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Adjust test_binops for pandas 2.2 #15078

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merged 4 commits into from
Feb 20, 2024
Merged

Adjust test_binops for pandas 2.2 #15078

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097556c
Add xfail for test_operator_func_series_and_scalar_logical
mroeschke Feb 16, 2024
4ea1f93
Fix binops with datetime and dateoffset
mroeschke Feb 16, 2024
6384fd4
Merge remote-tracking branch 'upstream/branch-24.04' into p22/test_bi…
mroeschke Feb 19, 2024
d1090c4
xfail for pandas 2.1 bug
mroeschke Feb 19, 2024
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4 changes: 1 addition & 3 deletions python/cudf/cudf/core/column/datetime.py
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Original file line number Diff line number Diff line change
Expand Up @@ -567,9 +567,7 @@ def _binaryop(self, other: ColumnBinaryOperand, op: str) -> ColumnBase:
if other is NotImplemented:
return NotImplemented
if isinstance(other, cudf.DateOffset):
return other._datetime_binop(self, op, reflect=reflect).astype(
self.dtype
)
return other._datetime_binop(self, op, reflect=reflect)

# We check this on `other` before reflection since we already know the
# dtype of `self`.
Expand Down
96 changes: 71 additions & 25 deletions python/cudf/cudf/tests/test_binops.py
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Original file line number Diff line number Diff line change
Expand Up @@ -13,6 +13,7 @@

import cudf
from cudf import Series
from cudf.core._compat import PANDAS_GE_220
from cudf.core.buffer.spill_manager import get_global_manager
from cudf.core.index import as_index
from cudf.testing import _utils as utils
Expand Down Expand Up @@ -824,11 +825,21 @@ def test_operator_func_between_series_logical(
@pytest.mark.parametrize("fill_value", [None, 1.0])
@pytest.mark.parametrize("use_cudf_scalar", [False, True])
def test_operator_func_series_and_scalar_logical(
dtype, func, has_nulls, scalar, fill_value, use_cudf_scalar
request, dtype, func, has_nulls, scalar, fill_value, use_cudf_scalar
):
gdf_series = utils.gen_rand_series(
dtype, 1000, has_nulls=has_nulls, stride=10000
request.applymarker(
pytest.mark.xfail(
PANDAS_GE_220
and fill_value == 1.0
and scalar is np.nan
and (has_nulls or (not has_nulls and func not in {"eq", "ne"})),
reason="https://github.com/pandas-dev/pandas/issues/57447",
)
)
if has_nulls:
gdf_series = cudf.Series([-1.0, 0, cudf.NA, 1.1], dtype=dtype)
else:
gdf_series = cudf.Series([-1.0, 0, 10.5, 1.1], dtype=dtype)
pdf_series = gdf_series.to_pandas(nullable=True)
gdf_series_result = getattr(gdf_series, func)(
cudf.Scalar(scalar) if use_cudf_scalar else scalar,
Expand Down Expand Up @@ -1684,16 +1695,6 @@ def test_scalar_null_binops(op, dtype_l, dtype_r):
assert result.dtype == valid_result.dtype


@pytest.mark.parametrize(
"date_col",
[
[
"2000-01-01 00:00:00.012345678",
"2000-01-31 00:00:00.012345678",
"2000-02-29 00:00:00.012345678",
]
],
)
@pytest.mark.parametrize("n_periods", [0, 1, -1, 12, -12])
@pytest.mark.parametrize(
"frequency",
Expand All @@ -1714,8 +1715,40 @@ def test_scalar_null_binops(op, dtype_l, dtype_r):
)
@pytest.mark.parametrize("op", [operator.add, operator.sub])
def test_datetime_dateoffset_binaryop(
date_col, n_periods, frequency, dtype, op
request, n_periods, frequency, dtype, op
):
request.applymarker(
pytest.mark.xfail(
PANDAS_GE_220
and dtype in {"datetime64[ms]", "datetime64[s]"}
and frequency == "microseconds"
and n_periods == 0,
reason="https://github.com/pandas-dev/pandas/issues/57448",
)
)
request.applymarker(
pytest.mark.xfail(
not PANDAS_GE_220
and dtype in {"datetime64[ms]", "datetime64[s]"}
and frequency in ("microseconds", "nanoseconds")
and n_periods != 0,
reason="https://github.com/pandas-dev/pandas/pull/55595",
)
)
request.applymarker(
pytest.mark.xfail(
not PANDAS_GE_220
and dtype == "datetime64[us]"
and frequency == "nanoseconds"
and n_periods != 0,
reason="https://github.com/pandas-dev/pandas/pull/55595",
)
)
date_col = [
"2000-01-01 00:00:00.012345678",
"2000-01-31 00:00:00.012345678",
"2000-02-29 00:00:00.012345678",
]
gsr = cudf.Series(date_col, dtype=dtype)
psr = gsr.to_pandas()

Expand Down Expand Up @@ -1776,16 +1809,6 @@ def test_datetime_dateoffset_binaryop_multiple(date_col, kwargs, op):
utils.assert_eq(expect, got)


@pytest.mark.parametrize(
"date_col",
[
[
"2000-01-01 00:00:00.012345678",
"2000-01-31 00:00:00.012345678",
"2000-02-29 00:00:00.012345678",
]
],
)
@pytest.mark.parametrize("n_periods", [0, 1, -1, 12, -12])
@pytest.mark.parametrize(
"frequency",
Expand All @@ -1805,8 +1828,31 @@ def test_datetime_dateoffset_binaryop_multiple(date_col, kwargs, op):
["datetime64[ns]", "datetime64[us]", "datetime64[ms]", "datetime64[s]"],
)
def test_datetime_dateoffset_binaryop_reflected(
date_col, n_periods, frequency, dtype
request, n_periods, frequency, dtype
):
request.applymarker(
pytest.mark.xfail(
not PANDAS_GE_220
and dtype in {"datetime64[ms]", "datetime64[s]"}
and frequency in ("microseconds", "nanoseconds")
and n_periods != 0,
reason="https://github.com/pandas-dev/pandas/pull/55595",
)
)
request.applymarker(
pytest.mark.xfail(
not PANDAS_GE_220
and dtype == "datetime64[us]"
and frequency == "nanoseconds"
and n_periods != 0,
reason="https://github.com/pandas-dev/pandas/pull/55595",
)
)
date_col = [
"2000-01-01 00:00:00.012345678",
"2000-01-31 00:00:00.012345678",
"2000-02-29 00:00:00.012345678",
]
gsr = cudf.Series(date_col, dtype=dtype)
psr = gsr.to_pandas() # converts to nanos

Expand Down
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