fr/fr_env/lib/python3.8/site-packages/pandas/tests/groupby/conftest.py

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2021-03-02 18:34:59 +05:30
import numpy as np
import pytest
from pandas import DataFrame, MultiIndex
import pandas._testing as tm
from pandas.core.groupby.base import reduction_kernels, transformation_kernels
@pytest.fixture
def mframe():
index = MultiIndex(
levels=[["foo", "bar", "baz", "qux"], ["one", "two", "three"]],
codes=[[0, 0, 0, 1, 1, 2, 2, 3, 3, 3], [0, 1, 2, 0, 1, 1, 2, 0, 1, 2]],
names=["first", "second"],
)
return DataFrame(np.random.randn(10, 3), index=index, columns=["A", "B", "C"])
@pytest.fixture
def df():
return DataFrame(
{
"A": ["foo", "bar", "foo", "bar", "foo", "bar", "foo", "foo"],
"B": ["one", "one", "two", "three", "two", "two", "one", "three"],
"C": np.random.randn(8),
"D": np.random.randn(8),
}
)
@pytest.fixture
def ts():
return tm.makeTimeSeries()
@pytest.fixture
def tsd():
return tm.getTimeSeriesData()
@pytest.fixture
def tsframe(tsd):
return DataFrame(tsd)
@pytest.fixture
def df_mixed_floats():
return DataFrame(
{
"A": ["foo", "bar", "foo", "bar", "foo", "bar", "foo", "foo"],
"B": ["one", "one", "two", "three", "two", "two", "one", "three"],
"C": np.random.randn(8),
"D": np.array(np.random.randn(8), dtype="float32"),
}
)
@pytest.fixture
def three_group():
return DataFrame(
{
"A": [
"foo",
"foo",
"foo",
"foo",
"bar",
"bar",
"bar",
"bar",
"foo",
"foo",
"foo",
],
"B": [
"one",
"one",
"one",
"two",
"one",
"one",
"one",
"two",
"two",
"two",
"one",
],
"C": [
"dull",
"dull",
"shiny",
"dull",
"dull",
"shiny",
"shiny",
"dull",
"shiny",
"shiny",
"shiny",
],
"D": np.random.randn(11),
"E": np.random.randn(11),
"F": np.random.randn(11),
}
)
@pytest.fixture(params=sorted(reduction_kernels))
def reduction_func(request):
"""
yields the string names of all groupby reduction functions, one at a time.
"""
return request.param
@pytest.fixture(params=sorted(transformation_kernels))
def transformation_func(request):
"""yields the string names of all groupby transformation functions."""
return request.param
@pytest.fixture(params=sorted(reduction_kernels) + sorted(transformation_kernels))
def groupby_func(request):
"""yields both aggregation and transformation functions."""
return request.param
@pytest.fixture(params=[True, False])
def parallel(request):
"""parallel keyword argument for numba.jit"""
return request.param
@pytest.fixture(params=[True, False])
def nogil(request):
"""nogil keyword argument for numba.jit"""
return request.param
@pytest.fixture(params=[True, False])
def nopython(request):
"""nopython keyword argument for numba.jit"""
return request.param