mirror of
https://github.com/aykhans/AzSuicideDataVisualization.git
synced 2025-07-04 07:08:05 +00:00
first commit
This commit is contained in:
Ayxan
@ -0,0 +1,127 @@
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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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from pandas.core.api import (
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Float64Index,
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Int64Index,
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UInt64Index,
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)
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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(int)
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expected = Int64Index(
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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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expected = UInt64Index(
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np.array([3600000000000, 90000000000000], dtype="uint64")
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)
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tm.assert_index_equal(arr.astype("uint64"), expected)
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tm.assert_index_equal(arr.astype("uint32"), expected)
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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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result = idx.astype("timedelta64")
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expected = Float64Index([1e14] + [np.NaN] * 3, dtype="float64")
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tm.assert_index_equal(result, expected)
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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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@ -0,0 +1,40 @@
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import numpy as np
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from pandas import (
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TimedeltaIndex,
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factorize,
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timedelta_range,
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)
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import pandas._testing as tm
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class TestTimedeltaIndexFactorize:
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def test_factorize(self):
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idx1 = TimedeltaIndex(["1 day", "1 day", "2 day", "2 day", "3 day", "3 day"])
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exp_arr = np.array([0, 0, 1, 1, 2, 2], dtype=np.intp)
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exp_idx = TimedeltaIndex(["1 day", "2 day", "3 day"])
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arr, idx = idx1.factorize()
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tm.assert_numpy_array_equal(arr, exp_arr)
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tm.assert_index_equal(idx, exp_idx)
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assert idx.freq == exp_idx.freq
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arr, idx = idx1.factorize(sort=True)
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tm.assert_numpy_array_equal(arr, exp_arr)
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tm.assert_index_equal(idx, exp_idx)
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assert idx.freq == exp_idx.freq
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def test_factorize_preserves_freq(self):
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# GH#38120 freq should be preserved
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idx3 = timedelta_range("1 day", periods=4, freq="s")
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exp_arr = np.array([0, 1, 2, 3], dtype=np.intp)
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arr, idx = idx3.factorize()
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tm.assert_numpy_array_equal(arr, exp_arr)
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tm.assert_index_equal(idx, idx3)
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assert idx.freq == idx3.freq
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arr, idx = factorize(idx3)
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tm.assert_numpy_array_equal(arr, exp_arr)
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tm.assert_index_equal(idx, idx3)
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assert idx.freq == idx3.freq
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@ -0,0 +1,22 @@
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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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)
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import pandas._testing as tm
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class TestFillNA:
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def test_fillna_timedelta(self):
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# GH#11343
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idx = TimedeltaIndex(["1 day", NaT, "3 day"])
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exp = TimedeltaIndex(["1 day", "2 day", "3 day"])
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tm.assert_index_equal(idx.fillna(Timedelta("2 day")), exp)
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exp = TimedeltaIndex(["1 day", "3 hour", "3 day"])
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idx.fillna(Timedelta("3 hour"))
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exp = Index([Timedelta("1 day"), "x", Timedelta("3 day")], dtype=object)
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tm.assert_index_equal(idx.fillna("x"), exp)
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@ -0,0 +1,146 @@
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from datetime import timedelta
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import numpy as np
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import pytest
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from pandas._libs import lib
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import pandas as pd
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from pandas import (
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Index,
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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 TestTimedeltaIndexInsert:
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def test_insert(self):
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idx = TimedeltaIndex(["4day", "1day", "2day"], name="idx")
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result = idx.insert(2, timedelta(days=5))
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exp = TimedeltaIndex(["4day", "1day", "5day", "2day"], name="idx")
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tm.assert_index_equal(result, exp)
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# insertion of non-datetime should coerce to object index
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result = idx.insert(1, "inserted")
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expected = Index(
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[Timedelta("4day"), "inserted", Timedelta("1day"), Timedelta("2day")],
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name="idx",
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)
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assert not isinstance(result, TimedeltaIndex)
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tm.assert_index_equal(result, expected)
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assert result.name == expected.name
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idx = timedelta_range("1day 00:00:01", periods=3, freq="s", name="idx")
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# preserve freq
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expected_0 = TimedeltaIndex(
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["1day", "1day 00:00:01", "1day 00:00:02", "1day 00:00:03"],
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name="idx",
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freq="s",
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)
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expected_3 = TimedeltaIndex(
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["1day 00:00:01", "1day 00:00:02", "1day 00:00:03", "1day 00:00:04"],
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name="idx",
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freq="s",
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)
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# reset freq to None
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expected_1_nofreq = TimedeltaIndex(
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["1day 00:00:01", "1day 00:00:01", "1day 00:00:02", "1day 00:00:03"],
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name="idx",
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freq=None,
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)
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expected_3_nofreq = TimedeltaIndex(
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["1day 00:00:01", "1day 00:00:02", "1day 00:00:03", "1day 00:00:05"],
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name="idx",
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freq=None,
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)
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cases = [
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(0, Timedelta("1day"), expected_0),
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(-3, Timedelta("1day"), expected_0),
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(3, Timedelta("1day 00:00:04"), expected_3),
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(1, Timedelta("1day 00:00:01"), expected_1_nofreq),
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(3, Timedelta("1day 00:00:05"), expected_3_nofreq),
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]
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for n, d, expected in cases:
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result = idx.insert(n, d)
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tm.assert_index_equal(result, expected)
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assert result.name == expected.name
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assert result.freq == expected.freq
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@pytest.mark.parametrize(
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"null", [None, np.nan, np.timedelta64("NaT"), pd.NaT, pd.NA]
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)
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def test_insert_nat(self, null):
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# GH 18295 (test missing)
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idx = timedelta_range("1day", "3day")
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result = idx.insert(1, null)
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expected = TimedeltaIndex(["1day", pd.NaT, "2day", "3day"])
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tm.assert_index_equal(result, expected)
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def test_insert_invalid_na(self):
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idx = TimedeltaIndex(["4day", "1day", "2day"], name="idx")
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item = np.datetime64("NaT")
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result = idx.insert(0, item)
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expected = Index([item] + list(idx), dtype=object, name="idx")
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tm.assert_index_equal(result, expected)
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# Also works if we pass a different dt64nat object
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item2 = np.datetime64("NaT")
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result = idx.insert(0, item2)
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tm.assert_index_equal(result, expected)
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@pytest.mark.parametrize(
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"item", [0, np.int64(0), np.float64(0), np.array(0), np.datetime64(456, "us")]
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)
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def test_insert_mismatched_types_raises(self, item):
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# GH#33703 dont cast these to td64
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tdi = TimedeltaIndex(["4day", "1day", "2day"], name="idx")
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result = tdi.insert(1, item)
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expected = Index(
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[tdi[0], lib.item_from_zerodim(item)] + list(tdi[1:]),
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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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def test_insert_castable_str(self):
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idx = timedelta_range("1day", "3day")
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result = idx.insert(0, "1 Day")
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expected = TimedeltaIndex([idx[0]] + list(idx))
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tm.assert_index_equal(result, expected)
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def test_insert_non_castable_str(self):
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idx = timedelta_range("1day", "3day")
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result = idx.insert(0, "foo")
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expected = Index(["foo"] + list(idx), dtype=object)
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tm.assert_index_equal(result, expected)
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def test_insert_empty(self):
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# Corner case inserting with length zero doesn't raise IndexError
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# GH#33573 for freq preservation
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idx = timedelta_range("1 Day", periods=3)
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td = idx[0]
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result = idx[:0].insert(0, td)
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assert result.freq == "D"
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with pytest.raises(IndexError, match="loc must be an integer between"):
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result = idx[:0].insert(1, td)
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with pytest.raises(IndexError, match="loc must be an integer between"):
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result = idx[:0].insert(-1, td)
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@ -0,0 +1,34 @@
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import numpy as np
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from pandas import (
|
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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 TestRepeat:
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def test_repeat(self):
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index = timedelta_range("1 days", periods=2, freq="D")
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exp = TimedeltaIndex(["1 days", "1 days", "2 days", "2 days"])
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for res in [index.repeat(2), np.repeat(index, 2)]:
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tm.assert_index_equal(res, exp)
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assert res.freq is None
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index = TimedeltaIndex(["1 days", "NaT", "3 days"])
|
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exp = TimedeltaIndex(
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[
|
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"1 days",
|
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"1 days",
|
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"1 days",
|
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"NaT",
|
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"NaT",
|
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"NaT",
|
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"3 days",
|
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"3 days",
|
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"3 days",
|
||||
]
|
||||
)
|
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for res in [index.repeat(3), np.repeat(index, 3)]:
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tm.assert_index_equal(res, exp)
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assert res.freq is None
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@ -0,0 +1,77 @@
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import pytest
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|
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from pandas.errors import NullFrequencyError
|
||||
|
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import pandas as pd
|
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from pandas import TimedeltaIndex
|
||||
import pandas._testing as tm
|
||||
|
||||
|
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class TestTimedeltaIndexShift:
|
||||
|
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# -------------------------------------------------------------
|
||||
# TimedeltaIndex.shift is used by __add__/__sub__
|
||||
|
||||
def test_tdi_shift_empty(self):
|
||||
# GH#9903
|
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idx = TimedeltaIndex([], name="xxx")
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tm.assert_index_equal(idx.shift(0, freq="H"), idx)
|
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tm.assert_index_equal(idx.shift(3, freq="H"), idx)
|
||||
|
||||
def test_tdi_shift_hours(self):
|
||||
# GH#9903
|
||||
idx = TimedeltaIndex(["5 hours", "6 hours", "9 hours"], name="xxx")
|
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tm.assert_index_equal(idx.shift(0, freq="H"), idx)
|
||||
exp = TimedeltaIndex(["8 hours", "9 hours", "12 hours"], name="xxx")
|
||||
tm.assert_index_equal(idx.shift(3, freq="H"), exp)
|
||||
exp = TimedeltaIndex(["2 hours", "3 hours", "6 hours"], name="xxx")
|
||||
tm.assert_index_equal(idx.shift(-3, freq="H"), exp)
|
||||
|
||||
def test_tdi_shift_minutes(self):
|
||||
# GH#9903
|
||||
idx = TimedeltaIndex(["5 hours", "6 hours", "9 hours"], name="xxx")
|
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tm.assert_index_equal(idx.shift(0, freq="T"), idx)
|
||||
exp = TimedeltaIndex(["05:03:00", "06:03:00", "9:03:00"], name="xxx")
|
||||
tm.assert_index_equal(idx.shift(3, freq="T"), exp)
|
||||
exp = TimedeltaIndex(["04:57:00", "05:57:00", "8:57:00"], name="xxx")
|
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tm.assert_index_equal(idx.shift(-3, freq="T"), exp)
|
||||
|
||||
def test_tdi_shift_int(self):
|
||||
# GH#8083
|
||||
tdi = pd.to_timedelta(range(5), unit="d")
|
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trange = tdi._with_freq("infer") + pd.offsets.Hour(1)
|
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result = trange.shift(1)
|
||||
expected = TimedeltaIndex(
|
||||
[
|
||||
"1 days 01:00:00",
|
||||
"2 days 01:00:00",
|
||||
"3 days 01:00:00",
|
||||
"4 days 01:00:00",
|
||||
"5 days 01:00:00",
|
||||
],
|
||||
freq="D",
|
||||
)
|
||||
tm.assert_index_equal(result, expected)
|
||||
|
||||
def test_tdi_shift_nonstandard_freq(self):
|
||||
# GH#8083
|
||||
tdi = pd.to_timedelta(range(5), unit="d")
|
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trange = tdi._with_freq("infer") + pd.offsets.Hour(1)
|
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result = trange.shift(3, freq="2D 1s")
|
||||
expected = TimedeltaIndex(
|
||||
[
|
||||
"6 days 01:00:03",
|
||||
"7 days 01:00:03",
|
||||
"8 days 01:00:03",
|
||||
"9 days 01:00:03",
|
||||
"10 days 01:00:03",
|
||||
],
|
||||
freq="D",
|
||||
)
|
||||
tm.assert_index_equal(result, expected)
|
||||
|
||||
def test_shift_no_freq(self):
|
||||
# GH#19147
|
||||
tdi = TimedeltaIndex(["1 days 01:00:00", "2 days 01:00:00"], freq=None)
|
||||
with pytest.raises(NullFrequencyError, match="Cannot shift with no freq"):
|
||||
tdi.shift(2)
|
||||
@ -0,0 +1,276 @@
|
||||
from datetime import timedelta
|
||||
|
||||
import numpy as np
|
||||
import pytest
|
||||
|
||||
import pandas as pd
|
||||
from pandas import (
|
||||
Timedelta,
|
||||
TimedeltaIndex,
|
||||
timedelta_range,
|
||||
to_timedelta,
|
||||
)
|
||||
import pandas._testing as tm
|
||||
from pandas.core.arrays.timedeltas import (
|
||||
TimedeltaArray,
|
||||
sequence_to_td64ns,
|
||||
)
|
||||
|
||||
|
||||
class TestTimedeltaIndex:
|
||||
def test_array_of_dt64_nat_raises(self):
|
||||
# GH#39462
|
||||
nat = np.datetime64("NaT", "ns")
|
||||
arr = np.array([nat], dtype=object)
|
||||
|
||||
# TODO: should be TypeError?
|
||||
msg = "Invalid type for timedelta scalar"
|
||||
with pytest.raises(ValueError, match=msg):
|
||||
TimedeltaIndex(arr)
|
||||
|
||||
with pytest.raises(ValueError, match=msg):
|
||||
TimedeltaArray._from_sequence(arr)
|
||||
|
||||
with pytest.raises(ValueError, match=msg):
|
||||
sequence_to_td64ns(arr)
|
||||
|
||||
@pytest.mark.parametrize("unit", ["Y", "y", "M"])
|
||||
def test_unit_m_y_raises(self, unit):
|
||||
msg = "Units 'M', 'Y', and 'y' are no longer supported"
|
||||
with pytest.raises(ValueError, match=msg):
|
||||
TimedeltaIndex([1, 3, 7], unit)
|
||||
|
||||
def test_int64_nocopy(self):
|
||||
# GH#23539 check that a copy isn't made when we pass int64 data
|
||||
# and copy=False
|
||||
arr = np.arange(10, dtype=np.int64)
|
||||
tdi = TimedeltaIndex(arr, copy=False)
|
||||
assert tdi._data._data.base is arr
|
||||
|
||||
def test_infer_from_tdi(self):
|
||||
# GH#23539
|
||||
# fast-path for inferring a frequency if the passed data already
|
||||
# has one
|
||||
tdi = timedelta_range("1 second", periods=10**7, freq="1s")
|
||||
|
||||
result = TimedeltaIndex(tdi, freq="infer")
|
||||
assert result.freq == tdi.freq
|
||||
|
||||
# check that inferred_freq was not called by checking that the
|
||||
# value has not been cached
|
||||
assert "inferred_freq" not in getattr(result, "_cache", {})
|
||||
|
||||
def test_infer_from_tdi_mismatch(self):
|
||||
# GH#23539
|
||||
# fast-path for invalidating a frequency if the passed data already
|
||||
# has one and it does not match the `freq` input
|
||||
tdi = timedelta_range("1 second", periods=100, freq="1s")
|
||||
|
||||
msg = (
|
||||
"Inferred frequency .* from passed values does "
|
||||
"not conform to passed frequency"
|
||||
)
|
||||
with pytest.raises(ValueError, match=msg):
|
||||
TimedeltaIndex(tdi, freq="D")
|
||||
|
||||
with pytest.raises(ValueError, match=msg):
|
||||
# GH#23789
|
||||
TimedeltaArray(tdi, freq="D")
|
||||
|
||||
with pytest.raises(ValueError, match=msg):
|
||||
TimedeltaIndex(tdi._data, freq="D")
|
||||
|
||||
with pytest.raises(ValueError, match=msg):
|
||||
TimedeltaArray(tdi._data, freq="D")
|
||||
|
||||
def test_dt64_data_invalid(self):
|
||||
# GH#23539
|
||||
# passing tz-aware DatetimeIndex raises, naive or ndarray[datetime64]
|
||||
# raise as of GH#29794
|
||||
dti = pd.date_range("2016-01-01", periods=3)
|
||||
|
||||
msg = "cannot be converted to timedelta64"
|
||||
with pytest.raises(TypeError, match=msg):
|
||||
TimedeltaIndex(dti.tz_localize("Europe/Brussels"))
|
||||
|
||||
with pytest.raises(TypeError, match=msg):
|
||||
TimedeltaIndex(dti)
|
||||
|
||||
with pytest.raises(TypeError, match=msg):
|
||||
TimedeltaIndex(np.asarray(dti))
|
||||
|
||||
def test_float64_ns_rounded(self):
|
||||
# GH#23539 without specifying a unit, floats are regarded as nanos,
|
||||
# and fractional portions are truncated
|
||||
tdi = TimedeltaIndex([2.3, 9.7])
|
||||
expected = TimedeltaIndex([2, 9])
|
||||
tm.assert_index_equal(tdi, expected)
|
||||
|
||||
# integral floats are non-lossy
|
||||
tdi = TimedeltaIndex([2.0, 9.0])
|
||||
expected = TimedeltaIndex([2, 9])
|
||||
tm.assert_index_equal(tdi, expected)
|
||||
|
||||
# NaNs get converted to NaT
|
||||
tdi = TimedeltaIndex([2.0, np.nan])
|
||||
expected = TimedeltaIndex([Timedelta(nanoseconds=2), pd.NaT])
|
||||
tm.assert_index_equal(tdi, expected)
|
||||
|
||||
def test_float64_unit_conversion(self):
|
||||
# GH#23539
|
||||
tdi = TimedeltaIndex([1.5, 2.25], unit="D")
|
||||
expected = TimedeltaIndex([Timedelta(days=1.5), Timedelta(days=2.25)])
|
||||
tm.assert_index_equal(tdi, expected)
|
||||
|
||||
def test_construction_base_constructor(self):
|
||||
arr = [Timedelta("1 days"), pd.NaT, Timedelta("3 days")]
|
||||
tm.assert_index_equal(pd.Index(arr), TimedeltaIndex(arr))
|
||||
tm.assert_index_equal(pd.Index(np.array(arr)), TimedeltaIndex(np.array(arr)))
|
||||
|
||||
arr = [np.nan, pd.NaT, Timedelta("1 days")]
|
||||
tm.assert_index_equal(pd.Index(arr), TimedeltaIndex(arr))
|
||||
tm.assert_index_equal(pd.Index(np.array(arr)), TimedeltaIndex(np.array(arr)))
|
||||
|
||||
def test_constructor(self):
|
||||
expected = TimedeltaIndex(
|
||||
[
|
||||
"1 days",
|
||||
"1 days 00:00:05",
|
||||
"2 days",
|
||||
"2 days 00:00:02",
|
||||
"0 days 00:00:03",
|
||||
]
|
||||
)
|
||||
result = TimedeltaIndex(
|
||||
[
|
||||
"1 days",
|
||||
"1 days, 00:00:05",
|
||||
np.timedelta64(2, "D"),
|
||||
timedelta(days=2, seconds=2),
|
||||
pd.offsets.Second(3),
|
||||
]
|
||||
)
|
||||
tm.assert_index_equal(result, expected)
|
||||
|
||||
# unicode
|
||||
result = TimedeltaIndex(
|
||||
[
|
||||
"1 days",
|
||||
"1 days, 00:00:05",
|
||||
np.timedelta64(2, "D"),
|
||||
timedelta(days=2, seconds=2),
|
||||
pd.offsets.Second(3),
|
||||
]
|
||||
)
|
||||
|
||||
expected = TimedeltaIndex(
|
||||
["0 days 00:00:00", "0 days 00:00:01", "0 days 00:00:02"]
|
||||
)
|
||||
tm.assert_index_equal(TimedeltaIndex(range(3), unit="s"), expected)
|
||||
expected = TimedeltaIndex(
|
||||
["0 days 00:00:00", "0 days 00:00:05", "0 days 00:00:09"]
|
||||
)
|
||||
tm.assert_index_equal(TimedeltaIndex([0, 5, 9], unit="s"), expected)
|
||||
expected = TimedeltaIndex(
|
||||
["0 days 00:00:00.400", "0 days 00:00:00.450", "0 days 00:00:01.200"]
|
||||
)
|
||||
tm.assert_index_equal(TimedeltaIndex([400, 450, 1200], unit="ms"), expected)
|
||||
|
||||
def test_constructor_iso(self):
|
||||
# GH #21877
|
||||
expected = timedelta_range("1s", periods=9, freq="s")
|
||||
durations = [f"P0DT0H0M{i}S" for i in range(1, 10)]
|
||||
result = to_timedelta(durations)
|
||||
tm.assert_index_equal(result, expected)
|
||||
|
||||
def test_constructor_coverage(self):
|
||||
rng = timedelta_range("1 days", periods=10.5)
|
||||
exp = timedelta_range("1 days", periods=10)
|
||||
tm.assert_index_equal(rng, exp)
|
||||
|
||||
msg = "periods must be a number, got foo"
|
||||
with pytest.raises(TypeError, match=msg):
|
||||
timedelta_range(start="1 days", periods="foo", freq="D")
|
||||
|
||||
msg = (
|
||||
r"TimedeltaIndex\(\.\.\.\) must be called with a collection of some kind, "
|
||||
"'1 days' was passed"
|
||||
)
|
||||
with pytest.raises(TypeError, match=msg):
|
||||
TimedeltaIndex("1 days")
|
||||
|
||||
# generator expression
|
||||
gen = (timedelta(i) for i in range(10))
|
||||
result = TimedeltaIndex(gen)
|
||||
expected = TimedeltaIndex([timedelta(i) for i in range(10)])
|
||||
tm.assert_index_equal(result, expected)
|
||||
|
||||
# NumPy string array
|
||||
strings = np.array(["1 days", "2 days", "3 days"])
|
||||
result = TimedeltaIndex(strings)
|
||||
expected = to_timedelta([1, 2, 3], unit="d")
|
||||
tm.assert_index_equal(result, expected)
|
||||
|
||||
from_ints = TimedeltaIndex(expected.asi8)
|
||||
tm.assert_index_equal(from_ints, expected)
|
||||
|
||||
# non-conforming freq
|
||||
msg = (
|
||||
"Inferred frequency None from passed values does not conform to "
|
||||
"passed frequency D"
|
||||
)
|
||||
with pytest.raises(ValueError, match=msg):
|
||||
TimedeltaIndex(["1 days", "2 days", "4 days"], freq="D")
|
||||
|
||||
msg = (
|
||||
"Of the four parameters: start, end, periods, and freq, exactly "
|
||||
"three must be specified"
|
||||
)
|
||||
with pytest.raises(ValueError, match=msg):
|
||||
timedelta_range(periods=10, freq="D")
|
||||
|
||||
def test_constructor_name(self):
|
||||
idx = timedelta_range(start="1 days", periods=1, freq="D", name="TEST")
|
||||
assert idx.name == "TEST"
|
||||
|
||||
# GH10025
|
||||
idx2 = TimedeltaIndex(idx, name="something else")
|
||||
assert idx2.name == "something else"
|
||||
|
||||
def test_constructor_no_precision_raises(self):
|
||||
# GH-24753, GH-24739
|
||||
|
||||
msg = "with no precision is not allowed"
|
||||
with pytest.raises(ValueError, match=msg):
|
||||
TimedeltaIndex(["2000"], dtype="timedelta64")
|
||||
|
||||
with pytest.raises(ValueError, match=msg):
|
||||
pd.Index(["2000"], dtype="timedelta64")
|
||||
|
||||
def test_constructor_wrong_precision_raises(self):
|
||||
msg = r"dtype timedelta64\[us\] cannot be converted to timedelta64\[ns\]"
|
||||
with pytest.raises(ValueError, match=msg):
|
||||
TimedeltaIndex(["2000"], dtype="timedelta64[us]")
|
||||
|
||||
def test_explicit_none_freq(self):
|
||||
# Explicitly passing freq=None is respected
|
||||
tdi = timedelta_range(1, periods=5)
|
||||
assert tdi.freq is not None
|
||||
|
||||
result = TimedeltaIndex(tdi, freq=None)
|
||||
assert result.freq is None
|
||||
|
||||
result = TimedeltaIndex(tdi._data, freq=None)
|
||||
assert result.freq is None
|
||||
|
||||
def test_from_categorical(self):
|
||||
tdi = timedelta_range(1, periods=5)
|
||||
|
||||
cat = pd.Categorical(tdi)
|
||||
|
||||
result = TimedeltaIndex(cat)
|
||||
tm.assert_index_equal(result, tdi)
|
||||
|
||||
ci = pd.CategoricalIndex(tdi)
|
||||
result = TimedeltaIndex(ci)
|
||||
tm.assert_index_equal(result, tdi)
|
||||
@ -0,0 +1,71 @@
|
||||
from pandas import (
|
||||
TimedeltaIndex,
|
||||
timedelta_range,
|
||||
)
|
||||
import pandas._testing as tm
|
||||
|
||||
|
||||
class TestTimedeltaIndexDelete:
|
||||
def test_delete(self):
|
||||
idx = timedelta_range(start="1 Days", periods=5, freq="D", name="idx")
|
||||
|
||||
# preserve freq
|
||||
expected_0 = timedelta_range(start="2 Days", periods=4, freq="D", name="idx")
|
||||
expected_4 = timedelta_range(start="1 Days", periods=4, freq="D", name="idx")
|
||||
|
||||
# reset freq to None
|
||||
expected_1 = TimedeltaIndex(
|
||||
["1 day", "3 day", "4 day", "5 day"], freq=None, name="idx"
|
||||
)
|
||||
|
||||
cases = {
|
||||
0: expected_0,
|
||||
-5: expected_0,
|
||||
-1: expected_4,
|
||||
4: expected_4,
|
||||
1: expected_1,
|
||||
}
|
||||
for n, expected in cases.items():
|
||||
result = idx.delete(n)
|
||||
tm.assert_index_equal(result, expected)
|
||||
assert result.name == expected.name
|
||||
assert result.freq == expected.freq
|
||||
|
||||
with tm.external_error_raised((IndexError, ValueError)):
|
||||
# either depending on numpy version
|
||||
idx.delete(5)
|
||||
|
||||
def test_delete_slice(self):
|
||||
idx = timedelta_range(start="1 days", periods=10, freq="D", name="idx")
|
||||
|
||||
# preserve freq
|
||||
expected_0_2 = timedelta_range(start="4 days", periods=7, freq="D", name="idx")
|
||||
expected_7_9 = timedelta_range(start="1 days", periods=7, freq="D", name="idx")
|
||||
|
||||
# reset freq to None
|
||||
expected_3_5 = TimedeltaIndex(
|
||||
["1 d", "2 d", "3 d", "7 d", "8 d", "9 d", "10d"], freq=None, name="idx"
|
||||
)
|
||||
|
||||
cases = {
|
||||
(0, 1, 2): expected_0_2,
|
||||
(7, 8, 9): expected_7_9,
|
||||
(3, 4, 5): expected_3_5,
|
||||
}
|
||||
for n, expected in cases.items():
|
||||
result = idx.delete(n)
|
||||
tm.assert_index_equal(result, expected)
|
||||
assert result.name == expected.name
|
||||
assert result.freq == expected.freq
|
||||
|
||||
result = idx.delete(slice(n[0], n[-1] + 1))
|
||||
tm.assert_index_equal(result, expected)
|
||||
assert result.name == expected.name
|
||||
assert result.freq == expected.freq
|
||||
|
||||
def test_delete_doesnt_infer_freq(self):
|
||||
# GH#30655 behavior matches DatetimeIndex
|
||||
|
||||
tdi = TimedeltaIndex(["1 Day", "2 Days", None, "3 Days", "4 Days"])
|
||||
result = tdi.delete(2)
|
||||
assert result.freq is None
|
||||
@ -0,0 +1,93 @@
|
||||
import pytest
|
||||
|
||||
import pandas as pd
|
||||
from pandas import (
|
||||
Series,
|
||||
TimedeltaIndex,
|
||||
)
|
||||
|
||||
|
||||
class TestTimedeltaIndexRendering:
|
||||
@pytest.mark.parametrize("method", ["__repr__", "__str__"])
|
||||
def test_representation(self, method):
|
||||
idx1 = TimedeltaIndex([], freq="D")
|
||||
idx2 = TimedeltaIndex(["1 days"], freq="D")
|
||||
idx3 = TimedeltaIndex(["1 days", "2 days"], freq="D")
|
||||
idx4 = TimedeltaIndex(["1 days", "2 days", "3 days"], freq="D")
|
||||
idx5 = TimedeltaIndex(["1 days 00:00:01", "2 days", "3 days"])
|
||||
|
||||
exp1 = "TimedeltaIndex([], dtype='timedelta64[ns]', freq='D')"
|
||||
|
||||
exp2 = "TimedeltaIndex(['1 days'], dtype='timedelta64[ns]', freq='D')"
|
||||
|
||||
exp3 = "TimedeltaIndex(['1 days', '2 days'], dtype='timedelta64[ns]', freq='D')"
|
||||
|
||||
exp4 = (
|
||||
"TimedeltaIndex(['1 days', '2 days', '3 days'], "
|
||||
"dtype='timedelta64[ns]', freq='D')"
|
||||
)
|
||||
|
||||
exp5 = (
|
||||
"TimedeltaIndex(['1 days 00:00:01', '2 days 00:00:00', "
|
||||
"'3 days 00:00:00'], dtype='timedelta64[ns]', freq=None)"
|
||||
)
|
||||
|
||||
with pd.option_context("display.width", 300):
|
||||
for idx, expected in zip(
|
||||
[idx1, idx2, idx3, idx4, idx5], [exp1, exp2, exp3, exp4, exp5]
|
||||
):
|
||||
result = getattr(idx, method)()
|
||||
assert result == expected
|
||||
|
||||
def test_representation_to_series(self):
|
||||
idx1 = TimedeltaIndex([], freq="D")
|
||||
idx2 = TimedeltaIndex(["1 days"], freq="D")
|
||||
idx3 = TimedeltaIndex(["1 days", "2 days"], freq="D")
|
||||
idx4 = TimedeltaIndex(["1 days", "2 days", "3 days"], freq="D")
|
||||
idx5 = TimedeltaIndex(["1 days 00:00:01", "2 days", "3 days"])
|
||||
|
||||
exp1 = """Series([], dtype: timedelta64[ns])"""
|
||||
|
||||
exp2 = "0 1 days\ndtype: timedelta64[ns]"
|
||||
|
||||
exp3 = "0 1 days\n1 2 days\ndtype: timedelta64[ns]"
|
||||
|
||||
exp4 = "0 1 days\n1 2 days\n2 3 days\ndtype: timedelta64[ns]"
|
||||
|
||||
exp5 = (
|
||||
"0 1 days 00:00:01\n"
|
||||
"1 2 days 00:00:00\n"
|
||||
"2 3 days 00:00:00\n"
|
||||
"dtype: timedelta64[ns]"
|
||||
)
|
||||
|
||||
with pd.option_context("display.width", 300):
|
||||
for idx, expected in zip(
|
||||
[idx1, idx2, idx3, idx4, idx5], [exp1, exp2, exp3, exp4, exp5]
|
||||
):
|
||||
result = repr(Series(idx))
|
||||
assert result == expected
|
||||
|
||||
def test_summary(self):
|
||||
# GH#9116
|
||||
idx1 = TimedeltaIndex([], freq="D")
|
||||
idx2 = TimedeltaIndex(["1 days"], freq="D")
|
||||
idx3 = TimedeltaIndex(["1 days", "2 days"], freq="D")
|
||||
idx4 = TimedeltaIndex(["1 days", "2 days", "3 days"], freq="D")
|
||||
idx5 = TimedeltaIndex(["1 days 00:00:01", "2 days", "3 days"])
|
||||
|
||||
exp1 = "TimedeltaIndex: 0 entries\nFreq: D"
|
||||
|
||||
exp2 = "TimedeltaIndex: 1 entries, 1 days to 1 days\nFreq: D"
|
||||
|
||||
exp3 = "TimedeltaIndex: 2 entries, 1 days to 2 days\nFreq: D"
|
||||
|
||||
exp4 = "TimedeltaIndex: 3 entries, 1 days to 3 days\nFreq: D"
|
||||
|
||||
exp5 = "TimedeltaIndex: 3 entries, 1 days 00:00:01 to 3 days 00:00:00"
|
||||
|
||||
for idx, expected in zip(
|
||||
[idx1, idx2, idx3, idx4, idx5], [exp1, exp2, exp3, exp4, exp5]
|
||||
):
|
||||
result = idx._summary()
|
||||
assert result == expected
|
||||
@ -0,0 +1,61 @@
|
||||
import pytest
|
||||
|
||||
from pandas import TimedeltaIndex
|
||||
|
||||
from pandas.tseries.offsets import (
|
||||
DateOffset,
|
||||
Day,
|
||||
Hour,
|
||||
)
|
||||
|
||||
|
||||
class TestFreq:
|
||||
@pytest.mark.parametrize("values", [["0 days", "2 days", "4 days"], []])
|
||||
@pytest.mark.parametrize("freq", ["2D", Day(2), "48H", Hour(48)])
|
||||
def test_freq_setter(self, values, freq):
|
||||
# GH#20678
|
||||
idx = TimedeltaIndex(values)
|
||||
|
||||
# can set to an offset, converting from string if necessary
|
||||
idx._data.freq = freq
|
||||
assert idx.freq == freq
|
||||
assert isinstance(idx.freq, DateOffset)
|
||||
|
||||
# can reset to None
|
||||
idx._data.freq = None
|
||||
assert idx.freq is None
|
||||
|
||||
def test_freq_setter_errors(self):
|
||||
# GH#20678
|
||||
idx = TimedeltaIndex(["0 days", "2 days", "4 days"])
|
||||
|
||||
# setting with an incompatible freq
|
||||
msg = (
|
||||
"Inferred frequency 2D from passed values does not conform to "
|
||||
"passed frequency 5D"
|
||||
)
|
||||
with pytest.raises(ValueError, match=msg):
|
||||
idx._data.freq = "5D"
|
||||
|
||||
# setting with a non-fixed frequency
|
||||
msg = r"<2 \* BusinessDays> is a non-fixed frequency"
|
||||
with pytest.raises(ValueError, match=msg):
|
||||
idx._data.freq = "2B"
|
||||
|
||||
# setting with non-freq string
|
||||
with pytest.raises(ValueError, match="Invalid frequency"):
|
||||
idx._data.freq = "foo"
|
||||
|
||||
def test_freq_view_safe(self):
|
||||
# Setting the freq for one TimedeltaIndex shouldn't alter the freq
|
||||
# for another that views the same data
|
||||
|
||||
tdi = TimedeltaIndex(["0 days", "2 days", "4 days"], freq="2D")
|
||||
tda = tdi._data
|
||||
|
||||
tdi2 = TimedeltaIndex(tda)._with_freq(None)
|
||||
assert tdi2.freq is None
|
||||
|
||||
# Original was not altered
|
||||
assert tdi.freq == "2D"
|
||||
assert tda.freq == "2D"
|
||||
@ -0,0 +1,348 @@
|
||||
from datetime import (
|
||||
datetime,
|
||||
timedelta,
|
||||
)
|
||||
import re
|
||||
|
||||
import numpy as np
|
||||
import pytest
|
||||
|
||||
from pandas import (
|
||||
Index,
|
||||
NaT,
|
||||
Timedelta,
|
||||
TimedeltaIndex,
|
||||
Timestamp,
|
||||
notna,
|
||||
timedelta_range,
|
||||
to_timedelta,
|
||||
)
|
||||
import pandas._testing as tm
|
||||
|
||||
|
||||
class TestGetItem:
|
||||
def test_getitem_slice_keeps_name(self):
|
||||
# GH#4226
|
||||
tdi = timedelta_range("1d", "5d", freq="H", name="timebucket")
|
||||
assert tdi[1:].name == tdi.name
|
||||
|
||||
def test_getitem(self):
|
||||
idx1 = timedelta_range("1 day", "31 day", freq="D", name="idx")
|
||||
|
||||
for idx in [idx1]:
|
||||
result = idx[0]
|
||||
assert result == Timedelta("1 day")
|
||||
|
||||
result = idx[0:5]
|
||||
expected = timedelta_range("1 day", "5 day", freq="D", name="idx")
|
||||
tm.assert_index_equal(result, expected)
|
||||
assert result.freq == expected.freq
|
||||
|
||||
result = idx[0:10:2]
|
||||
expected = timedelta_range("1 day", "9 day", freq="2D", name="idx")
|
||||
tm.assert_index_equal(result, expected)
|
||||
assert result.freq == expected.freq
|
||||
|
||||
result = idx[-20:-5:3]
|
||||
expected = timedelta_range("12 day", "24 day", freq="3D", name="idx")
|
||||
tm.assert_index_equal(result, expected)
|
||||
assert result.freq == expected.freq
|
||||
|
||||
result = idx[4::-1]
|
||||
expected = TimedeltaIndex(
|
||||
["5 day", "4 day", "3 day", "2 day", "1 day"], freq="-1D", name="idx"
|
||||
)
|
||||
tm.assert_index_equal(result, expected)
|
||||
assert result.freq == expected.freq
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"key",
|
||||
[
|
||||
Timestamp("1970-01-01"),
|
||||
Timestamp("1970-01-02"),
|
||||
datetime(1970, 1, 1),
|
||||
Timestamp("1970-01-03").to_datetime64(),
|
||||
# non-matching NA values
|
||||
np.datetime64("NaT"),
|
||||
],
|
||||
)
|
||||
def test_timestamp_invalid_key(self, key):
|
||||
# GH#20464
|
||||
tdi = timedelta_range(0, periods=10)
|
||||
with pytest.raises(KeyError, match=re.escape(repr(key))):
|
||||
tdi.get_loc(key)
|
||||
|
||||
|
||||
class TestGetLoc:
|
||||
@pytest.mark.filterwarnings("ignore:Passing method:FutureWarning")
|
||||
def test_get_loc(self):
|
||||
idx = to_timedelta(["0 days", "1 days", "2 days"])
|
||||
|
||||
for method in [None, "pad", "backfill", "nearest"]:
|
||||
assert idx.get_loc(idx[1], method) == 1
|
||||
assert idx.get_loc(idx[1].to_pytimedelta(), method) == 1
|
||||
assert idx.get_loc(str(idx[1]), method) == 1
|
||||
|
||||
assert idx.get_loc(idx[1], "pad", tolerance=Timedelta(0)) == 1
|
||||
assert idx.get_loc(idx[1], "pad", tolerance=np.timedelta64(0, "s")) == 1
|
||||
assert idx.get_loc(idx[1], "pad", tolerance=timedelta(0)) == 1
|
||||
|
||||
with pytest.raises(ValueError, match="unit abbreviation w/o a number"):
|
||||
idx.get_loc(idx[1], method="nearest", tolerance="foo")
|
||||
|
||||
with pytest.raises(ValueError, match="tolerance size must match"):
|
||||
idx.get_loc(
|
||||
idx[1],
|
||||
method="nearest",
|
||||
tolerance=[
|
||||
Timedelta(0).to_timedelta64(),
|
||||
Timedelta(0).to_timedelta64(),
|
||||
],
|
||||
)
|
||||
|
||||
for method, loc in [("pad", 1), ("backfill", 2), ("nearest", 1)]:
|
||||
assert idx.get_loc("1 day 1 hour", method) == loc
|
||||
|
||||
# GH 16909
|
||||
assert idx.get_loc(idx[1].to_timedelta64()) == 1
|
||||
|
||||
# GH 16896
|
||||
assert idx.get_loc("0 days") == 0
|
||||
|
||||
def test_get_loc_nat(self):
|
||||
tidx = TimedeltaIndex(["1 days 01:00:00", "NaT", "2 days 01:00:00"])
|
||||
|
||||
assert tidx.get_loc(NaT) == 1
|
||||
assert tidx.get_loc(None) == 1
|
||||
assert tidx.get_loc(float("nan")) == 1
|
||||
assert tidx.get_loc(np.nan) == 1
|
||||
|
||||
|
||||
class TestGetIndexer:
|
||||
def test_get_indexer(self):
|
||||
idx = to_timedelta(["0 days", "1 days", "2 days"])
|
||||
tm.assert_numpy_array_equal(
|
||||
idx.get_indexer(idx), np.array([0, 1, 2], dtype=np.intp)
|
||||
)
|
||||
|
||||
target = to_timedelta(["-1 hour", "12 hours", "1 day 1 hour"])
|
||||
tm.assert_numpy_array_equal(
|
||||
idx.get_indexer(target, "pad"), np.array([-1, 0, 1], dtype=np.intp)
|
||||
)
|
||||
tm.assert_numpy_array_equal(
|
||||
idx.get_indexer(target, "backfill"), np.array([0, 1, 2], dtype=np.intp)
|
||||
)
|
||||
tm.assert_numpy_array_equal(
|
||||
idx.get_indexer(target, "nearest"), np.array([0, 1, 1], dtype=np.intp)
|
||||
)
|
||||
|
||||
res = idx.get_indexer(target, "nearest", tolerance=Timedelta("1 hour"))
|
||||
tm.assert_numpy_array_equal(res, np.array([0, -1, 1], dtype=np.intp))
|
||||
|
||||
|
||||
class TestWhere:
|
||||
def test_where_doesnt_retain_freq(self):
|
||||
tdi = timedelta_range("1 day", periods=3, freq="D", name="idx")
|
||||
cond = [True, True, False]
|
||||
expected = TimedeltaIndex([tdi[0], tdi[1], tdi[0]], freq=None, name="idx")
|
||||
|
||||
result = tdi.where(cond, tdi[::-1])
|
||||
tm.assert_index_equal(result, expected)
|
||||
|
||||
def test_where_invalid_dtypes(self, fixed_now_ts):
|
||||
tdi = timedelta_range("1 day", periods=3, freq="D", name="idx")
|
||||
|
||||
tail = tdi[2:].tolist()
|
||||
i2 = Index([NaT, NaT] + tail)
|
||||
mask = notna(i2)
|
||||
|
||||
expected = Index([NaT.value, NaT.value] + tail, dtype=object, name="idx")
|
||||
assert isinstance(expected[0], int)
|
||||
result = tdi.where(mask, i2.asi8)
|
||||
tm.assert_index_equal(result, expected)
|
||||
|
||||
ts = i2 + fixed_now_ts
|
||||
expected = Index([ts[0], ts[1]] + tail, dtype=object, name="idx")
|
||||
result = tdi.where(mask, ts)
|
||||
tm.assert_index_equal(result, expected)
|
||||
|
||||
per = (i2 + fixed_now_ts).to_period("D")
|
||||
expected = Index([per[0], per[1]] + tail, dtype=object, name="idx")
|
||||
result = tdi.where(mask, per)
|
||||
tm.assert_index_equal(result, expected)
|
||||
|
||||
ts = fixed_now_ts
|
||||
expected = Index([ts, ts] + tail, dtype=object, name="idx")
|
||||
result = tdi.where(mask, ts)
|
||||
tm.assert_index_equal(result, expected)
|
||||
|
||||
def test_where_mismatched_nat(self):
|
||||
tdi = timedelta_range("1 day", periods=3, freq="D", name="idx")
|
||||
cond = np.array([True, False, False])
|
||||
|
||||
dtnat = np.datetime64("NaT", "ns")
|
||||
expected = Index([tdi[0], dtnat, dtnat], dtype=object, name="idx")
|
||||
assert expected[2] is dtnat
|
||||
result = tdi.where(cond, dtnat)
|
||||
tm.assert_index_equal(result, expected)
|
||||
|
||||
|
||||
class TestTake:
|
||||
def test_take(self):
|
||||
# GH 10295
|
||||
idx1 = timedelta_range("1 day", "31 day", freq="D", name="idx")
|
||||
|
||||
for idx in [idx1]:
|
||||
result = idx.take([0])
|
||||
assert result == Timedelta("1 day")
|
||||
|
||||
result = idx.take([-1])
|
||||
assert result == Timedelta("31 day")
|
||||
|
||||
result = idx.take([0, 1, 2])
|
||||
expected = timedelta_range("1 day", "3 day", freq="D", name="idx")
|
||||
tm.assert_index_equal(result, expected)
|
||||
assert result.freq == expected.freq
|
||||
|
||||
result = idx.take([0, 2, 4])
|
||||
expected = timedelta_range("1 day", "5 day", freq="2D", name="idx")
|
||||
tm.assert_index_equal(result, expected)
|
||||
assert result.freq == expected.freq
|
||||
|
||||
result = idx.take([7, 4, 1])
|
||||
expected = timedelta_range("8 day", "2 day", freq="-3D", name="idx")
|
||||
tm.assert_index_equal(result, expected)
|
||||
assert result.freq == expected.freq
|
||||
|
||||
result = idx.take([3, 2, 5])
|
||||
expected = TimedeltaIndex(["4 day", "3 day", "6 day"], name="idx")
|
||||
tm.assert_index_equal(result, expected)
|
||||
assert result.freq is None
|
||||
|
||||
result = idx.take([-3, 2, 5])
|
||||
expected = TimedeltaIndex(["29 day", "3 day", "6 day"], name="idx")
|
||||
tm.assert_index_equal(result, expected)
|
||||
assert result.freq is None
|
||||
|
||||
def test_take_invalid_kwargs(self):
|
||||
idx = timedelta_range("1 day", "31 day", freq="D", name="idx")
|
||||
indices = [1, 6, 5, 9, 10, 13, 15, 3]
|
||||
|
||||
msg = r"take\(\) got an unexpected keyword argument 'foo'"
|
||||
with pytest.raises(TypeError, match=msg):
|
||||
idx.take(indices, foo=2)
|
||||
|
||||
msg = "the 'out' parameter is not supported"
|
||||
with pytest.raises(ValueError, match=msg):
|
||||
idx.take(indices, out=indices)
|
||||
|
||||
msg = "the 'mode' parameter is not supported"
|
||||
with pytest.raises(ValueError, match=msg):
|
||||
idx.take(indices, mode="clip")
|
||||
|
||||
def test_take_equiv_getitem(self):
|
||||
tds = ["1day 02:00:00", "1 day 04:00:00", "1 day 10:00:00"]
|
||||
idx = timedelta_range(start="1d", end="2d", freq="H", name="idx")
|
||||
expected = TimedeltaIndex(tds, freq=None, name="idx")
|
||||
|
||||
taken1 = idx.take([2, 4, 10])
|
||||
taken2 = idx[[2, 4, 10]]
|
||||
|
||||
for taken in [taken1, taken2]:
|
||||
tm.assert_index_equal(taken, expected)
|
||||
assert isinstance(taken, TimedeltaIndex)
|
||||
assert taken.freq is None
|
||||
assert taken.name == expected.name
|
||||
|
||||
def test_take_fill_value(self):
|
||||
# GH 12631
|
||||
idx = TimedeltaIndex(["1 days", "2 days", "3 days"], name="xxx")
|
||||
result = idx.take(np.array([1, 0, -1]))
|
||||
expected = TimedeltaIndex(["2 days", "1 days", "3 days"], name="xxx")
|
||||
tm.assert_index_equal(result, expected)
|
||||
|
||||
# fill_value
|
||||
result = idx.take(np.array([1, 0, -1]), fill_value=True)
|
||||
expected = TimedeltaIndex(["2 days", "1 days", "NaT"], name="xxx")
|
||||
tm.assert_index_equal(result, expected)
|
||||
|
||||
# allow_fill=False
|
||||
result = idx.take(np.array([1, 0, -1]), allow_fill=False, fill_value=True)
|
||||
expected = TimedeltaIndex(["2 days", "1 days", "3 days"], name="xxx")
|
||||
tm.assert_index_equal(result, expected)
|
||||
|
||||
msg = (
|
||||
"When allow_fill=True and fill_value is not None, "
|
||||
"all indices must be >= -1"
|
||||
)
|
||||
with pytest.raises(ValueError, match=msg):
|
||||
idx.take(np.array([1, 0, -2]), fill_value=True)
|
||||
with pytest.raises(ValueError, match=msg):
|
||||
idx.take(np.array([1, 0, -5]), fill_value=True)
|
||||
|
||||
msg = "index -5 is out of bounds for (axis 0 with )?size 3"
|
||||
with pytest.raises(IndexError, match=msg):
|
||||
idx.take(np.array([1, -5]))
|
||||
|
||||
|
||||
class TestMaybeCastSliceBound:
|
||||
@pytest.fixture(params=["increasing", "decreasing", None])
|
||||
def monotonic(self, request):
|
||||
return request.param
|
||||
|
||||
@pytest.fixture
|
||||
def tdi(self, monotonic):
|
||||
tdi = timedelta_range("1 Day", periods=10)
|
||||
if monotonic == "decreasing":
|
||||
tdi = tdi[::-1]
|
||||
elif monotonic is None:
|
||||
taker = np.arange(10, dtype=np.intp)
|
||||
np.random.shuffle(taker)
|
||||
tdi = tdi.take(taker)
|
||||
return tdi
|
||||
|
||||
def test_maybe_cast_slice_bound_invalid_str(self, tdi):
|
||||
# test the low-level _maybe_cast_slice_bound and that we get the
|
||||
# expected exception+message all the way up the stack
|
||||
msg = (
|
||||
"cannot do slice indexing on TimedeltaIndex with these "
|
||||
r"indexers \[foo\] of type str"
|
||||
)
|
||||
with pytest.raises(TypeError, match=msg):
|
||||
tdi._maybe_cast_slice_bound("foo", side="left")
|
||||
with pytest.raises(TypeError, match=msg):
|
||||
tdi.get_slice_bound("foo", side="left")
|
||||
with pytest.raises(TypeError, match=msg):
|
||||
tdi.slice_locs("foo", None, None)
|
||||
|
||||
def test_slice_invalid_str_with_timedeltaindex(
|
||||
self, tdi, frame_or_series, indexer_sl
|
||||
):
|
||||
obj = frame_or_series(range(10), index=tdi)
|
||||
|
||||
msg = (
|
||||
"cannot do slice indexing on TimedeltaIndex with these "
|
||||
r"indexers \[foo\] of type str"
|
||||
)
|
||||
with pytest.raises(TypeError, match=msg):
|
||||
indexer_sl(obj)["foo":]
|
||||
with pytest.raises(TypeError, match=msg):
|
||||
indexer_sl(obj)["foo":-1]
|
||||
with pytest.raises(TypeError, match=msg):
|
||||
indexer_sl(obj)[:"foo"]
|
||||
with pytest.raises(TypeError, match=msg):
|
||||
indexer_sl(obj)[tdi[0] : "foo"]
|
||||
|
||||
|
||||
class TestContains:
|
||||
def test_contains_nonunique(self):
|
||||
# GH#9512
|
||||
for vals in (
|
||||
[0, 1, 0],
|
||||
[0, 0, -1],
|
||||
[0, -1, -1],
|
||||
["00:01:00", "00:01:00", "00:02:00"],
|
||||
["00:01:00", "00:01:00", "00:00:01"],
|
||||
):
|
||||
idx = TimedeltaIndex(vals)
|
||||
assert idx[0] in idx
|
||||
@ -0,0 +1,53 @@
|
||||
import numpy as np
|
||||
|
||||
from pandas import (
|
||||
Index,
|
||||
Timedelta,
|
||||
timedelta_range,
|
||||
)
|
||||
import pandas._testing as tm
|
||||
|
||||
|
||||
class TestJoin:
|
||||
def test_append_join_nondatetimeindex(self):
|
||||
rng = timedelta_range("1 days", periods=10)
|
||||
idx = Index(["a", "b", "c", "d"])
|
||||
|
||||
result = rng.append(idx)
|
||||
assert isinstance(result[0], Timedelta)
|
||||
|
||||
# it works
|
||||
rng.join(idx, how="outer")
|
||||
|
||||
def test_join_self(self, join_type):
|
||||
index = timedelta_range("1 day", periods=10)
|
||||
joined = index.join(index, how=join_type)
|
||||
tm.assert_index_equal(index, joined)
|
||||
|
||||
def test_does_not_convert_mixed_integer(self):
|
||||
df = tm.makeCustomDataframe(
|
||||
10,
|
||||
10,
|
||||
data_gen_f=lambda *args, **kwargs: np.random.randn(),
|
||||
r_idx_type="i",
|
||||
c_idx_type="td",
|
||||
)
|
||||
str(df)
|
||||
|
||||
cols = df.columns.join(df.index, how="outer")
|
||||
joined = cols.join(df.columns)
|
||||
assert cols.dtype == np.dtype("O")
|
||||
assert cols.dtype == joined.dtype
|
||||
tm.assert_index_equal(cols, joined)
|
||||
|
||||
def test_join_preserves_freq(self):
|
||||
# GH#32157
|
||||
tdi = timedelta_range("1 day", periods=10)
|
||||
result = tdi[:5].join(tdi[5:], how="outer")
|
||||
assert result.freq == tdi.freq
|
||||
tm.assert_index_equal(result, tdi)
|
||||
|
||||
result = tdi[:5].join(tdi[6:], how="outer")
|
||||
assert result.freq is None
|
||||
expected = tdi.delete(5)
|
||||
tm.assert_index_equal(result, expected)
|
||||
@ -0,0 +1,14 @@
|
||||
from pandas import (
|
||||
TimedeltaIndex,
|
||||
timedelta_range,
|
||||
)
|
||||
import pandas._testing as tm
|
||||
|
||||
|
||||
class TestTimedeltaIndexOps:
|
||||
def test_infer_freq(self, freq_sample):
|
||||
# GH#11018
|
||||
idx = timedelta_range("1", freq=freq_sample, periods=10)
|
||||
result = TimedeltaIndex(idx.asi8, freq="infer")
|
||||
tm.assert_index_equal(idx, result)
|
||||
assert result.freq == freq_sample
|
||||
@ -0,0 +1,11 @@
|
||||
from pandas import timedelta_range
|
||||
import pandas._testing as tm
|
||||
|
||||
|
||||
class TestPickle:
|
||||
def test_pickle_after_set_freq(self):
|
||||
tdi = timedelta_range("1 day", periods=4, freq="s")
|
||||
tdi = tdi._with_freq(None)
|
||||
|
||||
res = tm.round_trip_pickle(tdi)
|
||||
tm.assert_index_equal(res, tdi)
|
||||
@ -0,0 +1,142 @@
|
||||
"""
|
||||
Tests for TimedeltaIndex methods behaving like their Timedelta counterparts
|
||||
"""
|
||||
|
||||
import numpy as np
|
||||
import pytest
|
||||
|
||||
from pandas._libs.tslibs.offsets import INVALID_FREQ_ERR_MSG
|
||||
|
||||
from pandas import (
|
||||
Index,
|
||||
Series,
|
||||
Timedelta,
|
||||
TimedeltaIndex,
|
||||
timedelta_range,
|
||||
)
|
||||
import pandas._testing as tm
|
||||
|
||||
|
||||
class TestVectorizedTimedelta:
|
||||
def test_tdi_total_seconds(self):
|
||||
# GH#10939
|
||||
# test index
|
||||
rng = timedelta_range("1 days, 10:11:12.100123456", periods=2, freq="s")
|
||||
expt = [
|
||||
1 * 86400 + 10 * 3600 + 11 * 60 + 12 + 100123456.0 / 1e9,
|
||||
1 * 86400 + 10 * 3600 + 11 * 60 + 13 + 100123456.0 / 1e9,
|
||||
]
|
||||
tm.assert_almost_equal(rng.total_seconds(), Index(expt))
|
||||
|
||||
# test Series
|
||||
ser = Series(rng)
|
||||
s_expt = Series(expt, index=[0, 1])
|
||||
tm.assert_series_equal(ser.dt.total_seconds(), s_expt)
|
||||
|
||||
# with nat
|
||||
ser[1] = np.nan
|
||||
s_expt = Series(
|
||||
[1 * 86400 + 10 * 3600 + 11 * 60 + 12 + 100123456.0 / 1e9, np.nan],
|
||||
index=[0, 1],
|
||||
)
|
||||
tm.assert_series_equal(ser.dt.total_seconds(), s_expt)
|
||||
|
||||
# with both nat
|
||||
ser = Series([np.nan, np.nan], dtype="timedelta64[ns]")
|
||||
tm.assert_series_equal(
|
||||
ser.dt.total_seconds(), Series([np.nan, np.nan], index=[0, 1])
|
||||
)
|
||||
|
||||
def test_tdi_round(self):
|
||||
td = timedelta_range(start="16801 days", periods=5, freq="30Min")
|
||||
elt = td[1]
|
||||
|
||||
expected_rng = TimedeltaIndex(
|
||||
[
|
||||
Timedelta("16801 days 00:00:00"),
|
||||
Timedelta("16801 days 00:00:00"),
|
||||
Timedelta("16801 days 01:00:00"),
|
||||
Timedelta("16801 days 02:00:00"),
|
||||
Timedelta("16801 days 02:00:00"),
|
||||
]
|
||||
)
|
||||
expected_elt = expected_rng[1]
|
||||
|
||||
tm.assert_index_equal(td.round(freq="H"), expected_rng)
|
||||
assert elt.round(freq="H") == expected_elt
|
||||
|
||||
msg = INVALID_FREQ_ERR_MSG
|
||||
with pytest.raises(ValueError, match=msg):
|
||||
td.round(freq="foo")
|
||||
with pytest.raises(ValueError, match=msg):
|
||||
elt.round(freq="foo")
|
||||
|
||||
msg = "<MonthEnd> is a non-fixed frequency"
|
||||
with pytest.raises(ValueError, match=msg):
|
||||
td.round(freq="M")
|
||||
with pytest.raises(ValueError, match=msg):
|
||||
elt.round(freq="M")
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"freq,msg",
|
||||
[
|
||||
("Y", "<YearEnd: month=12> is a non-fixed frequency"),
|
||||
("M", "<MonthEnd> is a non-fixed frequency"),
|
||||
("foobar", "Invalid frequency: foobar"),
|
||||
],
|
||||
)
|
||||
def test_tdi_round_invalid(self, freq, msg):
|
||||
t1 = timedelta_range("1 days", periods=3, freq="1 min 2 s 3 us")
|
||||
|
||||
with pytest.raises(ValueError, match=msg):
|
||||
t1.round(freq)
|
||||
with pytest.raises(ValueError, match=msg):
|
||||
# Same test for TimedeltaArray
|
||||
t1._data.round(freq)
|
||||
|
||||
# TODO: de-duplicate with test_tdi_round
|
||||
def test_round(self):
|
||||
t1 = timedelta_range("1 days", periods=3, freq="1 min 2 s 3 us")
|
||||
t2 = -1 * t1
|
||||
t1a = timedelta_range("1 days", periods=3, freq="1 min 2 s")
|
||||
t1c = TimedeltaIndex([1, 1, 1], unit="D")
|
||||
|
||||
# note that negative times round DOWN! so don't give whole numbers
|
||||
for (freq, s1, s2) in [
|
||||
("N", t1, t2),
|
||||
("U", t1, t2),
|
||||
(
|
||||
"L",
|
||||
t1a,
|
||||
TimedeltaIndex(
|
||||
["-1 days +00:00:00", "-2 days +23:58:58", "-2 days +23:57:56"]
|
||||
),
|
||||
),
|
||||
(
|
||||
"S",
|
||||
t1a,
|
||||
TimedeltaIndex(
|
||||
["-1 days +00:00:00", "-2 days +23:58:58", "-2 days +23:57:56"]
|
||||
),
|
||||
),
|
||||
("12T", t1c, TimedeltaIndex(["-1 days", "-1 days", "-1 days"])),
|
||||
("H", t1c, TimedeltaIndex(["-1 days", "-1 days", "-1 days"])),
|
||||
("d", t1c, TimedeltaIndex([-1, -1, -1], unit="D")),
|
||||
]:
|
||||
|
||||
r1 = t1.round(freq)
|
||||
tm.assert_index_equal(r1, s1)
|
||||
r2 = t2.round(freq)
|
||||
tm.assert_index_equal(r2, s2)
|
||||
|
||||
def test_components(self):
|
||||
rng = timedelta_range("1 days, 10:11:12", periods=2, freq="s")
|
||||
rng.components
|
||||
|
||||
# with nat
|
||||
s = Series(rng)
|
||||
s[1] = np.nan
|
||||
|
||||
result = s.dt.components
|
||||
assert not result.iloc[0].isna().all()
|
||||
assert result.iloc[1].isna().all()
|
||||
@ -0,0 +1,28 @@
|
||||
import numpy as np
|
||||
import pytest
|
||||
|
||||
from pandas import (
|
||||
TimedeltaIndex,
|
||||
Timestamp,
|
||||
)
|
||||
import pandas._testing as tm
|
||||
|
||||
|
||||
class TestSearchSorted:
|
||||
def test_searchsorted_different_argument_classes(self, listlike_box):
|
||||
idx = TimedeltaIndex(["1 day", "2 days", "3 days"])
|
||||
result = idx.searchsorted(listlike_box(idx))
|
||||
expected = np.arange(len(idx), dtype=result.dtype)
|
||||
tm.assert_numpy_array_equal(result, expected)
|
||||
|
||||
result = idx._data.searchsorted(listlike_box(idx))
|
||||
tm.assert_numpy_array_equal(result, expected)
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"arg", [[1, 2], ["a", "b"], [Timestamp("2020-01-01", tz="Europe/London")] * 2]
|
||||
)
|
||||
def test_searchsorted_invalid_argument_dtype(self, arg):
|
||||
idx = TimedeltaIndex(["1 day", "2 days", "3 days"])
|
||||
msg = "value should be a 'Timedelta', 'NaT', or array of those. Got"
|
||||
with pytest.raises(TypeError, match=msg):
|
||||
idx.searchsorted(arg)
|
||||
@ -0,0 +1,260 @@
|
||||
import numpy as np
|
||||
import pytest
|
||||
|
||||
import pandas as pd
|
||||
from pandas import (
|
||||
TimedeltaIndex,
|
||||
timedelta_range,
|
||||
)
|
||||
import pandas._testing as tm
|
||||
from pandas.core.api import Int64Index
|
||||
|
||||
from pandas.tseries.offsets import Hour
|
||||
|
||||
|
||||
class TestTimedeltaIndex:
|
||||
def test_union(self):
|
||||
|
||||
i1 = timedelta_range("1day", periods=5)
|
||||
i2 = timedelta_range("3day", periods=5)
|
||||
result = i1.union(i2)
|
||||
expected = timedelta_range("1day", periods=7)
|
||||
tm.assert_index_equal(result, expected)
|
||||
|
||||
i1 = Int64Index(np.arange(0, 20, 2))
|
||||
i2 = timedelta_range(start="1 day", periods=10, freq="D")
|
||||
i1.union(i2) # Works
|
||||
i2.union(i1) # Fails with "AttributeError: can't set attribute"
|
||||
|
||||
def test_union_sort_false(self):
|
||||
tdi = timedelta_range("1day", periods=5)
|
||||
|
||||
left = tdi[3:]
|
||||
right = tdi[:3]
|
||||
|
||||
# Check that we are testing the desired code path
|
||||
assert left._can_fast_union(right)
|
||||
|
||||
result = left.union(right)
|
||||
tm.assert_index_equal(result, tdi)
|
||||
|
||||
result = left.union(right, sort=False)
|
||||
expected = TimedeltaIndex(["4 Days", "5 Days", "1 Days", "2 Day", "3 Days"])
|
||||
tm.assert_index_equal(result, expected)
|
||||
|
||||
def test_union_coverage(self):
|
||||
|
||||
idx = TimedeltaIndex(["3d", "1d", "2d"])
|
||||
ordered = TimedeltaIndex(idx.sort_values(), freq="infer")
|
||||
result = ordered.union(idx)
|
||||
tm.assert_index_equal(result, ordered)
|
||||
|
||||
result = ordered[:0].union(ordered)
|
||||
tm.assert_index_equal(result, ordered)
|
||||
assert result.freq == ordered.freq
|
||||
|
||||
def test_union_bug_1730(self):
|
||||
|
||||
rng_a = timedelta_range("1 day", periods=4, freq="3H")
|
||||
rng_b = timedelta_range("1 day", periods=4, freq="4H")
|
||||
|
||||
result = rng_a.union(rng_b)
|
||||
exp = TimedeltaIndex(sorted(set(rng_a) | set(rng_b)))
|
||||
tm.assert_index_equal(result, exp)
|
||||
|
||||
def test_union_bug_1745(self):
|
||||
|
||||
left = TimedeltaIndex(["1 day 15:19:49.695000"])
|
||||
right = TimedeltaIndex(
|
||||
["2 day 13:04:21.322000", "1 day 15:27:24.873000", "1 day 15:31:05.350000"]
|
||||
)
|
||||
|
||||
result = left.union(right)
|
||||
exp = TimedeltaIndex(sorted(set(left) | set(right)))
|
||||
tm.assert_index_equal(result, exp)
|
||||
|
||||
def test_union_bug_4564(self):
|
||||
|
||||
left = timedelta_range("1 day", "30d")
|
||||
right = left + pd.offsets.Minute(15)
|
||||
|
||||
result = left.union(right)
|
||||
exp = TimedeltaIndex(sorted(set(left) | set(right)))
|
||||
tm.assert_index_equal(result, exp)
|
||||
|
||||
def test_union_freq_infer(self):
|
||||
# When taking the union of two TimedeltaIndexes, we infer
|
||||
# a freq even if the arguments don't have freq. This matches
|
||||
# DatetimeIndex behavior.
|
||||
tdi = timedelta_range("1 Day", periods=5)
|
||||
left = tdi[[0, 1, 3, 4]]
|
||||
right = tdi[[2, 3, 1]]
|
||||
|
||||
assert left.freq is None
|
||||
assert right.freq is None
|
||||
|
||||
result = left.union(right)
|
||||
tm.assert_index_equal(result, tdi)
|
||||
assert result.freq == "D"
|
||||
|
||||
def test_intersection_bug_1708(self):
|
||||
index_1 = timedelta_range("1 day", periods=4, freq="h")
|
||||
index_2 = index_1 + pd.offsets.Hour(5)
|
||||
|
||||
with tm.assert_produces_warning(FutureWarning):
|
||||
result = index_1 & index_2
|
||||
assert len(result) == 0
|
||||
|
||||
index_1 = timedelta_range("1 day", periods=4, freq="h")
|
||||
index_2 = index_1 + pd.offsets.Hour(1)
|
||||
|
||||
with tm.assert_produces_warning(FutureWarning):
|
||||
result = index_1 & index_2
|
||||
expected = timedelta_range("1 day 01:00:00", periods=3, freq="h")
|
||||
tm.assert_index_equal(result, expected)
|
||||
assert result.freq == expected.freq
|
||||
|
||||
def test_intersection_equal(self, sort):
|
||||
# GH 24471 Test intersection outcome given the sort keyword
|
||||
# for equal indices intersection should return the original index
|
||||
first = timedelta_range("1 day", periods=4, freq="h")
|
||||
second = timedelta_range("1 day", periods=4, freq="h")
|
||||
intersect = first.intersection(second, sort=sort)
|
||||
if sort is None:
|
||||
tm.assert_index_equal(intersect, second.sort_values())
|
||||
assert tm.equalContents(intersect, second)
|
||||
|
||||
# Corner cases
|
||||
inter = first.intersection(first, sort=sort)
|
||||
assert inter is first
|
||||
|
||||
@pytest.mark.parametrize("period_1, period_2", [(0, 4), (4, 0)])
|
||||
def test_intersection_zero_length(self, period_1, period_2, sort):
|
||||
# GH 24471 test for non overlap the intersection should be zero length
|
||||
index_1 = timedelta_range("1 day", periods=period_1, freq="h")
|
||||
index_2 = timedelta_range("1 day", periods=period_2, freq="h")
|
||||
expected = timedelta_range("1 day", periods=0, freq="h")
|
||||
result = index_1.intersection(index_2, sort=sort)
|
||||
tm.assert_index_equal(result, expected)
|
||||
|
||||
def test_zero_length_input_index(self, sort):
|
||||
# GH 24966 test for 0-len intersections are copied
|
||||
index_1 = timedelta_range("1 day", periods=0, freq="h")
|
||||
index_2 = timedelta_range("1 day", periods=3, freq="h")
|
||||
result = index_1.intersection(index_2, sort=sort)
|
||||
assert index_1 is not result
|
||||
assert index_2 is not result
|
||||
tm.assert_copy(result, index_1)
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"rng, expected",
|
||||
# if target has the same name, it is preserved
|
||||
[
|
||||
(
|
||||
timedelta_range("1 day", periods=5, freq="h", name="idx"),
|
||||
timedelta_range("1 day", periods=4, freq="h", name="idx"),
|
||||
),
|
||||
# if target name is different, it will be reset
|
||||
(
|
||||
timedelta_range("1 day", periods=5, freq="h", name="other"),
|
||||
timedelta_range("1 day", periods=4, freq="h", name=None),
|
||||
),
|
||||
# if no overlap exists return empty index
|
||||
(
|
||||
timedelta_range("1 day", periods=10, freq="h", name="idx")[5:],
|
||||
TimedeltaIndex([], freq="h", name="idx"),
|
||||
),
|
||||
],
|
||||
)
|
||||
def test_intersection(self, rng, expected, sort):
|
||||
# GH 4690 (with tz)
|
||||
base = timedelta_range("1 day", periods=4, freq="h", name="idx")
|
||||
result = base.intersection(rng, sort=sort)
|
||||
if sort is None:
|
||||
expected = expected.sort_values()
|
||||
tm.assert_index_equal(result, expected)
|
||||
assert result.name == expected.name
|
||||
assert result.freq == expected.freq
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"rng, expected",
|
||||
# part intersection works
|
||||
[
|
||||
(
|
||||
TimedeltaIndex(["5 hour", "2 hour", "4 hour", "9 hour"], name="idx"),
|
||||
TimedeltaIndex(["2 hour", "4 hour"], name="idx"),
|
||||
),
|
||||
# reordered part intersection
|
||||
(
|
||||
TimedeltaIndex(["2 hour", "5 hour", "5 hour", "1 hour"], name="other"),
|
||||
TimedeltaIndex(["1 hour", "2 hour"], name=None),
|
||||
),
|
||||
# reversed index
|
||||
(
|
||||
TimedeltaIndex(["1 hour", "2 hour", "4 hour", "3 hour"], name="idx")[
|
||||
::-1
|
||||
],
|
||||
TimedeltaIndex(["1 hour", "2 hour", "4 hour", "3 hour"], name="idx"),
|
||||
),
|
||||
],
|
||||
)
|
||||
def test_intersection_non_monotonic(self, rng, expected, sort):
|
||||
# 24471 non-monotonic
|
||||
base = TimedeltaIndex(["1 hour", "2 hour", "4 hour", "3 hour"], name="idx")
|
||||
result = base.intersection(rng, sort=sort)
|
||||
if sort is None:
|
||||
expected = expected.sort_values()
|
||||
tm.assert_index_equal(result, expected)
|
||||
assert result.name == expected.name
|
||||
|
||||
# if reversed order, frequency is still the same
|
||||
if all(base == rng[::-1]) and sort is None:
|
||||
assert isinstance(result.freq, Hour)
|
||||
else:
|
||||
assert result.freq is None
|
||||
|
||||
|
||||
class TestTimedeltaIndexDifference:
|
||||
def test_difference_freq(self, sort):
|
||||
# GH14323: Difference of TimedeltaIndex should not preserve frequency
|
||||
|
||||
index = timedelta_range("0 days", "5 days", freq="D")
|
||||
|
||||
other = timedelta_range("1 days", "4 days", freq="D")
|
||||
expected = TimedeltaIndex(["0 days", "5 days"], freq=None)
|
||||
idx_diff = index.difference(other, sort)
|
||||
tm.assert_index_equal(idx_diff, expected)
|
||||
tm.assert_attr_equal("freq", idx_diff, expected)
|
||||
|
||||
other = timedelta_range("2 days", "5 days", freq="D")
|
||||
idx_diff = index.difference(other, sort)
|
||||
expected = TimedeltaIndex(["0 days", "1 days"], freq=None)
|
||||
tm.assert_index_equal(idx_diff, expected)
|
||||
tm.assert_attr_equal("freq", idx_diff, expected)
|
||||
|
||||
def test_difference_sort(self, sort):
|
||||
|
||||
index = TimedeltaIndex(
|
||||
["5 days", "3 days", "2 days", "4 days", "1 days", "0 days"]
|
||||
)
|
||||
|
||||
other = timedelta_range("1 days", "4 days", freq="D")
|
||||
idx_diff = index.difference(other, sort)
|
||||
|
||||
expected = TimedeltaIndex(["5 days", "0 days"], freq=None)
|
||||
|
||||
if sort is None:
|
||||
expected = expected.sort_values()
|
||||
|
||||
tm.assert_index_equal(idx_diff, expected)
|
||||
tm.assert_attr_equal("freq", idx_diff, expected)
|
||||
|
||||
other = timedelta_range("2 days", "5 days", freq="D")
|
||||
idx_diff = index.difference(other, sort)
|
||||
expected = TimedeltaIndex(["1 days", "0 days"], freq=None)
|
||||
|
||||
if sort is None:
|
||||
expected = expected.sort_values()
|
||||
|
||||
tm.assert_index_equal(idx_diff, expected)
|
||||
tm.assert_attr_equal("freq", idx_diff, expected)
|
||||
@ -0,0 +1,145 @@
|
||||
from datetime import timedelta
|
||||
|
||||
import numpy as np
|
||||
import pytest
|
||||
|
||||
import pandas as pd
|
||||
from pandas import (
|
||||
Index,
|
||||
NaT,
|
||||
Series,
|
||||
Timedelta,
|
||||
TimedeltaIndex,
|
||||
timedelta_range,
|
||||
)
|
||||
import pandas._testing as tm
|
||||
from pandas.core.indexes.api import Int64Index
|
||||
from pandas.tests.indexes.datetimelike import DatetimeLike
|
||||
|
||||
randn = np.random.randn
|
||||
|
||||
|
||||
class TestTimedeltaIndex(DatetimeLike):
|
||||
_index_cls = TimedeltaIndex
|
||||
|
||||
@pytest.fixture
|
||||
def simple_index(self) -> TimedeltaIndex:
|
||||
index = pd.to_timedelta(range(5), unit="d")._with_freq("infer")
|
||||
assert index.freq == "D"
|
||||
ret = index + pd.offsets.Hour(1)
|
||||
assert ret.freq == "D"
|
||||
return ret
|
||||
|
||||
@pytest.fixture
|
||||
def index(self):
|
||||
return tm.makeTimedeltaIndex(10)
|
||||
|
||||
def test_numeric_compat(self):
|
||||
# Dummy method to override super's version; this test is now done
|
||||
# in test_arithmetic.py
|
||||
pass
|
||||
|
||||
def test_shift(self):
|
||||
pass # this is handled in test_arithmetic.py
|
||||
|
||||
def test_misc_coverage(self):
|
||||
|
||||
rng = timedelta_range("1 day", periods=5)
|
||||
result = rng.groupby(rng.days)
|
||||
assert isinstance(list(result.values())[0][0], Timedelta)
|
||||
|
||||
def test_map(self):
|
||||
# test_map_dictlike generally tests
|
||||
|
||||
rng = timedelta_range("1 day", periods=10)
|
||||
|
||||
f = lambda x: x.days
|
||||
result = rng.map(f)
|
||||
exp = Int64Index([f(x) for x in rng])
|
||||
tm.assert_index_equal(result, exp)
|
||||
|
||||
def test_pass_TimedeltaIndex_to_index(self):
|
||||
|
||||
rng = timedelta_range("1 days", "10 days")
|
||||
idx = Index(rng, dtype=object)
|
||||
|
||||
expected = Index(rng.to_pytimedelta(), dtype=object)
|
||||
|
||||
tm.assert_numpy_array_equal(idx.values, expected.values)
|
||||
|
||||
def test_fields(self):
|
||||
rng = timedelta_range("1 days, 10:11:12.100123456", periods=2, freq="s")
|
||||
tm.assert_index_equal(rng.days, Index([1, 1], dtype="int64"))
|
||||
tm.assert_index_equal(
|
||||
rng.seconds,
|
||||
Index([10 * 3600 + 11 * 60 + 12, 10 * 3600 + 11 * 60 + 13], dtype="int64"),
|
||||
)
|
||||
tm.assert_index_equal(
|
||||
rng.microseconds, Index([100 * 1000 + 123, 100 * 1000 + 123], dtype="int64")
|
||||
)
|
||||
tm.assert_index_equal(rng.nanoseconds, Index([456, 456], dtype="int64"))
|
||||
|
||||
msg = "'TimedeltaIndex' object has no attribute '{}'"
|
||||
with pytest.raises(AttributeError, match=msg.format("hours")):
|
||||
rng.hours
|
||||
with pytest.raises(AttributeError, match=msg.format("minutes")):
|
||||
rng.minutes
|
||||
with pytest.raises(AttributeError, match=msg.format("milliseconds")):
|
||||
rng.milliseconds
|
||||
|
||||
# with nat
|
||||
s = Series(rng)
|
||||
s[1] = np.nan
|
||||
|
||||
tm.assert_series_equal(s.dt.days, Series([1, np.nan], index=[0, 1]))
|
||||
tm.assert_series_equal(
|
||||
s.dt.seconds, Series([10 * 3600 + 11 * 60 + 12, np.nan], index=[0, 1])
|
||||
)
|
||||
|
||||
# preserve name (GH15589)
|
||||
rng.name = "name"
|
||||
assert rng.days.name == "name"
|
||||
|
||||
def test_freq_conversion_always_floating(self):
|
||||
# even if we have no NaTs, we get back float64; this matches TDA and Series
|
||||
tdi = timedelta_range("1 Day", periods=30)
|
||||
|
||||
res = tdi.astype("m8[s]")
|
||||
expected = Index((tdi.view("i8") / 10**9).astype(np.float64))
|
||||
tm.assert_index_equal(res, expected)
|
||||
|
||||
# check this matches Series and TimedeltaArray
|
||||
res = tdi._data.astype("m8[s]")
|
||||
tm.assert_numpy_array_equal(res, expected._values)
|
||||
|
||||
res = tdi.to_series().astype("m8[s]")
|
||||
tm.assert_numpy_array_equal(res._values, expected._values)
|
||||
|
||||
def test_freq_conversion(self, index_or_series):
|
||||
|
||||
# doc example
|
||||
|
||||
scalar = Timedelta(days=31)
|
||||
td = index_or_series(
|
||||
[scalar, scalar, scalar + timedelta(minutes=5, seconds=3), NaT],
|
||||
dtype="m8[ns]",
|
||||
)
|
||||
|
||||
result = td / np.timedelta64(1, "D")
|
||||
expected = index_or_series(
|
||||
[31, 31, (31 * 86400 + 5 * 60 + 3) / 86400.0, np.nan]
|
||||
)
|
||||
tm.assert_equal(result, expected)
|
||||
|
||||
result = td.astype("timedelta64[D]")
|
||||
expected = index_or_series([31, 31, 31, np.nan])
|
||||
tm.assert_equal(result, expected)
|
||||
|
||||
result = td / np.timedelta64(1, "s")
|
||||
expected = index_or_series(
|
||||
[31 * 86400, 31 * 86400, 31 * 86400 + 5 * 60 + 3, np.nan]
|
||||
)
|
||||
tm.assert_equal(result, expected)
|
||||
|
||||
result = td.astype("timedelta64[s]")
|
||||
tm.assert_equal(result, expected)
|
||||
@ -0,0 +1,92 @@
|
||||
import numpy as np
|
||||
import pytest
|
||||
|
||||
from pandas import (
|
||||
Timedelta,
|
||||
timedelta_range,
|
||||
to_timedelta,
|
||||
)
|
||||
import pandas._testing as tm
|
||||
|
||||
from pandas.tseries.offsets import (
|
||||
Day,
|
||||
Second,
|
||||
)
|
||||
|
||||
|
||||
class TestTimedeltas:
|
||||
def test_timedelta_range(self):
|
||||
|
||||
expected = to_timedelta(np.arange(5), unit="D")
|
||||
result = timedelta_range("0 days", periods=5, freq="D")
|
||||
tm.assert_index_equal(result, expected)
|
||||
|
||||
expected = to_timedelta(np.arange(11), unit="D")
|
||||
result = timedelta_range("0 days", "10 days", freq="D")
|
||||
tm.assert_index_equal(result, expected)
|
||||
|
||||
expected = to_timedelta(np.arange(5), unit="D") + Second(2) + Day()
|
||||
result = timedelta_range("1 days, 00:00:02", "5 days, 00:00:02", freq="D")
|
||||
tm.assert_index_equal(result, expected)
|
||||
|
||||
expected = to_timedelta([1, 3, 5, 7, 9], unit="D") + Second(2)
|
||||
result = timedelta_range("1 days, 00:00:02", periods=5, freq="2D")
|
||||
tm.assert_index_equal(result, expected)
|
||||
|
||||
expected = to_timedelta(np.arange(50), unit="T") * 30
|
||||
result = timedelta_range("0 days", freq="30T", periods=50)
|
||||
tm.assert_index_equal(result, expected)
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"periods, freq", [(3, "2D"), (5, "D"), (6, "19H12T"), (7, "16H"), (9, "12H")]
|
||||
)
|
||||
def test_linspace_behavior(self, periods, freq):
|
||||
# GH 20976
|
||||
result = timedelta_range(start="0 days", end="4 days", periods=periods)
|
||||
expected = timedelta_range(start="0 days", end="4 days", freq=freq)
|
||||
tm.assert_index_equal(result, expected)
|
||||
|
||||
def test_errors(self):
|
||||
# not enough params
|
||||
msg = (
|
||||
"Of the four parameters: start, end, periods, and freq, "
|
||||
"exactly three must be specified"
|
||||
)
|
||||
with pytest.raises(ValueError, match=msg):
|
||||
timedelta_range(start="0 days")
|
||||
|
||||
with pytest.raises(ValueError, match=msg):
|
||||
timedelta_range(end="5 days")
|
||||
|
||||
with pytest.raises(ValueError, match=msg):
|
||||
timedelta_range(periods=2)
|
||||
|
||||
with pytest.raises(ValueError, match=msg):
|
||||
timedelta_range()
|
||||
|
||||
# too many params
|
||||
with pytest.raises(ValueError, match=msg):
|
||||
timedelta_range(start="0 days", end="5 days", periods=10, freq="H")
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"start, end, freq, expected_periods",
|
||||
[
|
||||
("1D", "10D", "2D", (10 - 1) // 2 + 1),
|
||||
("2D", "30D", "3D", (30 - 2) // 3 + 1),
|
||||
("2s", "50s", "5s", (50 - 2) // 5 + 1),
|
||||
# tests that worked before GH 33498:
|
||||
("4D", "16D", "3D", (16 - 4) // 3 + 1),
|
||||
("8D", "16D", "40s", (16 * 3600 * 24 - 8 * 3600 * 24) // 40 + 1),
|
||||
],
|
||||
)
|
||||
def test_timedelta_range_freq_divide_end(self, start, end, freq, expected_periods):
|
||||
# GH 33498 only the cases where `(end % freq) == 0` used to fail
|
||||
res = timedelta_range(start=start, end=end, freq=freq)
|
||||
assert Timedelta(start) == res[0]
|
||||
assert Timedelta(end) >= res[-1]
|
||||
assert len(res) == expected_periods
|
||||
|
||||
def test_timedelta_range_infer_freq(self):
|
||||
# https://github.com/pandas-dev/pandas/issues/35897
|
||||
result = timedelta_range("0s", "1s", periods=31)
|
||||
assert result.freq is None
|
||||
Reference in New Issue
Block a user