2476 lines
87 KiB
Python
2476 lines
87 KiB
Python
# Arithmetic tests for DataFrame/Series/Index/Array classes that should
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# behave identically.
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# Specifically for datetime64 and datetime64tz dtypes
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from datetime import (
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datetime,
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time,
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timedelta,
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)
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from itertools import (
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product,
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starmap,
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)
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import operator
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import warnings
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import numpy as np
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import pytest
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import pytz
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from pandas._libs.tslibs.conversion import localize_pydatetime
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from pandas._libs.tslibs.offsets import shift_months
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from pandas.errors import PerformanceWarning
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import pandas as pd
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from pandas import (
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DateOffset,
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DatetimeIndex,
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NaT,
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Period,
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Series,
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Timedelta,
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TimedeltaIndex,
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Timestamp,
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date_range,
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)
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import pandas._testing as tm
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from pandas.core.ops import roperator
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from pandas.tests.arithmetic.common import (
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assert_cannot_add,
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assert_invalid_addsub_type,
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assert_invalid_comparison,
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get_upcast_box,
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)
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# ------------------------------------------------------------------
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# Comparisons
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class TestDatetime64ArrayLikeComparisons:
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# Comparison tests for datetime64 vectors fully parametrized over
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# DataFrame/Series/DatetimeIndex/DatetimeArray. Ideally all comparison
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# tests will eventually end up here.
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def test_compare_zerodim(self, tz_naive_fixture, box_with_array):
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# Test comparison with zero-dimensional array is unboxed
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tz = tz_naive_fixture
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box = box_with_array
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dti = date_range("20130101", periods=3, tz=tz)
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other = np.array(dti.to_numpy()[0])
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dtarr = tm.box_expected(dti, box)
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xbox = get_upcast_box(dtarr, other, True)
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result = dtarr <= other
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expected = np.array([True, False, False])
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expected = tm.box_expected(expected, xbox)
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tm.assert_equal(result, expected)
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@pytest.mark.parametrize(
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"other",
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[
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"foo",
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-1,
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99,
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4.0,
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object(),
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timedelta(days=2),
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# GH#19800, GH#19301 datetime.date comparison raises to
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# match DatetimeIndex/Timestamp. This also matches the behavior
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# of stdlib datetime.datetime
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datetime(2001, 1, 1).date(),
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# GH#19301 None and NaN are *not* cast to NaT for comparisons
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None,
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np.nan,
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],
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)
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def test_dt64arr_cmp_scalar_invalid(self, other, tz_naive_fixture, box_with_array):
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# GH#22074, GH#15966
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tz = tz_naive_fixture
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rng = date_range("1/1/2000", periods=10, tz=tz)
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dtarr = tm.box_expected(rng, box_with_array)
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assert_invalid_comparison(dtarr, other, box_with_array)
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@pytest.mark.parametrize(
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"other",
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[
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# GH#4968 invalid date/int comparisons
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list(range(10)),
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np.arange(10),
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np.arange(10).astype(np.float32),
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np.arange(10).astype(object),
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pd.timedelta_range("1ns", periods=10).array,
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np.array(pd.timedelta_range("1ns", periods=10)),
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list(pd.timedelta_range("1ns", periods=10)),
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pd.timedelta_range("1 Day", periods=10).astype(object),
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pd.period_range("1971-01-01", freq="D", periods=10).array,
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pd.period_range("1971-01-01", freq="D", periods=10).astype(object),
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],
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)
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def test_dt64arr_cmp_arraylike_invalid(
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self, other, tz_naive_fixture, box_with_array
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):
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tz = tz_naive_fixture
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dta = date_range("1970-01-01", freq="ns", periods=10, tz=tz)._data
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obj = tm.box_expected(dta, box_with_array)
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assert_invalid_comparison(obj, other, box_with_array)
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def test_dt64arr_cmp_mixed_invalid(self, tz_naive_fixture):
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tz = tz_naive_fixture
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dta = date_range("1970-01-01", freq="h", periods=5, tz=tz)._data
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other = np.array([0, 1, 2, dta[3], Timedelta(days=1)])
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result = dta == other
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expected = np.array([False, False, False, True, False])
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tm.assert_numpy_array_equal(result, expected)
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result = dta != other
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tm.assert_numpy_array_equal(result, ~expected)
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msg = "Invalid comparison between|Cannot compare type|not supported between"
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with pytest.raises(TypeError, match=msg):
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dta < other
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with pytest.raises(TypeError, match=msg):
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dta > other
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with pytest.raises(TypeError, match=msg):
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dta <= other
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with pytest.raises(TypeError, match=msg):
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dta >= other
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def test_dt64arr_nat_comparison(self, tz_naive_fixture, box_with_array):
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# GH#22242, GH#22163 DataFrame considered NaT == ts incorrectly
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tz = tz_naive_fixture
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box = box_with_array
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ts = Timestamp("2021-01-01", tz=tz)
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ser = Series([ts, NaT])
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obj = tm.box_expected(ser, box)
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xbox = get_upcast_box(obj, ts, True)
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expected = Series([True, False], dtype=np.bool_)
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expected = tm.box_expected(expected, xbox)
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result = obj == ts
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tm.assert_equal(result, expected)
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class TestDatetime64SeriesComparison:
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# TODO: moved from tests.series.test_operators; needs cleanup
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@pytest.mark.parametrize(
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"pair",
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[
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(
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[Timestamp("2011-01-01"), NaT, Timestamp("2011-01-03")],
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[NaT, NaT, Timestamp("2011-01-03")],
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),
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(
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[Timedelta("1 days"), NaT, Timedelta("3 days")],
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[NaT, NaT, Timedelta("3 days")],
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),
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(
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[Period("2011-01", freq="M"), NaT, Period("2011-03", freq="M")],
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[NaT, NaT, Period("2011-03", freq="M")],
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),
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],
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)
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@pytest.mark.parametrize("reverse", [True, False])
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@pytest.mark.parametrize("dtype", [None, object])
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@pytest.mark.parametrize(
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"op, expected",
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[
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(operator.eq, Series([False, False, True])),
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(operator.ne, Series([True, True, False])),
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(operator.lt, Series([False, False, False])),
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(operator.gt, Series([False, False, False])),
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(operator.ge, Series([False, False, True])),
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(operator.le, Series([False, False, True])),
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],
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)
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def test_nat_comparisons(
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self,
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dtype,
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index_or_series,
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reverse,
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pair,
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op,
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expected,
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):
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box = index_or_series
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lhs, rhs = pair
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if reverse:
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# add lhs / rhs switched data
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lhs, rhs = rhs, lhs
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left = Series(lhs, dtype=dtype)
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right = box(rhs, dtype=dtype)
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result = op(left, right)
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tm.assert_series_equal(result, expected)
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@pytest.mark.parametrize(
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"data",
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[
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[Timestamp("2011-01-01"), NaT, Timestamp("2011-01-03")],
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[Timedelta("1 days"), NaT, Timedelta("3 days")],
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[Period("2011-01", freq="M"), NaT, Period("2011-03", freq="M")],
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],
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)
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@pytest.mark.parametrize("dtype", [None, object])
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def test_nat_comparisons_scalar(self, dtype, data, box_with_array):
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box = box_with_array
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left = Series(data, dtype=dtype)
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left = tm.box_expected(left, box)
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xbox = get_upcast_box(left, NaT, True)
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expected = [False, False, False]
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expected = tm.box_expected(expected, xbox)
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if box is pd.array and dtype is object:
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expected = pd.array(expected, dtype="bool")
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tm.assert_equal(left == NaT, expected)
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tm.assert_equal(NaT == left, expected)
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expected = [True, True, True]
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expected = tm.box_expected(expected, xbox)
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if box is pd.array and dtype is object:
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expected = pd.array(expected, dtype="bool")
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tm.assert_equal(left != NaT, expected)
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tm.assert_equal(NaT != left, expected)
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expected = [False, False, False]
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expected = tm.box_expected(expected, xbox)
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if box is pd.array and dtype is object:
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expected = pd.array(expected, dtype="bool")
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tm.assert_equal(left < NaT, expected)
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tm.assert_equal(NaT > left, expected)
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tm.assert_equal(left <= NaT, expected)
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tm.assert_equal(NaT >= left, expected)
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tm.assert_equal(left > NaT, expected)
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tm.assert_equal(NaT < left, expected)
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tm.assert_equal(left >= NaT, expected)
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tm.assert_equal(NaT <= left, expected)
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@pytest.mark.parametrize("val", [datetime(2000, 1, 4), datetime(2000, 1, 5)])
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def test_series_comparison_scalars(self, val):
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series = Series(date_range("1/1/2000", periods=10))
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result = series > val
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expected = Series([x > val for x in series])
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tm.assert_series_equal(result, expected)
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@pytest.mark.parametrize(
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"left,right", [("lt", "gt"), ("le", "ge"), ("eq", "eq"), ("ne", "ne")]
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)
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def test_timestamp_compare_series(self, left, right):
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# see gh-4982
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# Make sure we can compare Timestamps on the right AND left hand side.
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ser = Series(date_range("20010101", periods=10), name="dates")
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s_nat = ser.copy(deep=True)
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ser[0] = Timestamp("nat")
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ser[3] = Timestamp("nat")
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left_f = getattr(operator, left)
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right_f = getattr(operator, right)
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# No NaT
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expected = left_f(ser, Timestamp("20010109"))
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result = right_f(Timestamp("20010109"), ser)
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tm.assert_series_equal(result, expected)
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# NaT
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expected = left_f(ser, Timestamp("nat"))
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result = right_f(Timestamp("nat"), ser)
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tm.assert_series_equal(result, expected)
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# Compare to Timestamp with series containing NaT
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expected = left_f(s_nat, Timestamp("20010109"))
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result = right_f(Timestamp("20010109"), s_nat)
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tm.assert_series_equal(result, expected)
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# Compare to NaT with series containing NaT
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expected = left_f(s_nat, NaT)
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result = right_f(NaT, s_nat)
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tm.assert_series_equal(result, expected)
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def test_dt64arr_timestamp_equality(self, box_with_array):
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# GH#11034
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box = box_with_array
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ser = Series([Timestamp("2000-01-29 01:59:00"), Timestamp("2000-01-30"), NaT])
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ser = tm.box_expected(ser, box)
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xbox = get_upcast_box(ser, ser, True)
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result = ser != ser
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expected = tm.box_expected([False, False, True], xbox)
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tm.assert_equal(result, expected)
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if box is pd.DataFrame:
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# alignment for frame vs series comparisons deprecated
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# in GH#46795 enforced 2.0
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with pytest.raises(ValueError, match="not aligned"):
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ser != ser[0]
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else:
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result = ser != ser[0]
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expected = tm.box_expected([False, True, True], xbox)
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tm.assert_equal(result, expected)
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if box is pd.DataFrame:
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# alignment for frame vs series comparisons deprecated
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# in GH#46795 enforced 2.0
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with pytest.raises(ValueError, match="not aligned"):
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ser != ser[2]
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else:
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result = ser != ser[2]
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expected = tm.box_expected([True, True, True], xbox)
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tm.assert_equal(result, expected)
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result = ser == ser
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expected = tm.box_expected([True, True, False], xbox)
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tm.assert_equal(result, expected)
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if box is pd.DataFrame:
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# alignment for frame vs series comparisons deprecated
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# in GH#46795 enforced 2.0
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with pytest.raises(ValueError, match="not aligned"):
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ser == ser[0]
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else:
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result = ser == ser[0]
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expected = tm.box_expected([True, False, False], xbox)
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tm.assert_equal(result, expected)
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if box is pd.DataFrame:
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# alignment for frame vs series comparisons deprecated
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# in GH#46795 enforced 2.0
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with pytest.raises(ValueError, match="not aligned"):
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ser == ser[2]
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else:
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result = ser == ser[2]
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expected = tm.box_expected([False, False, False], xbox)
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tm.assert_equal(result, expected)
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@pytest.mark.parametrize(
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"datetimelike",
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[
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Timestamp("20130101"),
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datetime(2013, 1, 1),
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np.datetime64("2013-01-01T00:00", "ns"),
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],
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)
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@pytest.mark.parametrize(
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"op,expected",
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[
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(operator.lt, [True, False, False, False]),
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(operator.le, [True, True, False, False]),
|
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(operator.eq, [False, True, False, False]),
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(operator.gt, [False, False, False, True]),
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],
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|
)
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def test_dt64_compare_datetime_scalar(self, datetimelike, op, expected):
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# GH#17965, test for ability to compare datetime64[ns] columns
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# to datetimelike
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ser = Series(
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[
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Timestamp("20120101"),
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Timestamp("20130101"),
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np.nan,
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Timestamp("20130103"),
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],
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name="A",
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)
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result = op(ser, datetimelike)
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expected = Series(expected, name="A")
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tm.assert_series_equal(result, expected)
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|
|
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class TestDatetimeIndexComparisons:
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# TODO: moved from tests.indexes.test_base; parametrize and de-duplicate
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def test_comparators(self, comparison_op):
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index = tm.makeDateIndex(100)
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element = index[len(index) // 2]
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element = Timestamp(element).to_datetime64()
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arr = np.array(index)
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arr_result = comparison_op(arr, element)
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index_result = comparison_op(index, element)
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assert isinstance(index_result, np.ndarray)
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tm.assert_numpy_array_equal(arr_result, index_result)
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|
@pytest.mark.parametrize(
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|
"other",
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[datetime(2016, 1, 1), Timestamp("2016-01-01"), np.datetime64("2016-01-01")],
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)
|
|
def test_dti_cmp_datetimelike(self, other, tz_naive_fixture):
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|
tz = tz_naive_fixture
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dti = date_range("2016-01-01", periods=2, tz=tz)
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if tz is not None:
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if isinstance(other, np.datetime64):
|
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# no tzaware version available
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return
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other = localize_pydatetime(other, dti.tzinfo)
|
|
|
|
result = dti == other
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|
expected = np.array([True, False])
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tm.assert_numpy_array_equal(result, expected)
|
|
|
|
result = dti > other
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expected = np.array([False, True])
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|
tm.assert_numpy_array_equal(result, expected)
|
|
|
|
result = dti >= other
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|
expected = np.array([True, True])
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|
tm.assert_numpy_array_equal(result, expected)
|
|
|
|
result = dti < other
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|
expected = np.array([False, False])
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|
tm.assert_numpy_array_equal(result, expected)
|
|
|
|
result = dti <= other
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|
expected = np.array([True, False])
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tm.assert_numpy_array_equal(result, expected)
|
|
|
|
@pytest.mark.parametrize("dtype", [None, object])
|
|
def test_dti_cmp_nat(self, dtype, box_with_array):
|
|
left = DatetimeIndex([Timestamp("2011-01-01"), NaT, Timestamp("2011-01-03")])
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|
right = DatetimeIndex([NaT, NaT, Timestamp("2011-01-03")])
|
|
|
|
left = tm.box_expected(left, box_with_array)
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|
right = tm.box_expected(right, box_with_array)
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|
xbox = get_upcast_box(left, right, True)
|
|
|
|
lhs, rhs = left, right
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|
if dtype is object:
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|
lhs, rhs = left.astype(object), right.astype(object)
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|
|
|
result = rhs == lhs
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|
expected = np.array([False, False, True])
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|
expected = tm.box_expected(expected, xbox)
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|
tm.assert_equal(result, expected)
|
|
|
|
result = lhs != rhs
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|
expected = np.array([True, True, False])
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|
expected = tm.box_expected(expected, xbox)
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|
tm.assert_equal(result, expected)
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|
|
|
expected = np.array([False, False, False])
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|
expected = tm.box_expected(expected, xbox)
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tm.assert_equal(lhs == NaT, expected)
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|
tm.assert_equal(NaT == rhs, expected)
|
|
|
|
expected = np.array([True, True, True])
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|
expected = tm.box_expected(expected, xbox)
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|
tm.assert_equal(lhs != NaT, expected)
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|
tm.assert_equal(NaT != lhs, expected)
|
|
|
|
expected = np.array([False, False, False])
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|
expected = tm.box_expected(expected, xbox)
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|
tm.assert_equal(lhs < NaT, expected)
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|
tm.assert_equal(NaT > lhs, expected)
|
|
|
|
def test_dti_cmp_nat_behaves_like_float_cmp_nan(self):
|
|
fidx1 = pd.Index([1.0, np.nan, 3.0, np.nan, 5.0, 7.0])
|
|
fidx2 = pd.Index([2.0, 3.0, np.nan, np.nan, 6.0, 7.0])
|
|
|
|
didx1 = DatetimeIndex(
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|
["2014-01-01", NaT, "2014-03-01", NaT, "2014-05-01", "2014-07-01"]
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|
)
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|
didx2 = DatetimeIndex(
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|
["2014-02-01", "2014-03-01", NaT, NaT, "2014-06-01", "2014-07-01"]
|
|
)
|
|
darr = np.array(
|
|
[
|
|
np.datetime64("2014-02-01 00:00"),
|
|
np.datetime64("2014-03-01 00:00"),
|
|
np.datetime64("nat"),
|
|
np.datetime64("nat"),
|
|
np.datetime64("2014-06-01 00:00"),
|
|
np.datetime64("2014-07-01 00:00"),
|
|
]
|
|
)
|
|
|
|
cases = [(fidx1, fidx2), (didx1, didx2), (didx1, darr)]
|
|
|
|
# Check pd.NaT is handles as the same as np.nan
|
|
with tm.assert_produces_warning(None):
|
|
for idx1, idx2 in cases:
|
|
result = idx1 < idx2
|
|
expected = np.array([True, False, False, False, True, False])
|
|
tm.assert_numpy_array_equal(result, expected)
|
|
|
|
result = idx2 > idx1
|
|
expected = np.array([True, False, False, False, True, False])
|
|
tm.assert_numpy_array_equal(result, expected)
|
|
|
|
result = idx1 <= idx2
|
|
expected = np.array([True, False, False, False, True, True])
|
|
tm.assert_numpy_array_equal(result, expected)
|
|
|
|
result = idx2 >= idx1
|
|
expected = np.array([True, False, False, False, True, True])
|
|
tm.assert_numpy_array_equal(result, expected)
|
|
|
|
result = idx1 == idx2
|
|
expected = np.array([False, False, False, False, False, True])
|
|
tm.assert_numpy_array_equal(result, expected)
|
|
|
|
result = idx1 != idx2
|
|
expected = np.array([True, True, True, True, True, False])
|
|
tm.assert_numpy_array_equal(result, expected)
|
|
|
|
with tm.assert_produces_warning(None):
|
|
for idx1, val in [(fidx1, np.nan), (didx1, NaT)]:
|
|
result = idx1 < val
|
|
expected = np.array([False, False, False, False, False, False])
|
|
tm.assert_numpy_array_equal(result, expected)
|
|
result = idx1 > val
|
|
tm.assert_numpy_array_equal(result, expected)
|
|
|
|
result = idx1 <= val
|
|
tm.assert_numpy_array_equal(result, expected)
|
|
result = idx1 >= val
|
|
tm.assert_numpy_array_equal(result, expected)
|
|
|
|
result = idx1 == val
|
|
tm.assert_numpy_array_equal(result, expected)
|
|
|
|
result = idx1 != val
|
|
expected = np.array([True, True, True, True, True, True])
|
|
tm.assert_numpy_array_equal(result, expected)
|
|
|
|
# Check pd.NaT is handles as the same as np.nan
|
|
with tm.assert_produces_warning(None):
|
|
for idx1, val in [(fidx1, 3), (didx1, datetime(2014, 3, 1))]:
|
|
result = idx1 < val
|
|
expected = np.array([True, False, False, False, False, False])
|
|
tm.assert_numpy_array_equal(result, expected)
|
|
result = idx1 > val
|
|
expected = np.array([False, False, False, False, True, True])
|
|
tm.assert_numpy_array_equal(result, expected)
|
|
|
|
result = idx1 <= val
|
|
expected = np.array([True, False, True, False, False, False])
|
|
tm.assert_numpy_array_equal(result, expected)
|
|
result = idx1 >= val
|
|
expected = np.array([False, False, True, False, True, True])
|
|
tm.assert_numpy_array_equal(result, expected)
|
|
|
|
result = idx1 == val
|
|
expected = np.array([False, False, True, False, False, False])
|
|
tm.assert_numpy_array_equal(result, expected)
|
|
|
|
result = idx1 != val
|
|
expected = np.array([True, True, False, True, True, True])
|
|
tm.assert_numpy_array_equal(result, expected)
|
|
|
|
def test_comparison_tzawareness_compat(self, comparison_op, box_with_array):
|
|
# GH#18162
|
|
op = comparison_op
|
|
box = box_with_array
|
|
|
|
dr = date_range("2016-01-01", periods=6)
|
|
dz = dr.tz_localize("US/Pacific")
|
|
|
|
dr = tm.box_expected(dr, box)
|
|
dz = tm.box_expected(dz, box)
|
|
|
|
if box is pd.DataFrame:
|
|
tolist = lambda x: x.astype(object).values.tolist()[0]
|
|
else:
|
|
tolist = list
|
|
|
|
if op not in [operator.eq, operator.ne]:
|
|
msg = (
|
|
r"Invalid comparison between dtype=datetime64\[ns.*\] "
|
|
"and (Timestamp|DatetimeArray|list|ndarray)"
|
|
)
|
|
with pytest.raises(TypeError, match=msg):
|
|
op(dr, dz)
|
|
|
|
with pytest.raises(TypeError, match=msg):
|
|
op(dr, tolist(dz))
|
|
with pytest.raises(TypeError, match=msg):
|
|
op(dr, np.array(tolist(dz), dtype=object))
|
|
with pytest.raises(TypeError, match=msg):
|
|
op(dz, dr)
|
|
|
|
with pytest.raises(TypeError, match=msg):
|
|
op(dz, tolist(dr))
|
|
with pytest.raises(TypeError, match=msg):
|
|
op(dz, np.array(tolist(dr), dtype=object))
|
|
|
|
# The aware==aware and naive==naive comparisons should *not* raise
|
|
assert np.all(dr == dr)
|
|
assert np.all(dr == tolist(dr))
|
|
assert np.all(tolist(dr) == dr)
|
|
assert np.all(np.array(tolist(dr), dtype=object) == dr)
|
|
assert np.all(dr == np.array(tolist(dr), dtype=object))
|
|
|
|
assert np.all(dz == dz)
|
|
assert np.all(dz == tolist(dz))
|
|
assert np.all(tolist(dz) == dz)
|
|
assert np.all(np.array(tolist(dz), dtype=object) == dz)
|
|
assert np.all(dz == np.array(tolist(dz), dtype=object))
|
|
|
|
def test_comparison_tzawareness_compat_scalars(self, comparison_op, box_with_array):
|
|
# GH#18162
|
|
op = comparison_op
|
|
|
|
dr = date_range("2016-01-01", periods=6)
|
|
dz = dr.tz_localize("US/Pacific")
|
|
|
|
dr = tm.box_expected(dr, box_with_array)
|
|
dz = tm.box_expected(dz, box_with_array)
|
|
|
|
# Check comparisons against scalar Timestamps
|
|
ts = Timestamp("2000-03-14 01:59")
|
|
ts_tz = Timestamp("2000-03-14 01:59", tz="Europe/Amsterdam")
|
|
|
|
assert np.all(dr > ts)
|
|
msg = r"Invalid comparison between dtype=datetime64\[ns.*\] and Timestamp"
|
|
if op not in [operator.eq, operator.ne]:
|
|
with pytest.raises(TypeError, match=msg):
|
|
op(dr, ts_tz)
|
|
|
|
assert np.all(dz > ts_tz)
|
|
if op not in [operator.eq, operator.ne]:
|
|
with pytest.raises(TypeError, match=msg):
|
|
op(dz, ts)
|
|
|
|
if op not in [operator.eq, operator.ne]:
|
|
# GH#12601: Check comparison against Timestamps and DatetimeIndex
|
|
with pytest.raises(TypeError, match=msg):
|
|
op(ts, dz)
|
|
|
|
@pytest.mark.parametrize(
|
|
"other",
|
|
[datetime(2016, 1, 1), Timestamp("2016-01-01"), np.datetime64("2016-01-01")],
|
|
)
|
|
# Bug in NumPy? https://github.com/numpy/numpy/issues/13841
|
|
# Raising in __eq__ will fallback to NumPy, which warns, fails,
|
|
# then re-raises the original exception. So we just need to ignore.
|
|
@pytest.mark.filterwarnings("ignore:elementwise comp:DeprecationWarning")
|
|
def test_scalar_comparison_tzawareness(
|
|
self, comparison_op, other, tz_aware_fixture, box_with_array
|
|
):
|
|
op = comparison_op
|
|
tz = tz_aware_fixture
|
|
dti = date_range("2016-01-01", periods=2, tz=tz)
|
|
|
|
dtarr = tm.box_expected(dti, box_with_array)
|
|
xbox = get_upcast_box(dtarr, other, True)
|
|
if op in [operator.eq, operator.ne]:
|
|
exbool = op is operator.ne
|
|
expected = np.array([exbool, exbool], dtype=bool)
|
|
expected = tm.box_expected(expected, xbox)
|
|
|
|
result = op(dtarr, other)
|
|
tm.assert_equal(result, expected)
|
|
|
|
result = op(other, dtarr)
|
|
tm.assert_equal(result, expected)
|
|
else:
|
|
msg = (
|
|
r"Invalid comparison between dtype=datetime64\[ns, .*\] "
|
|
f"and {type(other).__name__}"
|
|
)
|
|
with pytest.raises(TypeError, match=msg):
|
|
op(dtarr, other)
|
|
with pytest.raises(TypeError, match=msg):
|
|
op(other, dtarr)
|
|
|
|
def test_nat_comparison_tzawareness(self, comparison_op):
|
|
# GH#19276
|
|
# tzaware DatetimeIndex should not raise when compared to NaT
|
|
op = comparison_op
|
|
|
|
dti = DatetimeIndex(
|
|
["2014-01-01", NaT, "2014-03-01", NaT, "2014-05-01", "2014-07-01"]
|
|
)
|
|
expected = np.array([op == operator.ne] * len(dti))
|
|
result = op(dti, NaT)
|
|
tm.assert_numpy_array_equal(result, expected)
|
|
|
|
result = op(dti.tz_localize("US/Pacific"), NaT)
|
|
tm.assert_numpy_array_equal(result, expected)
|
|
|
|
def test_dti_cmp_str(self, tz_naive_fixture):
|
|
# GH#22074
|
|
# regardless of tz, we expect these comparisons are valid
|
|
tz = tz_naive_fixture
|
|
rng = date_range("1/1/2000", periods=10, tz=tz)
|
|
other = "1/1/2000"
|
|
|
|
result = rng == other
|
|
expected = np.array([True] + [False] * 9)
|
|
tm.assert_numpy_array_equal(result, expected)
|
|
|
|
result = rng != other
|
|
expected = np.array([False] + [True] * 9)
|
|
tm.assert_numpy_array_equal(result, expected)
|
|
|
|
result = rng < other
|
|
expected = np.array([False] * 10)
|
|
tm.assert_numpy_array_equal(result, expected)
|
|
|
|
result = rng <= other
|
|
expected = np.array([True] + [False] * 9)
|
|
tm.assert_numpy_array_equal(result, expected)
|
|
|
|
result = rng > other
|
|
expected = np.array([False] + [True] * 9)
|
|
tm.assert_numpy_array_equal(result, expected)
|
|
|
|
result = rng >= other
|
|
expected = np.array([True] * 10)
|
|
tm.assert_numpy_array_equal(result, expected)
|
|
|
|
def test_dti_cmp_list(self):
|
|
rng = date_range("1/1/2000", periods=10)
|
|
|
|
result = rng == list(rng)
|
|
expected = rng == rng
|
|
tm.assert_numpy_array_equal(result, expected)
|
|
|
|
@pytest.mark.parametrize(
|
|
"other",
|
|
[
|
|
pd.timedelta_range("1D", periods=10),
|
|
pd.timedelta_range("1D", periods=10).to_series(),
|
|
pd.timedelta_range("1D", periods=10).asi8.view("m8[ns]"),
|
|
],
|
|
ids=lambda x: type(x).__name__,
|
|
)
|
|
def test_dti_cmp_tdi_tzawareness(self, other):
|
|
# GH#22074
|
|
# reversion test that we _don't_ call _assert_tzawareness_compat
|
|
# when comparing against TimedeltaIndex
|
|
dti = date_range("2000-01-01", periods=10, tz="Asia/Tokyo")
|
|
|
|
result = dti == other
|
|
expected = np.array([False] * 10)
|
|
tm.assert_numpy_array_equal(result, expected)
|
|
|
|
result = dti != other
|
|
expected = np.array([True] * 10)
|
|
tm.assert_numpy_array_equal(result, expected)
|
|
msg = "Invalid comparison between"
|
|
with pytest.raises(TypeError, match=msg):
|
|
dti < other
|
|
with pytest.raises(TypeError, match=msg):
|
|
dti <= other
|
|
with pytest.raises(TypeError, match=msg):
|
|
dti > other
|
|
with pytest.raises(TypeError, match=msg):
|
|
dti >= other
|
|
|
|
def test_dti_cmp_object_dtype(self):
|
|
# GH#22074
|
|
dti = date_range("2000-01-01", periods=10, tz="Asia/Tokyo")
|
|
|
|
other = dti.astype("O")
|
|
|
|
result = dti == other
|
|
expected = np.array([True] * 10)
|
|
tm.assert_numpy_array_equal(result, expected)
|
|
|
|
other = dti.tz_localize(None)
|
|
result = dti != other
|
|
tm.assert_numpy_array_equal(result, expected)
|
|
|
|
other = np.array(list(dti[:5]) + [Timedelta(days=1)] * 5)
|
|
result = dti == other
|
|
expected = np.array([True] * 5 + [False] * 5)
|
|
tm.assert_numpy_array_equal(result, expected)
|
|
msg = ">=' not supported between instances of 'Timestamp' and 'Timedelta'"
|
|
with pytest.raises(TypeError, match=msg):
|
|
dti >= other
|
|
|
|
|
|
# ------------------------------------------------------------------
|
|
# Arithmetic
|
|
|
|
|
|
class TestDatetime64Arithmetic:
|
|
# This class is intended for "finished" tests that are fully parametrized
|
|
# over DataFrame/Series/Index/DatetimeArray
|
|
|
|
# -------------------------------------------------------------
|
|
# Addition/Subtraction of timedelta-like
|
|
|
|
@pytest.mark.arm_slow
|
|
def test_dt64arr_add_timedeltalike_scalar(
|
|
self, tz_naive_fixture, two_hours, box_with_array
|
|
):
|
|
# GH#22005, GH#22163 check DataFrame doesn't raise TypeError
|
|
tz = tz_naive_fixture
|
|
|
|
rng = date_range("2000-01-01", "2000-02-01", tz=tz)
|
|
expected = date_range("2000-01-01 02:00", "2000-02-01 02:00", tz=tz)
|
|
|
|
rng = tm.box_expected(rng, box_with_array)
|
|
expected = tm.box_expected(expected, box_with_array)
|
|
|
|
result = rng + two_hours
|
|
tm.assert_equal(result, expected)
|
|
|
|
result = two_hours + rng
|
|
tm.assert_equal(result, expected)
|
|
|
|
rng += two_hours
|
|
tm.assert_equal(rng, expected)
|
|
|
|
def test_dt64arr_sub_timedeltalike_scalar(
|
|
self, tz_naive_fixture, two_hours, box_with_array
|
|
):
|
|
tz = tz_naive_fixture
|
|
|
|
rng = date_range("2000-01-01", "2000-02-01", tz=tz)
|
|
expected = date_range("1999-12-31 22:00", "2000-01-31 22:00", tz=tz)
|
|
|
|
rng = tm.box_expected(rng, box_with_array)
|
|
expected = tm.box_expected(expected, box_with_array)
|
|
|
|
result = rng - two_hours
|
|
tm.assert_equal(result, expected)
|
|
|
|
rng -= two_hours
|
|
tm.assert_equal(rng, expected)
|
|
|
|
def test_dt64_array_sub_dt_with_different_timezone(self, box_with_array):
|
|
t1 = date_range("20130101", periods=3).tz_localize("US/Eastern")
|
|
t1 = tm.box_expected(t1, box_with_array)
|
|
t2 = Timestamp("20130101").tz_localize("CET")
|
|
tnaive = Timestamp(20130101)
|
|
|
|
result = t1 - t2
|
|
expected = TimedeltaIndex(
|
|
["0 days 06:00:00", "1 days 06:00:00", "2 days 06:00:00"]
|
|
)
|
|
expected = tm.box_expected(expected, box_with_array)
|
|
tm.assert_equal(result, expected)
|
|
|
|
result = t2 - t1
|
|
expected = TimedeltaIndex(
|
|
["-1 days +18:00:00", "-2 days +18:00:00", "-3 days +18:00:00"]
|
|
)
|
|
expected = tm.box_expected(expected, box_with_array)
|
|
tm.assert_equal(result, expected)
|
|
|
|
msg = "Cannot subtract tz-naive and tz-aware datetime-like objects"
|
|
with pytest.raises(TypeError, match=msg):
|
|
t1 - tnaive
|
|
|
|
with pytest.raises(TypeError, match=msg):
|
|
tnaive - t1
|
|
|
|
def test_dt64_array_sub_dt64_array_with_different_timezone(self, box_with_array):
|
|
t1 = date_range("20130101", periods=3).tz_localize("US/Eastern")
|
|
t1 = tm.box_expected(t1, box_with_array)
|
|
t2 = date_range("20130101", periods=3).tz_localize("CET")
|
|
t2 = tm.box_expected(t2, box_with_array)
|
|
tnaive = date_range("20130101", periods=3)
|
|
|
|
result = t1 - t2
|
|
expected = TimedeltaIndex(
|
|
["0 days 06:00:00", "0 days 06:00:00", "0 days 06:00:00"]
|
|
)
|
|
expected = tm.box_expected(expected, box_with_array)
|
|
tm.assert_equal(result, expected)
|
|
|
|
result = t2 - t1
|
|
expected = TimedeltaIndex(
|
|
["-1 days +18:00:00", "-1 days +18:00:00", "-1 days +18:00:00"]
|
|
)
|
|
expected = tm.box_expected(expected, box_with_array)
|
|
tm.assert_equal(result, expected)
|
|
|
|
msg = "Cannot subtract tz-naive and tz-aware datetime-like objects"
|
|
with pytest.raises(TypeError, match=msg):
|
|
t1 - tnaive
|
|
|
|
with pytest.raises(TypeError, match=msg):
|
|
tnaive - t1
|
|
|
|
def test_dt64arr_add_sub_td64_nat(self, box_with_array, tz_naive_fixture):
|
|
# GH#23320 special handling for timedelta64("NaT")
|
|
tz = tz_naive_fixture
|
|
|
|
dti = date_range("1994-04-01", periods=9, tz=tz, freq="QS")
|
|
other = np.timedelta64("NaT")
|
|
expected = DatetimeIndex(["NaT"] * 9, tz=tz)
|
|
|
|
obj = tm.box_expected(dti, box_with_array)
|
|
expected = tm.box_expected(expected, box_with_array)
|
|
|
|
result = obj + other
|
|
tm.assert_equal(result, expected)
|
|
result = other + obj
|
|
tm.assert_equal(result, expected)
|
|
result = obj - other
|
|
tm.assert_equal(result, expected)
|
|
msg = "cannot subtract"
|
|
with pytest.raises(TypeError, match=msg):
|
|
other - obj
|
|
|
|
def test_dt64arr_add_sub_td64ndarray(self, tz_naive_fixture, box_with_array):
|
|
tz = tz_naive_fixture
|
|
dti = date_range("2016-01-01", periods=3, tz=tz)
|
|
tdi = TimedeltaIndex(["-1 Day", "-1 Day", "-1 Day"])
|
|
tdarr = tdi.values
|
|
|
|
expected = date_range("2015-12-31", "2016-01-02", periods=3, tz=tz)
|
|
|
|
dtarr = tm.box_expected(dti, box_with_array)
|
|
expected = tm.box_expected(expected, box_with_array)
|
|
|
|
result = dtarr + tdarr
|
|
tm.assert_equal(result, expected)
|
|
result = tdarr + dtarr
|
|
tm.assert_equal(result, expected)
|
|
|
|
expected = date_range("2016-01-02", "2016-01-04", periods=3, tz=tz)
|
|
expected = tm.box_expected(expected, box_with_array)
|
|
|
|
result = dtarr - tdarr
|
|
tm.assert_equal(result, expected)
|
|
msg = "cannot subtract|(bad|unsupported) operand type for unary"
|
|
with pytest.raises(TypeError, match=msg):
|
|
tdarr - dtarr
|
|
|
|
# -----------------------------------------------------------------
|
|
# Subtraction of datetime-like scalars
|
|
|
|
@pytest.mark.parametrize(
|
|
"ts",
|
|
[
|
|
Timestamp("2013-01-01"),
|
|
Timestamp("2013-01-01").to_pydatetime(),
|
|
Timestamp("2013-01-01").to_datetime64(),
|
|
# GH#7996, GH#22163 ensure non-nano datetime64 is converted to nano
|
|
# for DataFrame operation
|
|
np.datetime64("2013-01-01", "D"),
|
|
],
|
|
)
|
|
def test_dt64arr_sub_dtscalar(self, box_with_array, ts):
|
|
# GH#8554, GH#22163 DataFrame op should _not_ return dt64 dtype
|
|
idx = date_range("2013-01-01", periods=3)._with_freq(None)
|
|
idx = tm.box_expected(idx, box_with_array)
|
|
|
|
expected = TimedeltaIndex(["0 Days", "1 Day", "2 Days"])
|
|
expected = tm.box_expected(expected, box_with_array)
|
|
|
|
result = idx - ts
|
|
tm.assert_equal(result, expected)
|
|
|
|
result = ts - idx
|
|
tm.assert_equal(result, -expected)
|
|
tm.assert_equal(result, -expected)
|
|
|
|
def test_dt64arr_sub_timestamp_tzaware(self, box_with_array):
|
|
ser = date_range("2014-03-17", periods=2, freq="D", tz="US/Eastern")
|
|
ser = ser._with_freq(None)
|
|
ts = ser[0]
|
|
|
|
ser = tm.box_expected(ser, box_with_array)
|
|
|
|
delta_series = Series([np.timedelta64(0, "D"), np.timedelta64(1, "D")])
|
|
expected = tm.box_expected(delta_series, box_with_array)
|
|
|
|
tm.assert_equal(ser - ts, expected)
|
|
tm.assert_equal(ts - ser, -expected)
|
|
|
|
def test_dt64arr_sub_NaT(self, box_with_array):
|
|
# GH#18808
|
|
dti = DatetimeIndex([NaT, Timestamp("19900315")])
|
|
ser = tm.box_expected(dti, box_with_array)
|
|
|
|
result = ser - NaT
|
|
expected = Series([NaT, NaT], dtype="timedelta64[ns]")
|
|
expected = tm.box_expected(expected, box_with_array)
|
|
tm.assert_equal(result, expected)
|
|
|
|
dti_tz = dti.tz_localize("Asia/Tokyo")
|
|
ser_tz = tm.box_expected(dti_tz, box_with_array)
|
|
|
|
result = ser_tz - NaT
|
|
expected = Series([NaT, NaT], dtype="timedelta64[ns]")
|
|
expected = tm.box_expected(expected, box_with_array)
|
|
tm.assert_equal(result, expected)
|
|
|
|
# -------------------------------------------------------------
|
|
# Subtraction of datetime-like array-like
|
|
|
|
def test_dt64arr_sub_dt64object_array(self, box_with_array, tz_naive_fixture):
|
|
dti = date_range("2016-01-01", periods=3, tz=tz_naive_fixture)
|
|
expected = dti - dti
|
|
|
|
obj = tm.box_expected(dti, box_with_array)
|
|
expected = tm.box_expected(expected, box_with_array).astype(object)
|
|
|
|
with tm.assert_produces_warning(PerformanceWarning):
|
|
result = obj - obj.astype(object)
|
|
tm.assert_equal(result, expected)
|
|
|
|
def test_dt64arr_naive_sub_dt64ndarray(self, box_with_array):
|
|
dti = date_range("2016-01-01", periods=3, tz=None)
|
|
dt64vals = dti.values
|
|
|
|
dtarr = tm.box_expected(dti, box_with_array)
|
|
|
|
expected = dtarr - dtarr
|
|
result = dtarr - dt64vals
|
|
tm.assert_equal(result, expected)
|
|
result = dt64vals - dtarr
|
|
tm.assert_equal(result, expected)
|
|
|
|
def test_dt64arr_aware_sub_dt64ndarray_raises(
|
|
self, tz_aware_fixture, box_with_array
|
|
):
|
|
tz = tz_aware_fixture
|
|
dti = date_range("2016-01-01", periods=3, tz=tz)
|
|
dt64vals = dti.values
|
|
|
|
dtarr = tm.box_expected(dti, box_with_array)
|
|
msg = "Cannot subtract tz-naive and tz-aware datetime"
|
|
with pytest.raises(TypeError, match=msg):
|
|
dtarr - dt64vals
|
|
with pytest.raises(TypeError, match=msg):
|
|
dt64vals - dtarr
|
|
|
|
# -------------------------------------------------------------
|
|
# Addition of datetime-like others (invalid)
|
|
|
|
def test_dt64arr_add_dtlike_raises(self, tz_naive_fixture, box_with_array):
|
|
# GH#22163 ensure DataFrame doesn't cast Timestamp to i8
|
|
# GH#9631
|
|
tz = tz_naive_fixture
|
|
|
|
dti = date_range("2016-01-01", periods=3, tz=tz)
|
|
if tz is None:
|
|
dti2 = dti.tz_localize("US/Eastern")
|
|
else:
|
|
dti2 = dti.tz_localize(None)
|
|
dtarr = tm.box_expected(dti, box_with_array)
|
|
|
|
assert_cannot_add(dtarr, dti.values)
|
|
assert_cannot_add(dtarr, dti)
|
|
assert_cannot_add(dtarr, dtarr)
|
|
assert_cannot_add(dtarr, dti[0])
|
|
assert_cannot_add(dtarr, dti[0].to_pydatetime())
|
|
assert_cannot_add(dtarr, dti[0].to_datetime64())
|
|
assert_cannot_add(dtarr, dti2[0])
|
|
assert_cannot_add(dtarr, dti2[0].to_pydatetime())
|
|
assert_cannot_add(dtarr, np.datetime64("2011-01-01", "D"))
|
|
|
|
# -------------------------------------------------------------
|
|
# Other Invalid Addition/Subtraction
|
|
|
|
# Note: freq here includes both Tick and non-Tick offsets; this is
|
|
# relevant because historically integer-addition was allowed if we had
|
|
# a freq.
|
|
@pytest.mark.parametrize("freq", ["H", "D", "W", "M", "MS", "Q", "B", None])
|
|
@pytest.mark.parametrize("dtype", [None, "uint8"])
|
|
def test_dt64arr_addsub_intlike(
|
|
self, dtype, box_with_array, freq, tz_naive_fixture
|
|
):
|
|
# GH#19959, GH#19123, GH#19012
|
|
tz = tz_naive_fixture
|
|
if box_with_array is pd.DataFrame:
|
|
# alignment headaches
|
|
return
|
|
|
|
if freq is None:
|
|
dti = DatetimeIndex(["NaT", "2017-04-05 06:07:08"], tz=tz)
|
|
else:
|
|
dti = date_range("2016-01-01", periods=2, freq=freq, tz=tz)
|
|
|
|
obj = box_with_array(dti)
|
|
other = np.array([4, -1])
|
|
if dtype is not None:
|
|
other = other.astype(dtype)
|
|
|
|
msg = "|".join(
|
|
[
|
|
"Addition/subtraction of integers",
|
|
"cannot subtract DatetimeArray from",
|
|
# IntegerArray
|
|
"can only perform ops with numeric values",
|
|
"unsupported operand type.*Categorical",
|
|
r"unsupported operand type\(s\) for -: 'int' and 'Timestamp'",
|
|
]
|
|
)
|
|
assert_invalid_addsub_type(obj, 1, msg)
|
|
assert_invalid_addsub_type(obj, np.int64(2), msg)
|
|
assert_invalid_addsub_type(obj, np.array(3, dtype=np.int64), msg)
|
|
assert_invalid_addsub_type(obj, other, msg)
|
|
assert_invalid_addsub_type(obj, np.array(other), msg)
|
|
assert_invalid_addsub_type(obj, pd.array(other), msg)
|
|
assert_invalid_addsub_type(obj, pd.Categorical(other), msg)
|
|
assert_invalid_addsub_type(obj, pd.Index(other), msg)
|
|
assert_invalid_addsub_type(obj, Series(other), msg)
|
|
|
|
@pytest.mark.parametrize(
|
|
"other",
|
|
[
|
|
3.14,
|
|
np.array([2.0, 3.0]),
|
|
# GH#13078 datetime +/- Period is invalid
|
|
Period("2011-01-01", freq="D"),
|
|
# https://github.com/pandas-dev/pandas/issues/10329
|
|
time(1, 2, 3),
|
|
],
|
|
)
|
|
@pytest.mark.parametrize("dti_freq", [None, "D"])
|
|
def test_dt64arr_add_sub_invalid(self, dti_freq, other, box_with_array):
|
|
dti = DatetimeIndex(["2011-01-01", "2011-01-02"], freq=dti_freq)
|
|
dtarr = tm.box_expected(dti, box_with_array)
|
|
msg = "|".join(
|
|
[
|
|
"unsupported operand type",
|
|
"cannot (add|subtract)",
|
|
"cannot use operands with types",
|
|
"ufunc '?(add|subtract)'? cannot use operands with types",
|
|
"Concatenation operation is not implemented for NumPy arrays",
|
|
]
|
|
)
|
|
assert_invalid_addsub_type(dtarr, other, msg)
|
|
|
|
@pytest.mark.parametrize("pi_freq", ["D", "W", "Q", "H"])
|
|
@pytest.mark.parametrize("dti_freq", [None, "D"])
|
|
def test_dt64arr_add_sub_parr(
|
|
self, dti_freq, pi_freq, box_with_array, box_with_array2
|
|
):
|
|
# GH#20049 subtracting PeriodIndex should raise TypeError
|
|
dti = DatetimeIndex(["2011-01-01", "2011-01-02"], freq=dti_freq)
|
|
pi = dti.to_period(pi_freq)
|
|
|
|
dtarr = tm.box_expected(dti, box_with_array)
|
|
parr = tm.box_expected(pi, box_with_array2)
|
|
msg = "|".join(
|
|
[
|
|
"cannot (add|subtract)",
|
|
"unsupported operand",
|
|
"descriptor.*requires",
|
|
"ufunc.*cannot use operands",
|
|
]
|
|
)
|
|
assert_invalid_addsub_type(dtarr, parr, msg)
|
|
|
|
def test_dt64arr_addsub_time_objects_raises(self, box_with_array, tz_naive_fixture):
|
|
# https://github.com/pandas-dev/pandas/issues/10329
|
|
|
|
tz = tz_naive_fixture
|
|
|
|
obj1 = date_range("2012-01-01", periods=3, tz=tz)
|
|
obj2 = [time(i, i, i) for i in range(3)]
|
|
|
|
obj1 = tm.box_expected(obj1, box_with_array)
|
|
obj2 = tm.box_expected(obj2, box_with_array)
|
|
|
|
msg = "|".join(
|
|
[
|
|
"unsupported operand",
|
|
"cannot subtract DatetimeArray from ndarray",
|
|
]
|
|
)
|
|
|
|
with warnings.catch_warnings(record=True):
|
|
# pandas.errors.PerformanceWarning: Non-vectorized DateOffset being
|
|
# applied to Series or DatetimeIndex
|
|
# we aren't testing that here, so ignore.
|
|
warnings.simplefilter("ignore", PerformanceWarning)
|
|
|
|
assert_invalid_addsub_type(obj1, obj2, msg=msg)
|
|
|
|
# -------------------------------------------------------------
|
|
# Other invalid operations
|
|
|
|
@pytest.mark.parametrize(
|
|
"dt64_series",
|
|
[
|
|
Series([Timestamp("19900315"), Timestamp("19900315")]),
|
|
Series([NaT, Timestamp("19900315")]),
|
|
Series([NaT, NaT], dtype="datetime64[ns]"),
|
|
],
|
|
)
|
|
@pytest.mark.parametrize("one", [1, 1.0, np.array(1)])
|
|
def test_dt64_mul_div_numeric_invalid(self, one, dt64_series, box_with_array):
|
|
obj = tm.box_expected(dt64_series, box_with_array)
|
|
|
|
msg = "cannot perform .* with this index type"
|
|
|
|
# multiplication
|
|
with pytest.raises(TypeError, match=msg):
|
|
obj * one
|
|
with pytest.raises(TypeError, match=msg):
|
|
one * obj
|
|
|
|
# division
|
|
with pytest.raises(TypeError, match=msg):
|
|
obj / one
|
|
with pytest.raises(TypeError, match=msg):
|
|
one / obj
|
|
|
|
|
|
class TestDatetime64DateOffsetArithmetic:
|
|
# -------------------------------------------------------------
|
|
# Tick DateOffsets
|
|
|
|
# TODO: parametrize over timezone?
|
|
def test_dt64arr_series_add_tick_DateOffset(self, box_with_array):
|
|
# GH#4532
|
|
# operate with pd.offsets
|
|
ser = Series([Timestamp("20130101 9:01"), Timestamp("20130101 9:02")])
|
|
expected = Series(
|
|
[Timestamp("20130101 9:01:05"), Timestamp("20130101 9:02:05")]
|
|
)
|
|
|
|
ser = tm.box_expected(ser, box_with_array)
|
|
expected = tm.box_expected(expected, box_with_array)
|
|
|
|
result = ser + pd.offsets.Second(5)
|
|
tm.assert_equal(result, expected)
|
|
|
|
result2 = pd.offsets.Second(5) + ser
|
|
tm.assert_equal(result2, expected)
|
|
|
|
def test_dt64arr_series_sub_tick_DateOffset(self, box_with_array):
|
|
# GH#4532
|
|
# operate with pd.offsets
|
|
ser = Series([Timestamp("20130101 9:01"), Timestamp("20130101 9:02")])
|
|
expected = Series(
|
|
[Timestamp("20130101 9:00:55"), Timestamp("20130101 9:01:55")]
|
|
)
|
|
|
|
ser = tm.box_expected(ser, box_with_array)
|
|
expected = tm.box_expected(expected, box_with_array)
|
|
|
|
result = ser - pd.offsets.Second(5)
|
|
tm.assert_equal(result, expected)
|
|
|
|
result2 = -pd.offsets.Second(5) + ser
|
|
tm.assert_equal(result2, expected)
|
|
msg = "(bad|unsupported) operand type for unary"
|
|
with pytest.raises(TypeError, match=msg):
|
|
pd.offsets.Second(5) - ser
|
|
|
|
@pytest.mark.parametrize(
|
|
"cls_name", ["Day", "Hour", "Minute", "Second", "Milli", "Micro", "Nano"]
|
|
)
|
|
def test_dt64arr_add_sub_tick_DateOffset_smoke(self, cls_name, box_with_array):
|
|
# GH#4532
|
|
# smoke tests for valid DateOffsets
|
|
ser = Series([Timestamp("20130101 9:01"), Timestamp("20130101 9:02")])
|
|
ser = tm.box_expected(ser, box_with_array)
|
|
|
|
offset_cls = getattr(pd.offsets, cls_name)
|
|
ser + offset_cls(5)
|
|
offset_cls(5) + ser
|
|
ser - offset_cls(5)
|
|
|
|
def test_dti_add_tick_tzaware(self, tz_aware_fixture, box_with_array):
|
|
# GH#21610, GH#22163 ensure DataFrame doesn't return object-dtype
|
|
tz = tz_aware_fixture
|
|
if tz == "US/Pacific":
|
|
dates = date_range("2012-11-01", periods=3, tz=tz)
|
|
offset = dates + pd.offsets.Hour(5)
|
|
assert dates[0] + pd.offsets.Hour(5) == offset[0]
|
|
|
|
dates = date_range("2010-11-01 00:00", periods=3, tz=tz, freq="H")
|
|
expected = DatetimeIndex(
|
|
["2010-11-01 05:00", "2010-11-01 06:00", "2010-11-01 07:00"],
|
|
freq="H",
|
|
tz=tz,
|
|
)
|
|
|
|
dates = tm.box_expected(dates, box_with_array)
|
|
expected = tm.box_expected(expected, box_with_array)
|
|
|
|
for scalar in [pd.offsets.Hour(5), np.timedelta64(5, "h"), timedelta(hours=5)]:
|
|
offset = dates + scalar
|
|
tm.assert_equal(offset, expected)
|
|
offset = scalar + dates
|
|
tm.assert_equal(offset, expected)
|
|
|
|
roundtrip = offset - scalar
|
|
tm.assert_equal(roundtrip, dates)
|
|
|
|
msg = "|".join(
|
|
["bad operand type for unary -", "cannot subtract DatetimeArray"]
|
|
)
|
|
with pytest.raises(TypeError, match=msg):
|
|
scalar - dates
|
|
|
|
# -------------------------------------------------------------
|
|
# RelativeDelta DateOffsets
|
|
|
|
def test_dt64arr_add_sub_relativedelta_offsets(self, box_with_array):
|
|
# GH#10699
|
|
vec = DatetimeIndex(
|
|
[
|
|
Timestamp("2000-01-05 00:15:00"),
|
|
Timestamp("2000-01-31 00:23:00"),
|
|
Timestamp("2000-01-01"),
|
|
Timestamp("2000-03-31"),
|
|
Timestamp("2000-02-29"),
|
|
Timestamp("2000-12-31"),
|
|
Timestamp("2000-05-15"),
|
|
Timestamp("2001-06-15"),
|
|
]
|
|
)
|
|
vec = tm.box_expected(vec, box_with_array)
|
|
vec_items = vec.iloc[0] if box_with_array is pd.DataFrame else vec
|
|
|
|
# DateOffset relativedelta fastpath
|
|
relative_kwargs = [
|
|
("years", 2),
|
|
("months", 5),
|
|
("days", 3),
|
|
("hours", 5),
|
|
("minutes", 10),
|
|
("seconds", 2),
|
|
("microseconds", 5),
|
|
]
|
|
for i, (unit, value) in enumerate(relative_kwargs):
|
|
off = DateOffset(**{unit: value})
|
|
|
|
expected = DatetimeIndex([x + off for x in vec_items])
|
|
expected = tm.box_expected(expected, box_with_array)
|
|
tm.assert_equal(expected, vec + off)
|
|
|
|
expected = DatetimeIndex([x - off for x in vec_items])
|
|
expected = tm.box_expected(expected, box_with_array)
|
|
tm.assert_equal(expected, vec - off)
|
|
|
|
off = DateOffset(**dict(relative_kwargs[: i + 1]))
|
|
|
|
expected = DatetimeIndex([x + off for x in vec_items])
|
|
expected = tm.box_expected(expected, box_with_array)
|
|
tm.assert_equal(expected, vec + off)
|
|
|
|
expected = DatetimeIndex([x - off for x in vec_items])
|
|
expected = tm.box_expected(expected, box_with_array)
|
|
tm.assert_equal(expected, vec - off)
|
|
msg = "(bad|unsupported) operand type for unary"
|
|
with pytest.raises(TypeError, match=msg):
|
|
off - vec
|
|
|
|
# -------------------------------------------------------------
|
|
# Non-Tick, Non-RelativeDelta DateOffsets
|
|
|
|
# TODO: redundant with test_dt64arr_add_sub_DateOffset? that includes
|
|
# tz-aware cases which this does not
|
|
@pytest.mark.parametrize(
|
|
"cls_and_kwargs",
|
|
[
|
|
"YearBegin",
|
|
("YearBegin", {"month": 5}),
|
|
"YearEnd",
|
|
("YearEnd", {"month": 5}),
|
|
"MonthBegin",
|
|
"MonthEnd",
|
|
"SemiMonthEnd",
|
|
"SemiMonthBegin",
|
|
"Week",
|
|
("Week", {"weekday": 3}),
|
|
"Week",
|
|
("Week", {"weekday": 6}),
|
|
"BusinessDay",
|
|
"BDay",
|
|
"QuarterEnd",
|
|
"QuarterBegin",
|
|
"CustomBusinessDay",
|
|
"CDay",
|
|
"CBMonthEnd",
|
|
"CBMonthBegin",
|
|
"BMonthBegin",
|
|
"BMonthEnd",
|
|
"BusinessHour",
|
|
"BYearBegin",
|
|
"BYearEnd",
|
|
"BQuarterBegin",
|
|
("LastWeekOfMonth", {"weekday": 2}),
|
|
(
|
|
"FY5253Quarter",
|
|
{
|
|
"qtr_with_extra_week": 1,
|
|
"startingMonth": 1,
|
|
"weekday": 2,
|
|
"variation": "nearest",
|
|
},
|
|
),
|
|
("FY5253", {"weekday": 0, "startingMonth": 2, "variation": "nearest"}),
|
|
("WeekOfMonth", {"weekday": 2, "week": 2}),
|
|
"Easter",
|
|
("DateOffset", {"day": 4}),
|
|
("DateOffset", {"month": 5}),
|
|
],
|
|
)
|
|
@pytest.mark.parametrize("normalize", [True, False])
|
|
@pytest.mark.parametrize("n", [0, 5])
|
|
def test_dt64arr_add_sub_DateOffsets(
|
|
self, box_with_array, n, normalize, cls_and_kwargs
|
|
):
|
|
# GH#10699
|
|
# assert vectorized operation matches pointwise operations
|
|
|
|
if isinstance(cls_and_kwargs, tuple):
|
|
# If cls_name param is a tuple, then 2nd entry is kwargs for
|
|
# the offset constructor
|
|
cls_name, kwargs = cls_and_kwargs
|
|
else:
|
|
cls_name = cls_and_kwargs
|
|
kwargs = {}
|
|
|
|
if n == 0 and cls_name in [
|
|
"WeekOfMonth",
|
|
"LastWeekOfMonth",
|
|
"FY5253Quarter",
|
|
"FY5253",
|
|
]:
|
|
# passing n = 0 is invalid for these offset classes
|
|
return
|
|
|
|
vec = DatetimeIndex(
|
|
[
|
|
Timestamp("2000-01-05 00:15:00"),
|
|
Timestamp("2000-01-31 00:23:00"),
|
|
Timestamp("2000-01-01"),
|
|
Timestamp("2000-03-31"),
|
|
Timestamp("2000-02-29"),
|
|
Timestamp("2000-12-31"),
|
|
Timestamp("2000-05-15"),
|
|
Timestamp("2001-06-15"),
|
|
]
|
|
)
|
|
vec = tm.box_expected(vec, box_with_array)
|
|
vec_items = vec.iloc[0] if box_with_array is pd.DataFrame else vec
|
|
|
|
offset_cls = getattr(pd.offsets, cls_name)
|
|
|
|
with warnings.catch_warnings(record=True):
|
|
# pandas.errors.PerformanceWarning: Non-vectorized DateOffset being
|
|
# applied to Series or DatetimeIndex
|
|
# we aren't testing that here, so ignore.
|
|
warnings.simplefilter("ignore", PerformanceWarning)
|
|
|
|
offset = offset_cls(n, normalize=normalize, **kwargs)
|
|
|
|
expected = DatetimeIndex([x + offset for x in vec_items])
|
|
expected = tm.box_expected(expected, box_with_array)
|
|
tm.assert_equal(expected, vec + offset)
|
|
|
|
expected = DatetimeIndex([x - offset for x in vec_items])
|
|
expected = tm.box_expected(expected, box_with_array)
|
|
tm.assert_equal(expected, vec - offset)
|
|
|
|
expected = DatetimeIndex([offset + x for x in vec_items])
|
|
expected = tm.box_expected(expected, box_with_array)
|
|
tm.assert_equal(expected, offset + vec)
|
|
msg = "(bad|unsupported) operand type for unary"
|
|
with pytest.raises(TypeError, match=msg):
|
|
offset - vec
|
|
|
|
def test_dt64arr_add_sub_DateOffset(self, box_with_array):
|
|
# GH#10699
|
|
s = date_range("2000-01-01", "2000-01-31", name="a")
|
|
s = tm.box_expected(s, box_with_array)
|
|
result = s + DateOffset(years=1)
|
|
result2 = DateOffset(years=1) + s
|
|
exp = date_range("2001-01-01", "2001-01-31", name="a")._with_freq(None)
|
|
exp = tm.box_expected(exp, box_with_array)
|
|
tm.assert_equal(result, exp)
|
|
tm.assert_equal(result2, exp)
|
|
|
|
result = s - DateOffset(years=1)
|
|
exp = date_range("1999-01-01", "1999-01-31", name="a")._with_freq(None)
|
|
exp = tm.box_expected(exp, box_with_array)
|
|
tm.assert_equal(result, exp)
|
|
|
|
s = DatetimeIndex(
|
|
[
|
|
Timestamp("2000-01-15 00:15:00", tz="US/Central"),
|
|
Timestamp("2000-02-15", tz="US/Central"),
|
|
],
|
|
name="a",
|
|
)
|
|
s = tm.box_expected(s, box_with_array)
|
|
result = s + pd.offsets.Day()
|
|
result2 = pd.offsets.Day() + s
|
|
exp = DatetimeIndex(
|
|
[
|
|
Timestamp("2000-01-16 00:15:00", tz="US/Central"),
|
|
Timestamp("2000-02-16", tz="US/Central"),
|
|
],
|
|
name="a",
|
|
)
|
|
exp = tm.box_expected(exp, box_with_array)
|
|
tm.assert_equal(result, exp)
|
|
tm.assert_equal(result2, exp)
|
|
|
|
s = DatetimeIndex(
|
|
[
|
|
Timestamp("2000-01-15 00:15:00", tz="US/Central"),
|
|
Timestamp("2000-02-15", tz="US/Central"),
|
|
],
|
|
name="a",
|
|
)
|
|
s = tm.box_expected(s, box_with_array)
|
|
result = s + pd.offsets.MonthEnd()
|
|
result2 = pd.offsets.MonthEnd() + s
|
|
exp = DatetimeIndex(
|
|
[
|
|
Timestamp("2000-01-31 00:15:00", tz="US/Central"),
|
|
Timestamp("2000-02-29", tz="US/Central"),
|
|
],
|
|
name="a",
|
|
)
|
|
exp = tm.box_expected(exp, box_with_array)
|
|
tm.assert_equal(result, exp)
|
|
tm.assert_equal(result2, exp)
|
|
|
|
@pytest.mark.parametrize(
|
|
"other",
|
|
[
|
|
np.array([pd.offsets.MonthEnd(), pd.offsets.Day(n=2)]),
|
|
np.array([pd.offsets.DateOffset(years=1), pd.offsets.MonthEnd()]),
|
|
np.array( # matching offsets
|
|
[pd.offsets.DateOffset(years=1), pd.offsets.DateOffset(years=1)]
|
|
),
|
|
],
|
|
)
|
|
@pytest.mark.parametrize("op", [operator.add, roperator.radd, operator.sub])
|
|
@pytest.mark.parametrize("box_other", [True, False])
|
|
def test_dt64arr_add_sub_offset_array(
|
|
self, tz_naive_fixture, box_with_array, box_other, op, other
|
|
):
|
|
# GH#18849
|
|
# GH#10699 array of offsets
|
|
|
|
tz = tz_naive_fixture
|
|
dti = date_range("2017-01-01", periods=2, tz=tz)
|
|
dtarr = tm.box_expected(dti, box_with_array)
|
|
|
|
other = np.array([pd.offsets.MonthEnd(), pd.offsets.Day(n=2)])
|
|
expected = DatetimeIndex([op(dti[n], other[n]) for n in range(len(dti))])
|
|
expected = tm.box_expected(expected, box_with_array).astype(object)
|
|
|
|
if box_other:
|
|
other = tm.box_expected(other, box_with_array)
|
|
if box_with_array is pd.array and op is roperator.radd:
|
|
# We expect a PandasArray, not ndarray[object] here
|
|
expected = pd.array(expected, dtype=object)
|
|
|
|
with tm.assert_produces_warning(PerformanceWarning):
|
|
res = op(dtarr, other)
|
|
|
|
tm.assert_equal(res, expected)
|
|
|
|
@pytest.mark.parametrize(
|
|
"op, offset, exp, exp_freq",
|
|
[
|
|
(
|
|
"__add__",
|
|
DateOffset(months=3, days=10),
|
|
[
|
|
Timestamp("2014-04-11"),
|
|
Timestamp("2015-04-11"),
|
|
Timestamp("2016-04-11"),
|
|
Timestamp("2017-04-11"),
|
|
],
|
|
None,
|
|
),
|
|
(
|
|
"__add__",
|
|
DateOffset(months=3),
|
|
[
|
|
Timestamp("2014-04-01"),
|
|
Timestamp("2015-04-01"),
|
|
Timestamp("2016-04-01"),
|
|
Timestamp("2017-04-01"),
|
|
],
|
|
"AS-APR",
|
|
),
|
|
(
|
|
"__sub__",
|
|
DateOffset(months=3, days=10),
|
|
[
|
|
Timestamp("2013-09-21"),
|
|
Timestamp("2014-09-21"),
|
|
Timestamp("2015-09-21"),
|
|
Timestamp("2016-09-21"),
|
|
],
|
|
None,
|
|
),
|
|
(
|
|
"__sub__",
|
|
DateOffset(months=3),
|
|
[
|
|
Timestamp("2013-10-01"),
|
|
Timestamp("2014-10-01"),
|
|
Timestamp("2015-10-01"),
|
|
Timestamp("2016-10-01"),
|
|
],
|
|
"AS-OCT",
|
|
),
|
|
],
|
|
)
|
|
def test_dti_add_sub_nonzero_mth_offset(
|
|
self, op, offset, exp, exp_freq, tz_aware_fixture, box_with_array
|
|
):
|
|
# GH 26258
|
|
tz = tz_aware_fixture
|
|
date = date_range(start="01 Jan 2014", end="01 Jan 2017", freq="AS", tz=tz)
|
|
date = tm.box_expected(date, box_with_array, False)
|
|
mth = getattr(date, op)
|
|
result = mth(offset)
|
|
|
|
expected = DatetimeIndex(exp, tz=tz)
|
|
expected = tm.box_expected(expected, box_with_array, False)
|
|
tm.assert_equal(result, expected)
|
|
|
|
|
|
class TestDatetime64OverflowHandling:
|
|
# TODO: box + de-duplicate
|
|
|
|
def test_dt64_overflow_masking(self, box_with_array):
|
|
# GH#25317
|
|
left = Series([Timestamp("1969-12-31")])
|
|
right = Series([NaT])
|
|
|
|
left = tm.box_expected(left, box_with_array)
|
|
right = tm.box_expected(right, box_with_array)
|
|
|
|
expected = TimedeltaIndex([NaT])
|
|
expected = tm.box_expected(expected, box_with_array)
|
|
|
|
result = left - right
|
|
tm.assert_equal(result, expected)
|
|
|
|
def test_dt64_series_arith_overflow(self):
|
|
# GH#12534, fixed by GH#19024
|
|
dt = Timestamp("1700-01-31")
|
|
td = Timedelta("20000 Days")
|
|
dti = date_range("1949-09-30", freq="100Y", periods=4)
|
|
ser = Series(dti)
|
|
msg = "Overflow in int64 addition"
|
|
with pytest.raises(OverflowError, match=msg):
|
|
ser - dt
|
|
with pytest.raises(OverflowError, match=msg):
|
|
dt - ser
|
|
with pytest.raises(OverflowError, match=msg):
|
|
ser + td
|
|
with pytest.raises(OverflowError, match=msg):
|
|
td + ser
|
|
|
|
ser.iloc[-1] = NaT
|
|
expected = Series(
|
|
["2004-10-03", "2104-10-04", "2204-10-04", "NaT"], dtype="datetime64[ns]"
|
|
)
|
|
res = ser + td
|
|
tm.assert_series_equal(res, expected)
|
|
res = td + ser
|
|
tm.assert_series_equal(res, expected)
|
|
|
|
ser.iloc[1:] = NaT
|
|
expected = Series(["91279 Days", "NaT", "NaT", "NaT"], dtype="timedelta64[ns]")
|
|
res = ser - dt
|
|
tm.assert_series_equal(res, expected)
|
|
res = dt - ser
|
|
tm.assert_series_equal(res, -expected)
|
|
|
|
def test_datetimeindex_sub_timestamp_overflow(self):
|
|
dtimax = pd.to_datetime(["2021-12-28 17:19", Timestamp.max])
|
|
dtimin = pd.to_datetime(["2021-12-28 17:19", Timestamp.min])
|
|
|
|
tsneg = Timestamp("1950-01-01").as_unit("ns")
|
|
ts_neg_variants = [
|
|
tsneg,
|
|
tsneg.to_pydatetime(),
|
|
tsneg.to_datetime64().astype("datetime64[ns]"),
|
|
tsneg.to_datetime64().astype("datetime64[D]"),
|
|
]
|
|
|
|
tspos = Timestamp("1980-01-01").as_unit("ns")
|
|
ts_pos_variants = [
|
|
tspos,
|
|
tspos.to_pydatetime(),
|
|
tspos.to_datetime64().astype("datetime64[ns]"),
|
|
tspos.to_datetime64().astype("datetime64[D]"),
|
|
]
|
|
msg = "Overflow in int64 addition"
|
|
for variant in ts_neg_variants:
|
|
with pytest.raises(OverflowError, match=msg):
|
|
dtimax - variant
|
|
|
|
expected = Timestamp.max._value - tspos._value
|
|
for variant in ts_pos_variants:
|
|
res = dtimax - variant
|
|
assert res[1]._value == expected
|
|
|
|
expected = Timestamp.min._value - tsneg._value
|
|
for variant in ts_neg_variants:
|
|
res = dtimin - variant
|
|
assert res[1]._value == expected
|
|
|
|
for variant in ts_pos_variants:
|
|
with pytest.raises(OverflowError, match=msg):
|
|
dtimin - variant
|
|
|
|
def test_datetimeindex_sub_datetimeindex_overflow(self):
|
|
# GH#22492, GH#22508
|
|
dtimax = pd.to_datetime(["2021-12-28 17:19", Timestamp.max])
|
|
dtimin = pd.to_datetime(["2021-12-28 17:19", Timestamp.min])
|
|
|
|
ts_neg = pd.to_datetime(["1950-01-01", "1950-01-01"])
|
|
ts_pos = pd.to_datetime(["1980-01-01", "1980-01-01"])
|
|
|
|
# General tests
|
|
expected = Timestamp.max._value - ts_pos[1]._value
|
|
result = dtimax - ts_pos
|
|
assert result[1]._value == expected
|
|
|
|
expected = Timestamp.min._value - ts_neg[1]._value
|
|
result = dtimin - ts_neg
|
|
assert result[1]._value == expected
|
|
msg = "Overflow in int64 addition"
|
|
with pytest.raises(OverflowError, match=msg):
|
|
dtimax - ts_neg
|
|
|
|
with pytest.raises(OverflowError, match=msg):
|
|
dtimin - ts_pos
|
|
|
|
# Edge cases
|
|
tmin = pd.to_datetime([Timestamp.min])
|
|
t1 = tmin + Timedelta.max + Timedelta("1us")
|
|
with pytest.raises(OverflowError, match=msg):
|
|
t1 - tmin
|
|
|
|
tmax = pd.to_datetime([Timestamp.max])
|
|
t2 = tmax + Timedelta.min - Timedelta("1us")
|
|
with pytest.raises(OverflowError, match=msg):
|
|
tmax - t2
|
|
|
|
|
|
class TestTimestampSeriesArithmetic:
|
|
def test_empty_series_add_sub(self, box_with_array):
|
|
# GH#13844
|
|
a = Series(dtype="M8[ns]")
|
|
b = Series(dtype="m8[ns]")
|
|
a = box_with_array(a)
|
|
b = box_with_array(b)
|
|
tm.assert_equal(a, a + b)
|
|
tm.assert_equal(a, a - b)
|
|
tm.assert_equal(a, b + a)
|
|
msg = "cannot subtract"
|
|
with pytest.raises(TypeError, match=msg):
|
|
b - a
|
|
|
|
def test_operators_datetimelike(self):
|
|
# ## timedelta64 ###
|
|
td1 = Series([timedelta(minutes=5, seconds=3)] * 3)
|
|
td1.iloc[2] = np.nan
|
|
|
|
# ## datetime64 ###
|
|
dt1 = Series(
|
|
[
|
|
Timestamp("20111230"),
|
|
Timestamp("20120101"),
|
|
Timestamp("20120103"),
|
|
]
|
|
)
|
|
dt1.iloc[2] = np.nan
|
|
dt2 = Series(
|
|
[
|
|
Timestamp("20111231"),
|
|
Timestamp("20120102"),
|
|
Timestamp("20120104"),
|
|
]
|
|
)
|
|
dt1 - dt2
|
|
dt2 - dt1
|
|
|
|
# datetime64 with timetimedelta
|
|
dt1 + td1
|
|
td1 + dt1
|
|
dt1 - td1
|
|
|
|
# timetimedelta with datetime64
|
|
td1 + dt1
|
|
dt1 + td1
|
|
|
|
def test_dt64ser_sub_datetime_dtype(self):
|
|
ts = Timestamp(datetime(1993, 1, 7, 13, 30, 00))
|
|
dt = datetime(1993, 6, 22, 13, 30)
|
|
ser = Series([ts])
|
|
result = pd.to_timedelta(np.abs(ser - dt))
|
|
assert result.dtype == "timedelta64[ns]"
|
|
|
|
# -------------------------------------------------------------
|
|
# TODO: This next block of tests came from tests.series.test_operators,
|
|
# needs to be de-duplicated and parametrized over `box` classes
|
|
|
|
@pytest.mark.parametrize(
|
|
"left, right, op_fail",
|
|
[
|
|
[
|
|
[Timestamp("20111230"), Timestamp("20120101"), NaT],
|
|
[Timestamp("20111231"), Timestamp("20120102"), Timestamp("20120104")],
|
|
["__sub__", "__rsub__"],
|
|
],
|
|
[
|
|
[Timestamp("20111230"), Timestamp("20120101"), NaT],
|
|
[timedelta(minutes=5, seconds=3), timedelta(minutes=5, seconds=3), NaT],
|
|
["__add__", "__radd__", "__sub__"],
|
|
],
|
|
[
|
|
[
|
|
Timestamp("20111230", tz="US/Eastern"),
|
|
Timestamp("20111230", tz="US/Eastern"),
|
|
NaT,
|
|
],
|
|
[timedelta(minutes=5, seconds=3), NaT, timedelta(minutes=5, seconds=3)],
|
|
["__add__", "__radd__", "__sub__"],
|
|
],
|
|
],
|
|
)
|
|
def test_operators_datetimelike_invalid(
|
|
self, left, right, op_fail, all_arithmetic_operators
|
|
):
|
|
# these are all TypeError ops
|
|
op_str = all_arithmetic_operators
|
|
arg1 = Series(left)
|
|
arg2 = Series(right)
|
|
# check that we are getting a TypeError
|
|
# with 'operate' (from core/ops.py) for the ops that are not
|
|
# defined
|
|
op = getattr(arg1, op_str, None)
|
|
# Previously, _validate_for_numeric_binop in core/indexes/base.py
|
|
# did this for us.
|
|
if op_str not in op_fail:
|
|
with pytest.raises(
|
|
TypeError, match="operate|[cC]annot|unsupported operand"
|
|
):
|
|
op(arg2)
|
|
else:
|
|
# Smoke test
|
|
op(arg2)
|
|
|
|
def test_sub_single_tz(self):
|
|
# GH#12290
|
|
s1 = Series([Timestamp("2016-02-10", tz="America/Sao_Paulo")])
|
|
s2 = Series([Timestamp("2016-02-08", tz="America/Sao_Paulo")])
|
|
result = s1 - s2
|
|
expected = Series([Timedelta("2days")])
|
|
tm.assert_series_equal(result, expected)
|
|
result = s2 - s1
|
|
expected = Series([Timedelta("-2days")])
|
|
tm.assert_series_equal(result, expected)
|
|
|
|
def test_dt64tz_series_sub_dtitz(self):
|
|
# GH#19071 subtracting tzaware DatetimeIndex from tzaware Series
|
|
# (with same tz) raises, fixed by #19024
|
|
dti = date_range("1999-09-30", periods=10, tz="US/Pacific")
|
|
ser = Series(dti)
|
|
expected = Series(TimedeltaIndex(["0days"] * 10))
|
|
|
|
res = dti - ser
|
|
tm.assert_series_equal(res, expected)
|
|
res = ser - dti
|
|
tm.assert_series_equal(res, expected)
|
|
|
|
def test_sub_datetime_compat(self):
|
|
# see GH#14088
|
|
s = Series([datetime(2016, 8, 23, 12, tzinfo=pytz.utc), NaT])
|
|
dt = datetime(2016, 8, 22, 12, tzinfo=pytz.utc)
|
|
exp = Series([Timedelta("1 days"), NaT])
|
|
tm.assert_series_equal(s - dt, exp)
|
|
tm.assert_series_equal(s - Timestamp(dt), exp)
|
|
|
|
def test_dt64_series_add_mixed_tick_DateOffset(self):
|
|
# GH#4532
|
|
# operate with pd.offsets
|
|
s = Series([Timestamp("20130101 9:01"), Timestamp("20130101 9:02")])
|
|
|
|
result = s + pd.offsets.Milli(5)
|
|
result2 = pd.offsets.Milli(5) + s
|
|
expected = Series(
|
|
[Timestamp("20130101 9:01:00.005"), Timestamp("20130101 9:02:00.005")]
|
|
)
|
|
tm.assert_series_equal(result, expected)
|
|
tm.assert_series_equal(result2, expected)
|
|
|
|
result = s + pd.offsets.Minute(5) + pd.offsets.Milli(5)
|
|
expected = Series(
|
|
[Timestamp("20130101 9:06:00.005"), Timestamp("20130101 9:07:00.005")]
|
|
)
|
|
tm.assert_series_equal(result, expected)
|
|
|
|
def test_datetime64_ops_nat(self):
|
|
# GH#11349
|
|
datetime_series = Series([NaT, Timestamp("19900315")])
|
|
nat_series_dtype_timestamp = Series([NaT, NaT], dtype="datetime64[ns]")
|
|
single_nat_dtype_datetime = Series([NaT], dtype="datetime64[ns]")
|
|
|
|
# subtraction
|
|
tm.assert_series_equal(-NaT + datetime_series, nat_series_dtype_timestamp)
|
|
msg = "bad operand type for unary -: 'DatetimeArray'"
|
|
with pytest.raises(TypeError, match=msg):
|
|
-single_nat_dtype_datetime + datetime_series
|
|
|
|
tm.assert_series_equal(
|
|
-NaT + nat_series_dtype_timestamp, nat_series_dtype_timestamp
|
|
)
|
|
with pytest.raises(TypeError, match=msg):
|
|
-single_nat_dtype_datetime + nat_series_dtype_timestamp
|
|
|
|
# addition
|
|
tm.assert_series_equal(
|
|
nat_series_dtype_timestamp + NaT, nat_series_dtype_timestamp
|
|
)
|
|
tm.assert_series_equal(
|
|
NaT + nat_series_dtype_timestamp, nat_series_dtype_timestamp
|
|
)
|
|
|
|
tm.assert_series_equal(
|
|
nat_series_dtype_timestamp + NaT, nat_series_dtype_timestamp
|
|
)
|
|
tm.assert_series_equal(
|
|
NaT + nat_series_dtype_timestamp, nat_series_dtype_timestamp
|
|
)
|
|
|
|
# -------------------------------------------------------------
|
|
# Timezone-Centric Tests
|
|
|
|
def test_operators_datetimelike_with_timezones(self):
|
|
tz = "US/Eastern"
|
|
dt1 = Series(date_range("2000-01-01 09:00:00", periods=5, tz=tz), name="foo")
|
|
dt2 = dt1.copy()
|
|
dt2.iloc[2] = np.nan
|
|
|
|
td1 = Series(pd.timedelta_range("1 days 1 min", periods=5, freq="H"))
|
|
td2 = td1.copy()
|
|
td2.iloc[1] = np.nan
|
|
assert td2._values.freq is None
|
|
|
|
result = dt1 + td1[0]
|
|
exp = (dt1.dt.tz_localize(None) + td1[0]).dt.tz_localize(tz)
|
|
tm.assert_series_equal(result, exp)
|
|
|
|
result = dt2 + td2[0]
|
|
exp = (dt2.dt.tz_localize(None) + td2[0]).dt.tz_localize(tz)
|
|
tm.assert_series_equal(result, exp)
|
|
|
|
# odd numpy behavior with scalar timedeltas
|
|
result = td1[0] + dt1
|
|
exp = (dt1.dt.tz_localize(None) + td1[0]).dt.tz_localize(tz)
|
|
tm.assert_series_equal(result, exp)
|
|
|
|
result = td2[0] + dt2
|
|
exp = (dt2.dt.tz_localize(None) + td2[0]).dt.tz_localize(tz)
|
|
tm.assert_series_equal(result, exp)
|
|
|
|
result = dt1 - td1[0]
|
|
exp = (dt1.dt.tz_localize(None) - td1[0]).dt.tz_localize(tz)
|
|
tm.assert_series_equal(result, exp)
|
|
msg = "(bad|unsupported) operand type for unary"
|
|
with pytest.raises(TypeError, match=msg):
|
|
td1[0] - dt1
|
|
|
|
result = dt2 - td2[0]
|
|
exp = (dt2.dt.tz_localize(None) - td2[0]).dt.tz_localize(tz)
|
|
tm.assert_series_equal(result, exp)
|
|
with pytest.raises(TypeError, match=msg):
|
|
td2[0] - dt2
|
|
|
|
result = dt1 + td1
|
|
exp = (dt1.dt.tz_localize(None) + td1).dt.tz_localize(tz)
|
|
tm.assert_series_equal(result, exp)
|
|
|
|
result = dt2 + td2
|
|
exp = (dt2.dt.tz_localize(None) + td2).dt.tz_localize(tz)
|
|
tm.assert_series_equal(result, exp)
|
|
|
|
result = dt1 - td1
|
|
exp = (dt1.dt.tz_localize(None) - td1).dt.tz_localize(tz)
|
|
tm.assert_series_equal(result, exp)
|
|
|
|
result = dt2 - td2
|
|
exp = (dt2.dt.tz_localize(None) - td2).dt.tz_localize(tz)
|
|
tm.assert_series_equal(result, exp)
|
|
msg = "cannot (add|subtract)"
|
|
with pytest.raises(TypeError, match=msg):
|
|
td1 - dt1
|
|
with pytest.raises(TypeError, match=msg):
|
|
td2 - dt2
|
|
|
|
|
|
class TestDatetimeIndexArithmetic:
|
|
# -------------------------------------------------------------
|
|
# Binary operations DatetimeIndex and TimedeltaIndex/array
|
|
|
|
def test_dti_add_tdi(self, tz_naive_fixture):
|
|
# GH#17558
|
|
tz = tz_naive_fixture
|
|
dti = DatetimeIndex([Timestamp("2017-01-01", tz=tz)] * 10)
|
|
tdi = pd.timedelta_range("0 days", periods=10)
|
|
expected = date_range("2017-01-01", periods=10, tz=tz)
|
|
expected = expected._with_freq(None)
|
|
|
|
# add with TimedeltaIndex
|
|
result = dti + tdi
|
|
tm.assert_index_equal(result, expected)
|
|
|
|
result = tdi + dti
|
|
tm.assert_index_equal(result, expected)
|
|
|
|
# add with timedelta64 array
|
|
result = dti + tdi.values
|
|
tm.assert_index_equal(result, expected)
|
|
|
|
result = tdi.values + dti
|
|
tm.assert_index_equal(result, expected)
|
|
|
|
def test_dti_iadd_tdi(self, tz_naive_fixture):
|
|
# GH#17558
|
|
tz = tz_naive_fixture
|
|
dti = DatetimeIndex([Timestamp("2017-01-01", tz=tz)] * 10)
|
|
tdi = pd.timedelta_range("0 days", periods=10)
|
|
expected = date_range("2017-01-01", periods=10, tz=tz)
|
|
expected = expected._with_freq(None)
|
|
|
|
# iadd with TimedeltaIndex
|
|
result = DatetimeIndex([Timestamp("2017-01-01", tz=tz)] * 10)
|
|
result += tdi
|
|
tm.assert_index_equal(result, expected)
|
|
|
|
result = pd.timedelta_range("0 days", periods=10)
|
|
result += dti
|
|
tm.assert_index_equal(result, expected)
|
|
|
|
# iadd with timedelta64 array
|
|
result = DatetimeIndex([Timestamp("2017-01-01", tz=tz)] * 10)
|
|
result += tdi.values
|
|
tm.assert_index_equal(result, expected)
|
|
|
|
result = pd.timedelta_range("0 days", periods=10)
|
|
result += dti
|
|
tm.assert_index_equal(result, expected)
|
|
|
|
def test_dti_sub_tdi(self, tz_naive_fixture):
|
|
# GH#17558
|
|
tz = tz_naive_fixture
|
|
dti = DatetimeIndex([Timestamp("2017-01-01", tz=tz)] * 10)
|
|
tdi = pd.timedelta_range("0 days", periods=10)
|
|
expected = date_range("2017-01-01", periods=10, tz=tz, freq="-1D")
|
|
expected = expected._with_freq(None)
|
|
|
|
# sub with TimedeltaIndex
|
|
result = dti - tdi
|
|
tm.assert_index_equal(result, expected)
|
|
|
|
msg = "cannot subtract .*TimedeltaArray"
|
|
with pytest.raises(TypeError, match=msg):
|
|
tdi - dti
|
|
|
|
# sub with timedelta64 array
|
|
result = dti - tdi.values
|
|
tm.assert_index_equal(result, expected)
|
|
|
|
msg = "cannot subtract a datelike from a TimedeltaArray"
|
|
with pytest.raises(TypeError, match=msg):
|
|
tdi.values - dti
|
|
|
|
def test_dti_isub_tdi(self, tz_naive_fixture):
|
|
# GH#17558
|
|
tz = tz_naive_fixture
|
|
dti = DatetimeIndex([Timestamp("2017-01-01", tz=tz)] * 10)
|
|
tdi = pd.timedelta_range("0 days", periods=10)
|
|
expected = date_range("2017-01-01", periods=10, tz=tz, freq="-1D")
|
|
expected = expected._with_freq(None)
|
|
|
|
# isub with TimedeltaIndex
|
|
result = DatetimeIndex([Timestamp("2017-01-01", tz=tz)] * 10)
|
|
result -= tdi
|
|
tm.assert_index_equal(result, expected)
|
|
|
|
# DTA.__isub__ GH#43904
|
|
dta = dti._data.copy()
|
|
dta -= tdi
|
|
tm.assert_datetime_array_equal(dta, expected._data)
|
|
|
|
out = dti._data.copy()
|
|
np.subtract(out, tdi, out=out)
|
|
tm.assert_datetime_array_equal(out, expected._data)
|
|
|
|
msg = "cannot subtract a datelike from a TimedeltaArray"
|
|
with pytest.raises(TypeError, match=msg):
|
|
tdi -= dti
|
|
|
|
# isub with timedelta64 array
|
|
result = DatetimeIndex([Timestamp("2017-01-01", tz=tz)] * 10)
|
|
result -= tdi.values
|
|
tm.assert_index_equal(result, expected)
|
|
|
|
with pytest.raises(TypeError, match=msg):
|
|
tdi.values -= dti
|
|
|
|
with pytest.raises(TypeError, match=msg):
|
|
tdi._values -= dti
|
|
|
|
# -------------------------------------------------------------
|
|
# Binary Operations DatetimeIndex and datetime-like
|
|
# TODO: A couple other tests belong in this section. Move them in
|
|
# A PR where there isn't already a giant diff.
|
|
|
|
# -------------------------------------------------------------
|
|
|
|
def test_dta_add_sub_index(self, tz_naive_fixture):
|
|
# Check that DatetimeArray defers to Index classes
|
|
dti = date_range("20130101", periods=3, tz=tz_naive_fixture)
|
|
dta = dti.array
|
|
result = dta - dti
|
|
expected = dti - dti
|
|
tm.assert_index_equal(result, expected)
|
|
|
|
tdi = result
|
|
result = dta + tdi
|
|
expected = dti + tdi
|
|
tm.assert_index_equal(result, expected)
|
|
|
|
result = dta - tdi
|
|
expected = dti - tdi
|
|
tm.assert_index_equal(result, expected)
|
|
|
|
def test_sub_dti_dti(self):
|
|
# previously performed setop (deprecated in 0.16.0), now changed to
|
|
# return subtraction -> TimeDeltaIndex (GH ...)
|
|
|
|
dti = date_range("20130101", periods=3)
|
|
dti_tz = date_range("20130101", periods=3).tz_localize("US/Eastern")
|
|
expected = TimedeltaIndex([0, 0, 0])
|
|
|
|
result = dti - dti
|
|
tm.assert_index_equal(result, expected)
|
|
|
|
result = dti_tz - dti_tz
|
|
tm.assert_index_equal(result, expected)
|
|
msg = "Cannot subtract tz-naive and tz-aware datetime-like objects"
|
|
with pytest.raises(TypeError, match=msg):
|
|
dti_tz - dti
|
|
|
|
with pytest.raises(TypeError, match=msg):
|
|
dti - dti_tz
|
|
|
|
# isub
|
|
dti -= dti
|
|
tm.assert_index_equal(dti, expected)
|
|
|
|
# different length raises ValueError
|
|
dti1 = date_range("20130101", periods=3)
|
|
dti2 = date_range("20130101", periods=4)
|
|
msg = "cannot add indices of unequal length"
|
|
with pytest.raises(ValueError, match=msg):
|
|
dti1 - dti2
|
|
|
|
# NaN propagation
|
|
dti1 = DatetimeIndex(["2012-01-01", np.nan, "2012-01-03"])
|
|
dti2 = DatetimeIndex(["2012-01-02", "2012-01-03", np.nan])
|
|
expected = TimedeltaIndex(["1 days", np.nan, np.nan])
|
|
result = dti2 - dti1
|
|
tm.assert_index_equal(result, expected)
|
|
|
|
# -------------------------------------------------------------------
|
|
# TODO: Most of this block is moved from series or frame tests, needs
|
|
# cleanup, box-parametrization, and de-duplication
|
|
|
|
@pytest.mark.parametrize("op", [operator.add, operator.sub])
|
|
def test_timedelta64_equal_timedelta_supported_ops(self, op, box_with_array):
|
|
ser = Series(
|
|
[
|
|
Timestamp("20130301"),
|
|
Timestamp("20130228 23:00:00"),
|
|
Timestamp("20130228 22:00:00"),
|
|
Timestamp("20130228 21:00:00"),
|
|
]
|
|
)
|
|
obj = box_with_array(ser)
|
|
|
|
intervals = ["D", "h", "m", "s", "us"]
|
|
|
|
def timedelta64(*args):
|
|
# see casting notes in NumPy gh-12927
|
|
return np.sum(list(starmap(np.timedelta64, zip(args, intervals))))
|
|
|
|
for d, h, m, s, us in product(*([range(2)] * 5)):
|
|
nptd = timedelta64(d, h, m, s, us)
|
|
pytd = timedelta(days=d, hours=h, minutes=m, seconds=s, microseconds=us)
|
|
lhs = op(obj, nptd)
|
|
rhs = op(obj, pytd)
|
|
|
|
tm.assert_equal(lhs, rhs)
|
|
|
|
def test_ops_nat_mixed_datetime64_timedelta64(self):
|
|
# GH#11349
|
|
timedelta_series = Series([NaT, Timedelta("1s")])
|
|
datetime_series = Series([NaT, Timestamp("19900315")])
|
|
nat_series_dtype_timedelta = Series([NaT, NaT], dtype="timedelta64[ns]")
|
|
nat_series_dtype_timestamp = Series([NaT, NaT], dtype="datetime64[ns]")
|
|
single_nat_dtype_datetime = Series([NaT], dtype="datetime64[ns]")
|
|
single_nat_dtype_timedelta = Series([NaT], dtype="timedelta64[ns]")
|
|
|
|
# subtraction
|
|
tm.assert_series_equal(
|
|
datetime_series - single_nat_dtype_datetime, nat_series_dtype_timedelta
|
|
)
|
|
|
|
tm.assert_series_equal(
|
|
datetime_series - single_nat_dtype_timedelta, nat_series_dtype_timestamp
|
|
)
|
|
tm.assert_series_equal(
|
|
-single_nat_dtype_timedelta + datetime_series, nat_series_dtype_timestamp
|
|
)
|
|
|
|
# without a Series wrapping the NaT, it is ambiguous
|
|
# whether it is a datetime64 or timedelta64
|
|
# defaults to interpreting it as timedelta64
|
|
tm.assert_series_equal(
|
|
nat_series_dtype_timestamp - single_nat_dtype_datetime,
|
|
nat_series_dtype_timedelta,
|
|
)
|
|
|
|
tm.assert_series_equal(
|
|
nat_series_dtype_timestamp - single_nat_dtype_timedelta,
|
|
nat_series_dtype_timestamp,
|
|
)
|
|
tm.assert_series_equal(
|
|
-single_nat_dtype_timedelta + nat_series_dtype_timestamp,
|
|
nat_series_dtype_timestamp,
|
|
)
|
|
msg = "cannot subtract a datelike"
|
|
with pytest.raises(TypeError, match=msg):
|
|
timedelta_series - single_nat_dtype_datetime
|
|
|
|
# addition
|
|
tm.assert_series_equal(
|
|
nat_series_dtype_timestamp + single_nat_dtype_timedelta,
|
|
nat_series_dtype_timestamp,
|
|
)
|
|
tm.assert_series_equal(
|
|
single_nat_dtype_timedelta + nat_series_dtype_timestamp,
|
|
nat_series_dtype_timestamp,
|
|
)
|
|
|
|
tm.assert_series_equal(
|
|
nat_series_dtype_timestamp + single_nat_dtype_timedelta,
|
|
nat_series_dtype_timestamp,
|
|
)
|
|
tm.assert_series_equal(
|
|
single_nat_dtype_timedelta + nat_series_dtype_timestamp,
|
|
nat_series_dtype_timestamp,
|
|
)
|
|
|
|
tm.assert_series_equal(
|
|
nat_series_dtype_timedelta + single_nat_dtype_datetime,
|
|
nat_series_dtype_timestamp,
|
|
)
|
|
tm.assert_series_equal(
|
|
single_nat_dtype_datetime + nat_series_dtype_timedelta,
|
|
nat_series_dtype_timestamp,
|
|
)
|
|
|
|
def test_ufunc_coercions(self):
|
|
idx = date_range("2011-01-01", periods=3, freq="2D", name="x")
|
|
|
|
delta = np.timedelta64(1, "D")
|
|
exp = date_range("2011-01-02", periods=3, freq="2D", name="x")
|
|
for result in [idx + delta, np.add(idx, delta)]:
|
|
assert isinstance(result, DatetimeIndex)
|
|
tm.assert_index_equal(result, exp)
|
|
assert result.freq == "2D"
|
|
|
|
exp = date_range("2010-12-31", periods=3, freq="2D", name="x")
|
|
|
|
for result in [idx - delta, np.subtract(idx, delta)]:
|
|
assert isinstance(result, DatetimeIndex)
|
|
tm.assert_index_equal(result, exp)
|
|
assert result.freq == "2D"
|
|
|
|
# When adding/subtracting an ndarray (which has no .freq), the result
|
|
# does not infer freq
|
|
idx = idx._with_freq(None)
|
|
delta = np.array(
|
|
[np.timedelta64(1, "D"), np.timedelta64(2, "D"), np.timedelta64(3, "D")]
|
|
)
|
|
exp = DatetimeIndex(["2011-01-02", "2011-01-05", "2011-01-08"], name="x")
|
|
|
|
for result in [idx + delta, np.add(idx, delta)]:
|
|
tm.assert_index_equal(result, exp)
|
|
assert result.freq == exp.freq
|
|
|
|
exp = DatetimeIndex(["2010-12-31", "2011-01-01", "2011-01-02"], name="x")
|
|
for result in [idx - delta, np.subtract(idx, delta)]:
|
|
assert isinstance(result, DatetimeIndex)
|
|
tm.assert_index_equal(result, exp)
|
|
assert result.freq == exp.freq
|
|
|
|
def test_dti_add_series(self, tz_naive_fixture, names):
|
|
# GH#13905
|
|
tz = tz_naive_fixture
|
|
index = DatetimeIndex(
|
|
["2016-06-28 05:30", "2016-06-28 05:31"], tz=tz, name=names[0]
|
|
)
|
|
ser = Series([Timedelta(seconds=5)] * 2, index=index, name=names[1])
|
|
expected = Series(index + Timedelta(seconds=5), index=index, name=names[2])
|
|
|
|
# passing name arg isn't enough when names[2] is None
|
|
expected.name = names[2]
|
|
assert expected.dtype == index.dtype
|
|
result = ser + index
|
|
tm.assert_series_equal(result, expected)
|
|
result2 = index + ser
|
|
tm.assert_series_equal(result2, expected)
|
|
|
|
expected = index + Timedelta(seconds=5)
|
|
result3 = ser.values + index
|
|
tm.assert_index_equal(result3, expected)
|
|
result4 = index + ser.values
|
|
tm.assert_index_equal(result4, expected)
|
|
|
|
@pytest.mark.parametrize("op", [operator.add, roperator.radd, operator.sub])
|
|
def test_dti_addsub_offset_arraylike(
|
|
self, tz_naive_fixture, names, op, index_or_series
|
|
):
|
|
# GH#18849, GH#19744
|
|
other_box = index_or_series
|
|
|
|
tz = tz_naive_fixture
|
|
dti = date_range("2017-01-01", periods=2, tz=tz, name=names[0])
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|
other = other_box([pd.offsets.MonthEnd(), pd.offsets.Day(n=2)], name=names[1])
|
|
|
|
xbox = get_upcast_box(dti, other)
|
|
|
|
with tm.assert_produces_warning(PerformanceWarning):
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|
res = op(dti, other)
|
|
|
|
expected = DatetimeIndex(
|
|
[op(dti[n], other[n]) for n in range(len(dti))], name=names[2], freq="infer"
|
|
)
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|
expected = tm.box_expected(expected, xbox).astype(object)
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|
tm.assert_equal(res, expected)
|
|
|
|
@pytest.mark.parametrize("other_box", [pd.Index, np.array])
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|
def test_dti_addsub_object_arraylike(
|
|
self, tz_naive_fixture, box_with_array, other_box
|
|
):
|
|
tz = tz_naive_fixture
|
|
|
|
dti = date_range("2017-01-01", periods=2, tz=tz)
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|
dtarr = tm.box_expected(dti, box_with_array)
|
|
other = other_box([pd.offsets.MonthEnd(), Timedelta(days=4)])
|
|
xbox = get_upcast_box(dtarr, other)
|
|
|
|
expected = DatetimeIndex(["2017-01-31", "2017-01-06"], tz=tz_naive_fixture)
|
|
expected = tm.box_expected(expected, xbox).astype(object)
|
|
|
|
with tm.assert_produces_warning(PerformanceWarning):
|
|
result = dtarr + other
|
|
tm.assert_equal(result, expected)
|
|
|
|
expected = DatetimeIndex(["2016-12-31", "2016-12-29"], tz=tz_naive_fixture)
|
|
expected = tm.box_expected(expected, xbox).astype(object)
|
|
|
|
with tm.assert_produces_warning(PerformanceWarning):
|
|
result = dtarr - other
|
|
tm.assert_equal(result, expected)
|
|
|
|
|
|
@pytest.mark.parametrize("years", [-1, 0, 1])
|
|
@pytest.mark.parametrize("months", [-2, 0, 2])
|
|
def test_shift_months(years, months):
|
|
dti = DatetimeIndex(
|
|
[
|
|
Timestamp("2000-01-05 00:15:00"),
|
|
Timestamp("2000-01-31 00:23:00"),
|
|
Timestamp("2000-01-01"),
|
|
Timestamp("2000-02-29"),
|
|
Timestamp("2000-12-31"),
|
|
]
|
|
)
|
|
actual = DatetimeIndex(shift_months(dti.asi8, years * 12 + months))
|
|
|
|
raw = [x + pd.offsets.DateOffset(years=years, months=months) for x in dti]
|
|
expected = DatetimeIndex(raw)
|
|
tm.assert_index_equal(actual, expected)
|
|
|
|
|
|
def test_dt64arr_addsub_object_dtype_2d():
|
|
# block-wise DataFrame operations will require operating on 2D
|
|
# DatetimeArray/TimedeltaArray, so check that specifically.
|
|
dti = date_range("1994-02-13", freq="2W", periods=4)
|
|
dta = dti._data.reshape((4, 1))
|
|
|
|
other = np.array([[pd.offsets.Day(n)] for n in range(4)])
|
|
assert other.shape == dta.shape
|
|
|
|
with tm.assert_produces_warning(PerformanceWarning):
|
|
result = dta + other
|
|
with tm.assert_produces_warning(PerformanceWarning):
|
|
expected = (dta[:, 0] + other[:, 0]).reshape(-1, 1)
|
|
|
|
tm.assert_numpy_array_equal(result, expected)
|
|
|
|
with tm.assert_produces_warning(PerformanceWarning):
|
|
# Case where we expect to get a TimedeltaArray back
|
|
result2 = dta - dta.astype(object)
|
|
|
|
assert result2.shape == (4, 1)
|
|
assert all(td._value == 0 for td in result2.ravel())
|
|
|
|
|
|
def test_non_nano_dt64_addsub_np_nat_scalars():
|
|
# GH 52295
|
|
ser = Series([1233242342344, 232432434324, 332434242344], dtype="datetime64[ms]")
|
|
result = ser - np.datetime64("nat", "ms")
|
|
expected = Series([NaT] * 3, dtype="timedelta64[ms]")
|
|
tm.assert_series_equal(result, expected)
|
|
|
|
result = ser + np.timedelta64("nat", "ms")
|
|
expected = Series([NaT] * 3, dtype="datetime64[ms]")
|
|
tm.assert_series_equal(result, expected)
|
|
|
|
|
|
def test_non_nano_dt64_addsub_np_nat_scalars_unitless():
|
|
# GH 52295
|
|
# TODO: Can we default to the ser unit?
|
|
ser = Series([1233242342344, 232432434324, 332434242344], dtype="datetime64[ms]")
|
|
result = ser - np.datetime64("nat")
|
|
expected = Series([NaT] * 3, dtype="timedelta64[ns]")
|
|
tm.assert_series_equal(result, expected)
|
|
|
|
result = ser + np.timedelta64("nat")
|
|
expected = Series([NaT] * 3, dtype="datetime64[ns]")
|
|
tm.assert_series_equal(result, expected)
|
|
|
|
|
|
def test_non_nano_dt64_addsub_np_nat_scalars_unsupported_unit():
|
|
# GH 52295
|
|
ser = Series([12332, 23243, 33243], dtype="datetime64[s]")
|
|
result = ser - np.datetime64("nat", "D")
|
|
expected = Series([NaT] * 3, dtype="timedelta64[s]")
|
|
tm.assert_series_equal(result, expected)
|
|
|
|
result = ser + np.timedelta64("nat", "D")
|
|
expected = Series([NaT] * 3, dtype="datetime64[s]")
|
|
tm.assert_series_equal(result, expected)
|