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fix mean for datetime-like using the respective time resolution unit #9977

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Merged
merged 9 commits into from
Jan 29, 2025
Merged

fix mean for datetime-like using the respective time resolution unit #9977

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f1e8be4
fix mean for datetime-like by using the respective dtype time resolut…
kmuehlbauer Jan 23, 2025
a66656b
fix mypy
kmuehlbauer Jan 23, 2025
618760d
add PR to existing entry for non-nanosecond datetimes
kmuehlbauer Jan 23, 2025
9226088
Merge branch 'main' into fix-datetime-mean
kmuehlbauer Jan 24, 2025
5d919a0
Update xarray/core/duck_array_ops.py
kmuehlbauer Jan 25, 2025
dfc9e03
cast to "int64" in calculation of datime-like mean
kmuehlbauer Jan 25, 2025
180aa0a
Apply suggestions from code review
kmuehlbauer Jan 26, 2025
295d816
Apply suggestions from code review
kmuehlbauer Jan 26, 2025
892fc07
Merge branch 'main' into fix-datetime-mean
dcherian Jan 27, 2025
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Apply suggestions from code review 
Co-authored-by: Spencer Clark <spencerkclark@gmail.com>
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@kmuehlbauer @spencerkclark
kmuehlbauer and spencerkclark authored Jan 26, 2025
commit 295d8167ff5a45701f06b219ec5dac0a8f3c87ba
3 changes: 1 addition & 2 deletions xarray/core/duck_array_ops.py
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Expand Up @@ -231,7 +231,7 @@
xp = get_array_namespace(data)
if xp == np:
# numpy currently doesn't have a astype:
return data.astype(dtype, **kwargs)

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return xp.astype(data, dtype, **kwargs)
return data.astype(dtype, **kwargs)

Expand Down Expand Up @@ -713,8 +713,7 @@
# is one of "s", "ms", "us", "ns".
# To not have to worry about the resolution, we just convert the output
# to "timedelta64" (without unit) and let the dtype of offset take precedence.
# This is fully backwards compatible with datetime64[ns]. For other
# this might lead to imprecise output, where fractional parts are truncated.
# This is fully backwards compatible with datetime64[ns].
return (
_mean(
datetime_to_numeric(array, offset), axis=axis, skipna=skipna, **kwargs
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4 changes: 0 additions & 4 deletions xarray/tests/test_duck_array_ops.py
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Expand Up @@ -970,8 +970,6 @@ def test_np_timedelta64_to_float(
# tests any combination of source np.timedelta64 (NPDatetimeUnitOptions) with
# np_timedelta_to_float with dedicated target unit (PDDatetimeUnitOptions)
td = np.timedelta64(1, np_dt_unit)
if _NS_PER_TIME_DELTA[np_dt_unit] < _NS_PER_TIME_DELTA[time_unit]:
pytest.skip("combination cannot be calculated without precision loss")
expected = _NS_PER_TIME_DELTA[np_dt_unit] / _NS_PER_TIME_DELTA[time_unit]

out = np_timedelta64_to_float(td, datetime_unit=time_unit)
Expand All @@ -989,8 +987,6 @@ def test_pd_timedelta_to_float(
# tests any combination of source pd.Timedelta (NPDatetimeUnitOptions) with
# np_timedelta_to_float with dedicated target unit (PDDatetimeUnitOptions)
td = pd.Timedelta(1, np_dt_unit)
if _NS_PER_TIME_DELTA[np_dt_unit] < _NS_PER_TIME_DELTA[time_unit]:
pytest.skip("combination cannot be calculated without precision loss")
expected = _NS_PER_TIME_DELTA[np_dt_unit] / _NS_PER_TIME_DELTA[time_unit]

out = pd_timedelta_to_float(td, datetime_unit=time_unit)
Expand Down
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