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CLN: remove no-longer-needed warning filters (#58025)
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jbrockmendel committed Mar 27, 2024
1 parent 1f4c56b commit 2e80a5b
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Showing 12 changed files with 6 additions and 53 deletions.
8 changes: 1 addition & 7 deletions pandas/core/generic.py
Expand Up @@ -9660,13 +9660,7 @@ def _where(

# make sure we are boolean
fill_value = bool(inplace)
with warnings.catch_warnings():
warnings.filterwarnings(
"ignore",
"Downcasting object dtype arrays",
category=FutureWarning,
)
cond = cond.fillna(fill_value)
cond = cond.fillna(fill_value)
cond = cond.infer_objects()

msg = "Boolean array expected for the condition, not {dtype}"
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9 changes: 1 addition & 8 deletions pandas/io/formats/xml.py
Expand Up @@ -11,7 +11,6 @@
Any,
final,
)
import warnings

from pandas.errors import AbstractMethodError
from pandas.util._decorators import (
Expand Down Expand Up @@ -208,13 +207,7 @@ def _process_dataframe(self) -> dict[int | str, dict[str, Any]]:
df = df.reset_index()

if self.na_rep is not None:
with warnings.catch_warnings():
warnings.filterwarnings(
"ignore",
"Downcasting object dtype arrays",
category=FutureWarning,
)
df = df.fillna(self.na_rep)
df = df.fillna(self.na_rep)

return df.to_dict(orient="index")

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9 changes: 1 addition & 8 deletions pandas/io/json/_json.py
Expand Up @@ -16,7 +16,6 @@
final,
overload,
)
import warnings

import numpy as np

Expand Down Expand Up @@ -1173,13 +1172,7 @@ def _try_convert_data(
if all(notna(data)):
return data, False

with warnings.catch_warnings():
warnings.filterwarnings(
"ignore",
"Downcasting object dtype arrays",
category=FutureWarning,
)
filled = data.fillna(np.nan)
filled = data.fillna(np.nan)

return filled, True

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8 changes: 1 addition & 7 deletions pandas/io/stata.py
Expand Up @@ -2887,13 +2887,7 @@ def _prepare_data(self) -> np.rec.recarray:
for i, col in enumerate(data):
typ = typlist[i]
if typ <= self._max_string_length:
with warnings.catch_warnings():
warnings.filterwarnings(
"ignore",
"Downcasting object dtype arrays",
category=FutureWarning,
)
dc = data[col].fillna("")
dc = data[col].fillna("")
data[col] = dc.apply(_pad_bytes, args=(typ,))
stype = f"S{typ}"
dtypes[col] = stype
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8 changes: 1 addition & 7 deletions pandas/plotting/_matplotlib/core.py
Expand Up @@ -1725,13 +1725,7 @@ def _kind(self) -> Literal["area"]:

def __init__(self, data, **kwargs) -> None:
kwargs.setdefault("stacked", True)
with warnings.catch_warnings():
warnings.filterwarnings(
"ignore",
"Downcasting object dtype arrays",
category=FutureWarning,
)
data = data.fillna(value=0)
data = data.fillna(value=0)
LinePlot.__init__(self, data, **kwargs)

if not self.stacked:
Expand Down
10 changes: 1 addition & 9 deletions pandas/tests/extension/test_masked.py
Expand Up @@ -14,8 +14,6 @@
"""

import warnings

import numpy as np
import pytest

Expand Down Expand Up @@ -215,13 +213,7 @@ def _cast_pointwise_result(self, op_name: str, obj, other, pointwise_result):

if sdtype.kind in "iu":
if op_name in ("__rtruediv__", "__truediv__", "__div__"):
with warnings.catch_warnings():
warnings.filterwarnings(
"ignore",
"Downcasting object dtype arrays",
category=FutureWarning,
)
filled = expected.fillna(np.nan)
filled = expected.fillna(np.nan)
expected = filled.astype("Float64")
else:
# combine method result in 'biggest' (int64) dtype
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2 changes: 0 additions & 2 deletions pandas/tests/frame/indexing/test_where.py
Expand Up @@ -96,7 +96,6 @@ def test_where_upcasting(self):

tm.assert_series_equal(result, expected)

@pytest.mark.filterwarnings("ignore:Downcasting object dtype arrays:FutureWarning")
def test_where_alignment(self, where_frame, float_string_frame):
# aligning
def _check_align(df, cond, other, check_dtypes=True):
Expand Down Expand Up @@ -171,7 +170,6 @@ def test_where_invalid(self):
with pytest.raises(ValueError, match=msg):
df.mask(0)

@pytest.mark.filterwarnings("ignore:Downcasting object dtype arrays:FutureWarning")
def test_where_set(self, where_frame, float_string_frame, mixed_int_frame):
# where inplace

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1 change: 0 additions & 1 deletion pandas/tests/frame/test_reductions.py
Expand Up @@ -1272,7 +1272,6 @@ def test_any_all_bool_with_na(
):
getattr(bool_frame_with_na, all_boolean_reductions)(axis=axis, bool_only=False)

@pytest.mark.filterwarnings("ignore:Downcasting object dtype arrays:FutureWarning")
def test_any_all_bool_frame(self, all_boolean_reductions, bool_frame_with_na):
# GH#12863: numpy gives back non-boolean data for object type
# so fill NaNs to compare with pandas behavior
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1 change: 0 additions & 1 deletion pandas/tests/frame/test_stack_unstack.py
Expand Up @@ -1223,7 +1223,6 @@ def test_stack_preserve_categorical_dtype_values(self, future_stack):
@pytest.mark.filterwarnings(
"ignore:The previous implementation of stack is deprecated"
)
@pytest.mark.filterwarnings("ignore:Downcasting object dtype arrays:FutureWarning")
@pytest.mark.parametrize(
"index",
[
Expand Down
1 change: 0 additions & 1 deletion pandas/tests/groupby/test_numeric_only.py
Expand Up @@ -310,7 +310,6 @@ def test_numeric_only(kernel, has_arg, numeric_only, keys):
method(*args, **kwargs)


@pytest.mark.filterwarnings("ignore:Downcasting object dtype arrays:FutureWarning")
@pytest.mark.parametrize("dtype", [bool, int, float, object])
def test_deprecate_numeric_only_series(dtype, groupby_func, request):
# GH#46560
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1 change: 0 additions & 1 deletion pandas/tests/series/test_api.py
Expand Up @@ -195,7 +195,6 @@ def test_series_datetimelike_attribute_access_invalid(self):
with pytest.raises(AttributeError, match=msg):
ser.weekday

@pytest.mark.filterwarnings("ignore:Downcasting object dtype arrays:FutureWarning")
@pytest.mark.parametrize(
"kernel, has_numeric_only",
[
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1 change: 0 additions & 1 deletion pandas/tests/series/test_logical_ops.py
Expand Up @@ -15,7 +15,6 @@


class TestSeriesLogicalOps:
@pytest.mark.filterwarnings("ignore:Downcasting object dtype arrays:FutureWarning")
@pytest.mark.parametrize("bool_op", [operator.and_, operator.or_, operator.xor])
def test_bool_operators_with_nas(self, bool_op):
# boolean &, |, ^ should work with object arrays and propagate NAs
Expand Down

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