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| import itertools
|
| import numpy as np
| import pytest
|
| from pandas import (
| DataFrame,
| Series,
| notna,
| )
|
|
| def create_series():
| return [
| Series(dtype=np.float64, name="a"),
| Series([np.nan] * 5),
| Series([1.0] * 5),
| Series(range(5, 0, -1)),
| Series(range(5)),
| Series([np.nan, 1.0, np.nan, 1.0, 1.0]),
| Series([np.nan, 1.0, np.nan, 2.0, 3.0]),
| Series([np.nan, 1.0, np.nan, 3.0, 2.0]),
| ]
|
|
| def create_dataframes():
| return [
| DataFrame(columns=["a", "a"]),
| DataFrame(np.arange(15).reshape((5, 3)), columns=["a", "a", 99]),
| ] + [DataFrame(s) for s in create_series()]
|
|
| def is_constant(x):
| values = x.values.ravel("K")
| return len(set(values[notna(values)])) == 1
|
|
| @pytest.fixture(
| params=(
| obj
| for obj in itertools.chain(create_series(), create_dataframes())
| if is_constant(obj)
| ),
| )
| def consistent_data(request):
| return request.param
|
|
| @pytest.fixture(params=create_series())
| def series_data(request):
| return request.param
|
|
| @pytest.fixture(params=itertools.chain(create_series(), create_dataframes()))
| def all_data(request):
| """
| Test:
| - Empty Series / DataFrame
| - All NaN
| - All consistent value
| - Monotonically decreasing
| - Monotonically increasing
| - Monotonically consistent with NaNs
| - Monotonically increasing with NaNs
| - Monotonically decreasing with NaNs
| """
| return request.param
|
|
| @pytest.fixture(params=[0, 2])
| def min_periods(request):
| return request.param
|
|
