import numpy as np
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import pytest
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from pandas import (
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CategoricalIndex,
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DatetimeIndex,
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Index,
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NaT,
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Period,
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PeriodIndex,
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period_range,
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)
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import pandas._testing as tm
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class TestPeriodIndexAsType:
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@pytest.mark.parametrize("dtype", [float, "timedelta64", "timedelta64[ns]"])
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def test_astype_raises(self, dtype):
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# GH#13149, GH#13209
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idx = PeriodIndex(["2016-05-16", "NaT", NaT, np.NaN], freq="D")
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msg = "Cannot cast PeriodIndex to dtype"
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with pytest.raises(TypeError, match=msg):
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idx.astype(dtype)
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def test_astype_conversion(self):
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# GH#13149, GH#13209
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idx = PeriodIndex(["2016-05-16", "NaT", NaT, np.NaN], freq="D", name="idx")
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result = idx.astype(object)
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expected = Index(
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[Period("2016-05-16", freq="D")] + [Period(NaT, freq="D")] * 3,
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dtype="object",
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name="idx",
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)
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tm.assert_index_equal(result, expected)
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result = idx.astype(np.int64)
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expected = Index(
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[16937] + [-9223372036854775808] * 3, dtype=np.int64, name="idx"
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)
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tm.assert_index_equal(result, expected)
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result = idx.astype(str)
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expected = Index([str(x) for x in idx], name="idx")
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tm.assert_index_equal(result, expected)
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idx = period_range("1990", "2009", freq="A", name="idx")
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result = idx.astype("i8")
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tm.assert_index_equal(result, Index(idx.asi8, name="idx"))
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tm.assert_numpy_array_equal(result.values, idx.asi8)
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def test_astype_uint(self):
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arr = period_range("2000", periods=2, name="idx")
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with pytest.raises(TypeError, match=r"Do obj.astype\('int64'\)"):
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arr.astype("uint64")
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with pytest.raises(TypeError, match=r"Do obj.astype\('int64'\)"):
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arr.astype("uint32")
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def test_astype_object(self):
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idx = PeriodIndex([], freq="M")
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exp = np.array([], dtype=object)
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tm.assert_numpy_array_equal(idx.astype(object).values, exp)
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tm.assert_numpy_array_equal(idx._mpl_repr(), exp)
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idx = PeriodIndex(["2011-01", NaT], freq="M")
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exp = np.array([Period("2011-01", freq="M"), NaT], dtype=object)
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tm.assert_numpy_array_equal(idx.astype(object).values, exp)
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tm.assert_numpy_array_equal(idx._mpl_repr(), exp)
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exp = np.array([Period("2011-01-01", freq="D"), NaT], dtype=object)
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idx = PeriodIndex(["2011-01-01", NaT], freq="D")
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tm.assert_numpy_array_equal(idx.astype(object).values, exp)
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tm.assert_numpy_array_equal(idx._mpl_repr(), exp)
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# TODO: de-duplicate this version (from test_ops) with the one above
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# (from test_period)
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def test_astype_object2(self):
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idx = period_range(start="2013-01-01", periods=4, freq="M", name="idx")
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expected_list = [
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Period("2013-01-31", freq="M"),
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Period("2013-02-28", freq="M"),
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Period("2013-03-31", freq="M"),
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Period("2013-04-30", freq="M"),
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]
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expected = Index(expected_list, dtype=object, name="idx")
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result = idx.astype(object)
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assert isinstance(result, Index)
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assert result.dtype == object
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tm.assert_index_equal(result, expected)
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assert result.name == expected.name
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assert idx.tolist() == expected_list
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idx = PeriodIndex(
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["2013-01-01", "2013-01-02", "NaT", "2013-01-04"], freq="D", name="idx"
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)
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expected_list = [
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Period("2013-01-01", freq="D"),
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Period("2013-01-02", freq="D"),
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Period("NaT", freq="D"),
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Period("2013-01-04", freq="D"),
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]
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expected = Index(expected_list, dtype=object, name="idx")
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result = idx.astype(object)
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assert isinstance(result, Index)
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assert result.dtype == object
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tm.assert_index_equal(result, expected)
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for i in [0, 1, 3]:
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assert result[i] == expected[i]
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assert result[2] is NaT
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assert result.name == expected.name
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result_list = idx.tolist()
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for i in [0, 1, 3]:
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assert result_list[i] == expected_list[i]
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assert result_list[2] is NaT
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def test_astype_category(self):
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obj = period_range("2000", periods=2, name="idx")
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result = obj.astype("category")
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expected = CategoricalIndex(
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[Period("2000-01-01", freq="D"), Period("2000-01-02", freq="D")], name="idx"
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)
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tm.assert_index_equal(result, expected)
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result = obj._data.astype("category")
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expected = expected.values
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tm.assert_categorical_equal(result, expected)
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def test_astype_array_fallback(self):
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obj = period_range("2000", periods=2, name="idx")
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result = obj.astype(bool)
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expected = Index(np.array([True, True]), name="idx")
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tm.assert_index_equal(result, expected)
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result = obj._data.astype(bool)
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expected = np.array([True, True])
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tm.assert_numpy_array_equal(result, expected)
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def test_period_astype_to_timestamp(self):
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pi = PeriodIndex(["2011-01", "2011-02", "2011-03"], freq="M")
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exp = DatetimeIndex(["2011-01-01", "2011-02-01", "2011-03-01"], tz="US/Eastern")
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res = pi.astype("datetime64[ns, US/Eastern]")
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tm.assert_index_equal(res, exp)
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assert res.freq == exp.freq
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