57 lines
1.6 KiB
Python
57 lines
1.6 KiB
Python
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import pytest
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from pandas import (
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DatetimeIndex,
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Series,
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Timestamp,
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date_range,
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)
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import pandas._testing as tm
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@pytest.mark.parametrize(
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"cons",
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[
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lambda x: DatetimeIndex(x),
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lambda x: DatetimeIndex(DatetimeIndex(x)),
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],
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)
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def test_datetimeindex(using_copy_on_write, cons):
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dt = date_range("2019-12-31", periods=3, freq="D")
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ser = Series(dt)
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idx = cons(ser)
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expected = idx.copy(deep=True)
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ser.iloc[0] = Timestamp("2020-12-31")
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if using_copy_on_write:
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tm.assert_index_equal(idx, expected)
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def test_datetimeindex_tz_convert(using_copy_on_write):
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dt = date_range("2019-12-31", periods=3, freq="D", tz="Europe/Berlin")
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ser = Series(dt)
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idx = DatetimeIndex(ser).tz_convert("US/Eastern")
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expected = idx.copy(deep=True)
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ser.iloc[0] = Timestamp("2020-12-31", tz="Europe/Berlin")
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if using_copy_on_write:
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tm.assert_index_equal(idx, expected)
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def test_datetimeindex_tz_localize(using_copy_on_write):
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dt = date_range("2019-12-31", periods=3, freq="D")
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ser = Series(dt)
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idx = DatetimeIndex(ser).tz_localize("Europe/Berlin")
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expected = idx.copy(deep=True)
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ser.iloc[0] = Timestamp("2020-12-31")
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if using_copy_on_write:
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tm.assert_index_equal(idx, expected)
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def test_datetimeindex_isocalendar(using_copy_on_write):
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dt = date_range("2019-12-31", periods=3, freq="D")
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ser = Series(dt)
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df = DatetimeIndex(ser).isocalendar()
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expected = df.index.copy(deep=True)
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ser.iloc[0] = Timestamp("2020-12-31")
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if using_copy_on_write:
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tm.assert_index_equal(df.index, expected)
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