s].index.values
array([0, 2, 3, 7])

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Using np.nonzero

>>> np.nonzero(s)
(array([0, 2, 3, 7]),)

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Using np.flatnonzero

>>> np.flatnonzero(s)
array([0, 2, 3, 7])

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Using np.where

>>> np.where(s)[0]
array([0, 2, 3, 7])

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Using np.argwhere

>>> np.argwhere(s).ravel()
array([0, 2, 3, 7])

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Using pd.Series.index

>>> s.index[s]
array([0, 2, 3, 7])

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Using python's built-in filter

>>> [*filter(s.get, s.index)]
[0, 2, 3, 7]

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Using list comprehension

>>> [i for i in s.index if s[i]]
[0, 2, 3, 7]