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Period accepts datetime64 value #9869

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Period accepts datetime64 value #9869

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1 change: 1 addition & 0 deletions doc/source/whatsnew/v0.16.1.txt
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Expand Up @@ -49,6 +49,7 @@ Enhancements

- Allow conversion of values with dtype ``datetime64`` or ``timedelta64`` to strings using ``astype(str)`` (:issue:`9757`)
- ``get_dummies`` function now accepts ``sparse`` keyword. If set to ``True``, the return ``DataFrame`` is sparse, e.g. ``SparseDataFrame``. (:issue:`8823`)
- ``Period`` now accepts ``datetime64`` as value input. (:issue:`9054`)

.. _whatsnew_0161.api:

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4 changes: 4 additions & 0 deletions pandas/src/period.pyx
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Expand Up @@ -710,6 +710,10 @@ cdef class Period(object):
dt = value
if freq is None:
raise ValueError('Must supply freq for datetime value')
elif isinstance(value, np.datetime64):
dt = Timestamp(value)
if freq is None:
raise ValueError('Must supply freq for datetime value')
elif isinstance(value, date):
dt = datetime(year=value.year, month=value.month, day=value.day)
if freq is None:
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6 changes: 6 additions & 0 deletions pandas/tseries/tests/test_period.py
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Expand Up @@ -226,7 +226,13 @@ def test_period_constructor(self):

i1 = Period(date(2007, 1, 1), freq='M')
i2 = Period(datetime(2007, 1, 1), freq='M')
i3 = Period(np.datetime64('2007-01-01'), freq='M')
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can you add a couple of more tests that have different numpy units,

e.g.

In [3]: np.datetime64('2007-01-01 00:00:00',dtype='M8[s]').dtype
Out[3]: dtype('<M8[s]')

i4 = Period(np.datetime64('2007-01-01 00:00:00Z'), freq='M')
i5 = Period(np.datetime64('2007-01-01 00:00:00.000Z'), freq='M')
self.assertEqual(i1, i2)
self.assertEqual(i1, i3)
self.assertEqual(i1, i4)
self.assertEqual(i1, i5)

i1 = Period('2007-01-01 09:00:00.001')
expected = Period(datetime(2007, 1, 1, 9, 0, 0, 1000), freq='L')
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