from datetime import timedelta
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import numpy as np
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import pytest
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import pandas as pd
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from pandas import (
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Index,
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NaT,
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Timedelta,
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TimedeltaIndex,
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timedelta_range,
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)
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import pandas._testing as tm
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class TestTimedeltaIndex:
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def test_astype_object(self):
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idx = timedelta_range(start="1 days", periods=4, freq="D", name="idx")
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expected_list = [
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Timedelta("1 days"),
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Timedelta("2 days"),
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Timedelta("3 days"),
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Timedelta("4 days"),
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]
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result = idx.astype(object)
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expected = Index(expected_list, dtype=object, name="idx")
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tm.assert_index_equal(result, expected)
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assert idx.tolist() == expected_list
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def test_astype_object_with_nat(self):
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idx = TimedeltaIndex(
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[timedelta(days=1), timedelta(days=2), NaT, timedelta(days=4)], name="idx"
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)
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expected_list = [
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Timedelta("1 days"),
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Timedelta("2 days"),
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NaT,
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Timedelta("4 days"),
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]
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result = idx.astype(object)
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expected = Index(expected_list, dtype=object, name="idx")
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tm.assert_index_equal(result, expected)
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assert idx.tolist() == expected_list
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def test_astype(self):
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# GH 13149, GH 13209
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idx = TimedeltaIndex([1e14, "NaT", NaT, np.NaN], name="idx")
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result = idx.astype(object)
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expected = Index(
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[Timedelta("1 days 03:46:40")] + [NaT] * 3, dtype=object, 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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[100000000000000] + [-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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rng = timedelta_range("1 days", periods=10)
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result = rng.astype("i8")
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tm.assert_index_equal(result, Index(rng.asi8))
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tm.assert_numpy_array_equal(rng.asi8, result.values)
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def test_astype_uint(self):
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arr = timedelta_range("1H", periods=2)
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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_timedelta64(self):
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# GH 13149, GH 13209
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idx = TimedeltaIndex([1e14, "NaT", NaT, np.NaN])
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msg = (
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r"Cannot convert from timedelta64\[ns\] to timedelta64. "
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"Supported resolutions are 's', 'ms', 'us', 'ns'"
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)
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with pytest.raises(ValueError, match=msg):
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idx.astype("timedelta64")
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result = idx.astype("timedelta64[ns]")
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tm.assert_index_equal(result, idx)
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assert result is not idx
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result = idx.astype("timedelta64[ns]", copy=False)
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tm.assert_index_equal(result, idx)
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assert result is idx
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@pytest.mark.parametrize("dtype", [float, "datetime64", "datetime64[ns]"])
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def test_astype_raises(self, dtype):
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# GH 13149, GH 13209
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idx = TimedeltaIndex([1e14, "NaT", NaT, np.NaN])
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msg = "Cannot cast TimedeltaIndex 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_category(self):
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obj = timedelta_range("1H", periods=2, freq="H")
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result = obj.astype("category")
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expected = pd.CategoricalIndex([Timedelta("1H"), Timedelta("2H")])
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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 = timedelta_range("1H", periods=2)
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result = obj.astype(bool)
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expected = Index(np.array([True, True]))
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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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