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PROPOSAL: use datetime64 and timedelta64 to eval #22063

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PROPOSAL: use datetime64 and timedelta64 to eval #22063

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6c33b65
use datetime64 and timedelta64 to eval
holymonson Jul 26, 2018
7ff27d2
block: save .tz in DatetimeTZBlock, discard DatetimeIndex
holymonson Jul 27, 2018
98bd79a
compat: add np_percentile_compat for datetime64
holymonson Jul 27, 2018
0c90051
add pytest.raises to test_binop_other
holymonson Jul 28, 2018
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16 changes: 16 additions & 0 deletions pandas/compat/numpy/__init__.py
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Expand Up @@ -68,6 +68,22 @@ def np_array_datetime64_compat(arr, *args, **kwargs):
return np.array(arr, *args, **kwargs)


# np.percentile should support datetime64 in upsteam. numpy/numpy#11620
# TODO: change the version if the bug fixed
if _nlv >= '99.99.99':
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Is this just a placeholder for "distant future"?

np_percentile_compat = np.percentile
else:
def np_percentile_compat(values, q, **kw):
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the iNat concern aside, this looks like a nice function. But I don't see why it should be in compat. Might make more sense in nanops?

'''
provide compat for np.percentile supporting datetime64
'''
if values.dtype.kind == 'M':
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Does timedelta64 get handled correctly by numpy?

result = np.percentile(values.view('i8'), q, **kw)
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Will this handle iNaT correctly?

return result.astype(values.dtype)
else:
return np.percentile(values, q, **kw)


__all__ = ['np',
'_np_version_under1p10',
'_np_version_under1p11',
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