ENH: std for dt64 dtype #37436
ENH: std for dt64 dtype #37436
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jreback
added
ExtensionArray
| @@ -785,6 +784,9 @@ def nanstd(values, axis=None, skipna=True, ddof=1, mask=None): | |||
| >>> nanops.nanstd(s) | |||
| 1.0 | |||
| """ | |||
| if values.dtype == "M8[ns]": | |||
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shouldn't this be done in _get_values?
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this is specific to std
| @@ -290,8 +290,18 @@ def test_sum_2d_skipna_false(self): | |||
| )._values | |||
| tm.assert_timedelta_array_equal(result, expected) | |||
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| def test_std(self): | |||
| tdi = pd.TimedeltaIndex(["0H", "4H", "NaT", "4H", "0H", "2H"]) | |||
| # Adding a Timestamp makes this a test for DatetimeArray.std | |||
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shouldn't this be in test_datetimes? yes i read your comment, but still the location is odd
| result = nanops.nanstd(np.asarray(arr), skipna=False) | ||
| assert result is pd.NaT | ||
| if getattr(arr, "tz", None) is None: | ||
| result = nanops.nanstd(np.asarray(arr), skipna=False) |
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are we sure the actual result is correct? e.g. you are just comparing vs the implementation itself. IOW a result which checks a fixed series of datetimes for mean/std would be good.
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agreed these tests needs fleshing out. im still giving thought to where they should live
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sure, that's fine about location. i am more concerned with if the results are actually correct; reasoning is that they are converted to i8 but need to make sure that these are coming back correct as well. i am not sure this is actually tested.
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Yes, we have tests with explicit expected for std() with td64 in test_reductions, test_describe, and test_analytics.
black pandasgit diff upstream/master -u -- "*.py" | flake8 --diff