| /dports/math/py-pandas/pandas-1.2.5/doc/source/whatsnew/ |
| H A D | v0.16.1.rst | 308 - Allow conversion of values with dtype ``datetime64`` or ``timedelta64`` to strings using ``astype…
310 - ``Period`` now accepts ``datetime64`` as value input. (:issue:`9054`)
452 - Bug in ``where`` when dtype is ``datetime64/timedelta64``, but dtype of other is not (:issue:`980…
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| /dports/math/py-pandas/pandas-1.2.5/pandas/tests/series/indexing/ |
| H A D | test_indexing.py | 579 (np.datetime64("NaT", "ns"), True),
611 (np.datetime64("NaT", "ns"), False),
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| /dports/devel/py-numba/numba-0.51.2/docs/source/developer/ |
| H A D | dispatching.rst | 121 For non-so-trivial types (imagine a tuple, or a Numpy ``datetime64`` array,
210 ``datetime64``, or a C-contiguous array and a Fortran-contiguous array).
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| /dports/science/py-cirq-aqt/Cirq-0.12.0/cirq-core/cirq/work/ |
| H A D | observable_measurement_data.py | 266 self.timestamps = np.append(self.timestamps, [np.datetime64(datetime.datetime.now())])
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| /dports/science/py-cirq-pasqal/Cirq-0.13.1/cirq-core/cirq/work/ |
| H A D | observable_measurement_data.py | 285 self.timestamps = np.append(self.timestamps, [np.datetime64(datetime.datetime.now())])
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| /dports/science/py-cirq-core/Cirq-0.13.1/cirq-core/cirq/work/ |
| H A D | observable_measurement_data.py | 285 self.timestamps = np.append(self.timestamps, [np.datetime64(datetime.datetime.now())])
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| /dports/science/py-cirq-google/Cirq-0.13.0/cirq-core/cirq/work/ |
| H A D | observable_measurement_data.py | 285 self.timestamps = np.append(self.timestamps, [np.datetime64(datetime.datetime.now())])
|
| /dports/science/py-cirq-ionq/Cirq-0.13.1/cirq-core/cirq/work/ |
| H A D | observable_measurement_data.py | 285 self.timestamps = np.append(self.timestamps, [np.datetime64(datetime.datetime.now())])
|
| /dports/math/py-numpy/numpy-1.20.3/numpy/typing/tests/data/reveal/ |
| H A D | arithmetic.py | 13 dt = np.datetime64(0, "D")
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| /dports/math/py-pandas/pandas-1.2.5/pandas/tests/frame/methods/ |
| H A D | test_select_dtypes.py | 79 exclude = (np.datetime64,)
|
| /dports/math/py-pandas/pandas-1.2.5/pandas/tests/indexes/datetimes/ |
| H A D | test_misc.py | 383 arr = np.array([np.datetime64("2012-02-15T12:00:00.000000000")])
|
| /dports/math/py-pandas/pandas-1.2.5/pandas/core/arrays/ |
| H A D | floating.py | 390 kwargs = {"na_value": np.datetime64("NaT")}
|
| /dports/math/py-pandas/pandas-1.2.5/pandas/tests/arithmetic/ |
| H A D | test_datetime64.py | 379 [datetime(2016, 1, 1), Timestamp("2016-01-01"), np.datetime64("2016-01-01")],
385 if isinstance(other, np.datetime64):
471 np.datetime64("nat"),
642 [datetime(2016, 1, 1), Timestamp("2016-01-01"), np.datetime64("2016-01-01")],
957 dt64 = np.datetime64("2013-01-01")
2191 np.datetime64("2011-01-01"),
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| /dports/math/py-pandas/pandas-1.2.5/pandas/tests/frame/indexing/ |
| H A D | test_indexing.py | 1118 [13, np.datetime64("2013-01-01T00:00:00")],
1119 [14, np.datetime64("2014-01-01T00:00:00")],
1428 df.loc[0:1, "c"] = np.datetime64("2008-08-08")
1448 df["H"] = np.datetime64("NaT")
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| /dports/multimedia/navidrome/navidrome-0.40.0/vendor/github.com/ClickHouse/clickhouse-go/ |
| H A D | clickhouse_test.go | 93 datetime64 DateTime64,
116 datetime64,
158 datetime64,
|
| /dports/devel/py-xarray/xarray-0.20.1/xarray/plot/ |
| H A D | plot.py | 456 if np.issubdtype(xplt.dtype, np.datetime64):
1246 if np.issubdtype(xplt.dtype, np.datetime64):
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| /dports/math/py-pandas/pandas-1.2.5/pandas/tests/frame/ |
| H A D | test_block_internals.py | 225 df["dt1"] = np.datetime64("2013-01-01")
|
| /dports/graphics/py-plotly/plotly-4.14.3/plotly/express/ |
| H A D | _imshow.py | 274 if np.issubdtype(img.coords[ax].dtype, np.datetime64):
|
| /dports/math/py-pandas/pandas-1.2.5/pandas/_libs/tslibs/ |
| H A D | offsets.pyx | 255 # > np.datetime64(dt.datetime(2013,5,1),dtype='datetime64[D]')
256 # numpy.datetime64('2013-05-01T02:00:00.000000+0200')
257 # Thus astype is needed to cast datetime to datetime64[D]
264 dt = np.int64(dt).astype('datetime64[ns]')
266 dt = np.datetime64(dt)
267 if dt.dtype.name != "datetime64[D]":
268 dt = dt.astype("datetime64[D]")
1052 ndarray[datetime64[ns]]
1076 dt64other = shifted.view("datetime64[ns]")
3230 np_dt = np.datetime64(date_in.date())
[all …]
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| /dports/www/grafana8/grafana-8.3.6/vendor/github.com/apache/arrow/python/pyarrow/tests/ |
| H A D | test_array.py | 1894 n = np.datetime64('NaT', unit)
1895 x = np.datetime64('2017-01-01 01:01:01.111111111', unit)
1896 y = np.datetime64('2018-11-22 12:24:48.111111111', unit)
1907 n = np.datetime64('NaT')
1908 x = np.datetime64('2017-01-01 01:01:01.111111111')
1909 y = np.datetime64('2018-11-22 12:24:48.111111111')
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| /dports/math/py-pandas/pandas-1.2.5/pandas/tests/groupby/ |
| H A D | test_apply.py | 662 "datetime": [np.datetime64("2017-02-01 00:00:00")] * 3,
675 "date": [np.datetime64("2017-02-01 00:00:00")] * 3,
|
| /dports/math/py-matplotlib/matplotlib-3.4.3/doc/api/prev_api_changes/ |
| H A D | api_changes_2.1.0.rst | 103 `datetime.date` to `numpy.datetime64` for better portability across Python
104 versions. Note that Matplotlib does not fully support `numpy.datetime64` as
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| /dports/science/py-cirq-aqt/Cirq-0.12.0/cirq-core/cirq/ |
| H A D | _compat.py | 46 if np.issubdtype(value.dtype, np.datetime64):
|
| /dports/science/py-cirq-core/Cirq-0.13.1/cirq-core/cirq/ |
| H A D | _compat.py | 47 if np.issubdtype(value.dtype, np.datetime64):
|
| /dports/science/py-cirq-pasqal/Cirq-0.13.1/cirq-core/cirq/ |
| H A D | _compat.py | 47 if np.issubdtype(value.dtype, np.datetime64):
|