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143 lines
3.3 KiB
Python
143 lines
3.3 KiB
Python
import numpy as np
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import pytest
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from pandas import DataFrame, MultiIndex
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import pandas._testing as tm
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from pandas.core.groupby.base import reduction_kernels, transformation_kernels
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@pytest.fixture
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def mframe():
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index = MultiIndex(
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levels=[["foo", "bar", "baz", "qux"], ["one", "two", "three"]],
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codes=[[0, 0, 0, 1, 1, 2, 2, 3, 3, 3], [0, 1, 2, 0, 1, 1, 2, 0, 1, 2]],
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names=["first", "second"],
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)
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return DataFrame(np.random.randn(10, 3), index=index, columns=["A", "B", "C"])
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@pytest.fixture
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def df():
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return DataFrame(
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{
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"A": ["foo", "bar", "foo", "bar", "foo", "bar", "foo", "foo"],
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"B": ["one", "one", "two", "three", "two", "two", "one", "three"],
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"C": np.random.randn(8),
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"D": np.random.randn(8),
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}
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)
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@pytest.fixture
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def ts():
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return tm.makeTimeSeries()
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@pytest.fixture
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def tsd():
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return tm.getTimeSeriesData()
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@pytest.fixture
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def tsframe(tsd):
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return DataFrame(tsd)
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@pytest.fixture
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def df_mixed_floats():
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return DataFrame(
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{
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"A": ["foo", "bar", "foo", "bar", "foo", "bar", "foo", "foo"],
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"B": ["one", "one", "two", "three", "two", "two", "one", "three"],
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"C": np.random.randn(8),
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"D": np.array(np.random.randn(8), dtype="float32"),
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}
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)
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@pytest.fixture
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def three_group():
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return DataFrame(
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{
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"A": [
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"foo",
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"foo",
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"foo",
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"foo",
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"bar",
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"bar",
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"bar",
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"bar",
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"foo",
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"foo",
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"foo",
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],
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"B": [
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"one",
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"one",
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"one",
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"two",
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"one",
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"one",
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"one",
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"two",
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"two",
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"two",
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"one",
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],
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"C": [
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"dull",
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"dull",
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"shiny",
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"dull",
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"dull",
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"shiny",
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"shiny",
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"dull",
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"shiny",
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"shiny",
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"shiny",
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],
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"D": np.random.randn(11),
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"E": np.random.randn(11),
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"F": np.random.randn(11),
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}
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)
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@pytest.fixture(params=sorted(reduction_kernels))
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def reduction_func(request):
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"""
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yields the string names of all groupby reduction functions, one at a time.
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"""
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return request.param
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@pytest.fixture(params=sorted(transformation_kernels))
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def transformation_func(request):
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"""yields the string names of all groupby transformation functions."""
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return request.param
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@pytest.fixture(params=sorted(reduction_kernels) + sorted(transformation_kernels))
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def groupby_func(request):
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"""yields both aggregation and transformation functions."""
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return request.param
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@pytest.fixture(params=[True, False])
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def parallel(request):
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"""parallel keyword argument for numba.jit"""
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return request.param
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@pytest.fixture(params=[True, False])
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def nogil(request):
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"""nogil keyword argument for numba.jit"""
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return request.param
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@pytest.fixture(params=[True, False])
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def nopython(request):
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"""nopython keyword argument for numba.jit"""
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return request.param
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