import numpy as np
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import pytest
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import pandas as pd
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from pandas import (
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Index,
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RangeIndex,
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)
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import pandas._testing as tm
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from pandas.core.computation import expressions as expr
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@pytest.fixture(autouse=True, params=[0, 1000000], ids=["numexpr", "python"])
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def switch_numexpr_min_elements(request):
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_MIN_ELEMENTS = expr._MIN_ELEMENTS
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expr._MIN_ELEMENTS = request.param
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yield request.param
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expr._MIN_ELEMENTS = _MIN_ELEMENTS
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# ------------------------------------------------------------------
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# doctest with +SKIP for one fixture fails during setup with
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# 'DoctestItem' object has no attribute 'callspec'
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# due to switch_numexpr_min_elements fixture
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@pytest.fixture(params=[1, np.array(1, dtype=np.int64)])
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def one(request):
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"""
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Several variants of integer value 1. The zero-dim integer array
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behaves like an integer.
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This fixture can be used to check that datetimelike indexes handle
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addition and subtraction of integers and zero-dimensional arrays
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of integers.
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Examples
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--------
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dti = pd.date_range('2016-01-01', periods=2, freq='H')
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dti
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DatetimeIndex(['2016-01-01 00:00:00', '2016-01-01 01:00:00'],
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dtype='datetime64[ns]', freq='H')
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dti + one
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DatetimeIndex(['2016-01-01 01:00:00', '2016-01-01 02:00:00'],
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dtype='datetime64[ns]', freq='H')
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"""
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return request.param
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zeros = [
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box_cls([0] * 5, dtype=dtype)
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for box_cls in [Index, np.array, pd.array]
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for dtype in [np.int64, np.uint64, np.float64]
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]
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zeros.extend([box_cls([-0.0] * 5, dtype=np.float64) for box_cls in [Index, np.array]])
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zeros.extend([np.array(0, dtype=dtype) for dtype in [np.int64, np.uint64, np.float64]])
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zeros.extend([np.array(-0.0, dtype=np.float64)])
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zeros.extend([0, 0.0, -0.0])
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# doctest with +SKIP for zero fixture fails during setup with
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# 'DoctestItem' object has no attribute 'callspec'
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# due to switch_numexpr_min_elements fixture
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@pytest.fixture(params=zeros)
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def zero(request):
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"""
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Several types of scalar zeros and length 5 vectors of zeros.
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This fixture can be used to check that numeric-dtype indexes handle
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division by any zero numeric-dtype.
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Uses vector of length 5 for broadcasting with `numeric_idx` fixture,
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which creates numeric-dtype vectors also of length 5.
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Examples
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--------
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arr = RangeIndex(5)
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arr / zeros
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Index([nan, inf, inf, inf, inf], dtype='float64')
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"""
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return request.param
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# ------------------------------------------------------------------
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# Vector Fixtures
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@pytest.fixture(
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params=[
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# TODO: add more dtypes here
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Index(np.arange(5, dtype="float64")),
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Index(np.arange(5, dtype="int64")),
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Index(np.arange(5, dtype="uint64")),
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RangeIndex(5),
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],
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ids=lambda x: type(x).__name__,
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)
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def numeric_idx(request):
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"""
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Several types of numeric-dtypes Index objects
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"""
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return request.param
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# ------------------------------------------------------------------
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# Scalar Fixtures
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@pytest.fixture(
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params=[
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pd.Timedelta("10m7s").to_pytimedelta(),
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pd.Timedelta("10m7s"),
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pd.Timedelta("10m7s").to_timedelta64(),
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],
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ids=lambda x: type(x).__name__,
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)
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def scalar_td(request):
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"""
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Several variants of Timedelta scalars representing 10 minutes and 7 seconds.
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"""
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return request.param
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@pytest.fixture(
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params=[
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pd.offsets.Day(3),
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pd.offsets.Hour(72),
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pd.Timedelta(days=3).to_pytimedelta(),
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pd.Timedelta("72:00:00"),
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np.timedelta64(3, "D"),
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np.timedelta64(72, "h"),
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],
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ids=lambda x: type(x).__name__,
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)
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def three_days(request):
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"""
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Several timedelta-like and DateOffset objects that each represent
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a 3-day timedelta
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"""
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return request.param
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@pytest.fixture(
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params=[
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pd.offsets.Hour(2),
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pd.offsets.Minute(120),
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pd.Timedelta(hours=2).to_pytimedelta(),
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pd.Timedelta(seconds=2 * 3600),
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np.timedelta64(2, "h"),
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np.timedelta64(120, "m"),
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],
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ids=lambda x: type(x).__name__,
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)
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def two_hours(request):
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"""
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Several timedelta-like and DateOffset objects that each represent
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a 2-hour timedelta
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"""
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return request.param
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_common_mismatch = [
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pd.offsets.YearBegin(2),
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pd.offsets.MonthBegin(1),
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pd.offsets.Minute(),
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]
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@pytest.fixture(
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params=[
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pd.Timedelta(minutes=30).to_pytimedelta(),
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np.timedelta64(30, "s"),
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pd.Timedelta(seconds=30),
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]
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+ _common_mismatch
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)
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def not_hourly(request):
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"""
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Several timedelta-like and DateOffset instances that are _not_
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compatible with Hourly frequencies.
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"""
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return request.param
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@pytest.fixture(
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params=[
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np.timedelta64(4, "h"),
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pd.Timedelta(hours=23).to_pytimedelta(),
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pd.Timedelta("23:00:00"),
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]
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+ _common_mismatch
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)
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def not_daily(request):
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"""
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Several timedelta-like and DateOffset instances that are _not_
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compatible with Daily frequencies.
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"""
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return request.param
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@pytest.fixture(
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params=[
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np.timedelta64(365, "D"),
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pd.Timedelta(days=365).to_pytimedelta(),
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pd.Timedelta(days=365),
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]
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+ _common_mismatch
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)
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def mismatched_freq(request):
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"""
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Several timedelta-like and DateOffset instances that are _not_
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compatible with Monthly or Annual frequencies.
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"""
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return request.param
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# ------------------------------------------------------------------
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@pytest.fixture(
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params=[Index, pd.Series, tm.to_array, np.array, list], ids=lambda x: x.__name__
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)
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def box_1d_array(request):
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"""
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Fixture to test behavior for Index, Series, tm.to_array, numpy Array and list
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classes
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"""
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return request.param
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