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| import numpy as np
| import pytest
|
| from pandas.errors import DataError
|
| from pandas.core.dtypes.common import pandas_dtype
|
| from pandas import (
| NA,
| DataFrame,
| Series,
| )
| import pandas._testing as tm
|
| # gh-12373 : rolling functions error on float32 data
| # make sure rolling functions works for different dtypes
| #
| # further note that we are only checking rolling for fully dtype
| # compliance (though both expanding and ewm inherit)
|
|
| def get_dtype(dtype, coerce_int=None):
| if coerce_int is False and "int" in dtype:
| return None
| return pandas_dtype(dtype)
|
|
| @pytest.fixture(
| params=[
| "object",
| "category",
| "int8",
| "int16",
| "int32",
| "int64",
| "uint8",
| "uint16",
| "uint32",
| "uint64",
| "float16",
| "float32",
| "float64",
| "m8[ns]",
| "M8[ns]",
| "datetime64[ns, UTC]",
| ]
| )
| def dtypes(request):
| """Dtypes for window tests"""
| return request.param
|
|
| @pytest.mark.parametrize(
| "method, data, expected_data, coerce_int, min_periods",
| [
| ("count", np.arange(5), [1, 2, 2, 2, 2], True, 0),
| ("count", np.arange(10, 0, -2), [1, 2, 2, 2, 2], True, 0),
| ("count", [0, 1, 2, np.nan, 4], [1, 2, 2, 1, 1], False, 0),
| ("max", np.arange(5), [np.nan, 1, 2, 3, 4], True, None),
| ("max", np.arange(10, 0, -2), [np.nan, 10, 8, 6, 4], True, None),
| ("max", [0, 1, 2, np.nan, 4], [np.nan, 1, 2, np.nan, np.nan], False, None),
| ("min", np.arange(5), [np.nan, 0, 1, 2, 3], True, None),
| ("min", np.arange(10, 0, -2), [np.nan, 8, 6, 4, 2], True, None),
| ("min", [0, 1, 2, np.nan, 4], [np.nan, 0, 1, np.nan, np.nan], False, None),
| ("sum", np.arange(5), [np.nan, 1, 3, 5, 7], True, None),
| ("sum", np.arange(10, 0, -2), [np.nan, 18, 14, 10, 6], True, None),
| ("sum", [0, 1, 2, np.nan, 4], [np.nan, 1, 3, np.nan, np.nan], False, None),
| ("mean", np.arange(5), [np.nan, 0.5, 1.5, 2.5, 3.5], True, None),
| ("mean", np.arange(10, 0, -2), [np.nan, 9, 7, 5, 3], True, None),
| ("mean", [0, 1, 2, np.nan, 4], [np.nan, 0.5, 1.5, np.nan, np.nan], False, None),
| ("std", np.arange(5), [np.nan] + [np.sqrt(0.5)] * 4, True, None),
| ("std", np.arange(10, 0, -2), [np.nan] + [np.sqrt(2)] * 4, True, None),
| (
| "std",
| [0, 1, 2, np.nan, 4],
| [np.nan] + [np.sqrt(0.5)] * 2 + [np.nan] * 2,
| False,
| None,
| ),
| ("var", np.arange(5), [np.nan, 0.5, 0.5, 0.5, 0.5], True, None),
| ("var", np.arange(10, 0, -2), [np.nan, 2, 2, 2, 2], True, None),
| ("var", [0, 1, 2, np.nan, 4], [np.nan, 0.5, 0.5, np.nan, np.nan], False, None),
| ("median", np.arange(5), [np.nan, 0.5, 1.5, 2.5, 3.5], True, None),
| ("median", np.arange(10, 0, -2), [np.nan, 9, 7, 5, 3], True, None),
| (
| "median",
| [0, 1, 2, np.nan, 4],
| [np.nan, 0.5, 1.5, np.nan, np.nan],
| False,
| None,
| ),
| ],
| )
| def test_series_dtypes(
| method, data, expected_data, coerce_int, dtypes, min_periods, step
| ):
| ser = Series(data, dtype=get_dtype(dtypes, coerce_int=coerce_int))
| rolled = ser.rolling(2, min_periods=min_periods, step=step)
|
| if dtypes in ("m8[ns]", "M8[ns]", "datetime64[ns, UTC]") and method != "count":
| msg = "No numeric types to aggregate"
| with pytest.raises(DataError, match=msg):
| getattr(rolled, method)()
| else:
| result = getattr(rolled, method)()
| expected = Series(expected_data, dtype="float64")[::step]
| tm.assert_almost_equal(result, expected)
|
|
| def test_series_nullable_int(any_signed_int_ea_dtype, step):
| # GH 43016
| ser = Series([0, 1, NA], dtype=any_signed_int_ea_dtype)
| result = ser.rolling(2, step=step).mean()
| expected = Series([np.nan, 0.5, np.nan])[::step]
| tm.assert_series_equal(result, expected)
|
|
| @pytest.mark.parametrize(
| "method, expected_data, min_periods",
| [
| ("count", {0: Series([1, 2, 2, 2, 2]), 1: Series([1, 2, 2, 2, 2])}, 0),
| (
| "max",
| {0: Series([np.nan, 2, 4, 6, 8]), 1: Series([np.nan, 3, 5, 7, 9])},
| None,
| ),
| (
| "min",
| {0: Series([np.nan, 0, 2, 4, 6]), 1: Series([np.nan, 1, 3, 5, 7])},
| None,
| ),
| (
| "sum",
| {0: Series([np.nan, 2, 6, 10, 14]), 1: Series([np.nan, 4, 8, 12, 16])},
| None,
| ),
| (
| "mean",
| {0: Series([np.nan, 1, 3, 5, 7]), 1: Series([np.nan, 2, 4, 6, 8])},
| None,
| ),
| (
| "std",
| {
| 0: Series([np.nan] + [np.sqrt(2)] * 4),
| 1: Series([np.nan] + [np.sqrt(2)] * 4),
| },
| None,
| ),
| (
| "var",
| {0: Series([np.nan, 2, 2, 2, 2]), 1: Series([np.nan, 2, 2, 2, 2])},
| None,
| ),
| (
| "median",
| {0: Series([np.nan, 1, 3, 5, 7]), 1: Series([np.nan, 2, 4, 6, 8])},
| None,
| ),
| ],
| )
| def test_dataframe_dtypes(method, expected_data, dtypes, min_periods, step):
| df = DataFrame(np.arange(10).reshape((5, 2)), dtype=get_dtype(dtypes))
| rolled = df.rolling(2, min_periods=min_periods, step=step)
|
| if dtypes in ("m8[ns]", "M8[ns]", "datetime64[ns, UTC]") and method != "count":
| msg = "Cannot aggregate non-numeric type"
| with pytest.raises(DataError, match=msg):
| getattr(rolled, method)()
| else:
| result = getattr(rolled, method)()
| expected = DataFrame(expected_data, dtype="float64")[::step]
| tm.assert_frame_equal(result, expected)
|
|
