import numpy as np
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import pytest
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from pandas.core.dtypes.dtypes import PeriodDtype
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import pandas as pd
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import pandas._testing as tm
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from pandas.core.arrays import period_array
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@pytest.mark.parametrize("dtype", [int, np.int32, np.int64, "uint32", "uint64"])
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def test_astype_int(dtype):
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# We choose to ignore the sign and size of integers for
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# Period/Datetime/Timedelta astype
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arr = period_array(["2000", "2001", None], freq="D")
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if np.dtype(dtype) != np.int64:
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with pytest.raises(TypeError, match=r"Do obj.astype\('int64'\)"):
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arr.astype(dtype)
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return
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result = arr.astype(dtype)
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expected = arr._ndarray.view("i8")
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tm.assert_numpy_array_equal(result, expected)
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def test_astype_copies():
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arr = period_array(["2000", "2001", None], freq="D")
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result = arr.astype(np.int64, copy=False)
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# Add the `.base`, since we now use `.asi8` which returns a view.
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# We could maybe override it in PeriodArray to return ._ndarray directly.
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assert result.base is arr._ndarray
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result = arr.astype(np.int64, copy=True)
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assert result is not arr._ndarray
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tm.assert_numpy_array_equal(result, arr._ndarray.view("i8"))
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def test_astype_categorical():
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arr = period_array(["2000", "2001", "2001", None], freq="D")
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result = arr.astype("category")
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categories = pd.PeriodIndex(["2000", "2001"], freq="D")
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expected = pd.Categorical.from_codes([0, 1, 1, -1], categories=categories)
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tm.assert_categorical_equal(result, expected)
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def test_astype_period():
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arr = period_array(["2000", "2001", None], freq="D")
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result = arr.astype(PeriodDtype("M"))
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expected = period_array(["2000", "2001", None], freq="M")
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tm.assert_period_array_equal(result, expected)
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@pytest.mark.parametrize("other", ["datetime64[ns]", "timedelta64[ns]"])
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def test_astype_datetime(other):
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arr = period_array(["2000", "2001", None], freq="D")
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# slice off the [ns] so that the regex matches.
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if other == "timedelta64[ns]":
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with pytest.raises(TypeError, match=other[:-4]):
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arr.astype(other)
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else:
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# GH#45038 allow period->dt64 because we allow dt64->period
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result = arr.astype(other)
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expected = pd.DatetimeIndex(["2000", "2001", pd.NaT])._data
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tm.assert_datetime_array_equal(result, expected)
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