CLN: assorted

asv_bench/benchmarks/tslibs/tslib.py

@@ -51,7 +51,7 @@ class TimeIntsToPydatetime:
         _tzs,
     )
     param_names = ["box", "size", "tz"]
-    # TODO: fold? freq?
+    # TODO: fold?
 
     def setup(self, box, size, tz):
         if box == "date" and tz is not None:

pandas/core/arrays/_mixins.py

@@ -234,21 +234,9 @@ def searchsorted(
         side: Literal["left", "right"] = "left",
         sorter: NumpySorter = None,
     ) -> npt.NDArray[np.intp] | np.intp:
-        # TODO(2.0): use _validate_setitem_value once dt64tz mismatched-timezone
-        #  deprecation is enforced
-        npvalue = self._validate_searchsorted_value(value)
+        npvalue = self._validate_setitem_value(value)
         return self._ndarray.searchsorted(npvalue, side=side, sorter=sorter)
 
-    def _validate_searchsorted_value(
-        self, value: NumpyValueArrayLike | ExtensionArray
-    ) -> NumpyValueArrayLike:
-        # TODO(2.0): after deprecation in datetimelikearraymixin is enforced,
-        #  we can remove this and use _validate_setitem_value directly
-        if isinstance(value, ExtensionArray):
-            return value.to_numpy()
-        else:
-            return value
-
     @doc(ExtensionArray.shift)
     def shift(self, periods: int = 1, fill_value=None, axis: AxisInt = 0):
 

pandas/core/arrays/categorical.py

@@ -1301,8 +1301,6 @@ def _validate_setitem_value(self, value):
         else:
             return self._validate_scalar(value)
 
-    _validate_searchsorted_value = _validate_setitem_value
-
     def _validate_scalar(self, fill_value):
         """
         Convert a user-facing fill_value to a representation to use with our

pandas/core/arrays/datetimelike.py

@@ -600,7 +600,6 @@ def _validate_scalar(
         value,
         *,
         allow_listlike: bool = False,
-        setitem: bool = True,
         unbox: bool = True,
     ):
         """
@@ -612,8 +611,6 @@ def _validate_scalar(
         allow_listlike: bool, default False
             When raising an exception, whether the message should say
             listlike inputs are allowed.
-        setitem : bool, default True
-            Whether to check compatibility with setitem strictness.
         unbox : bool, default True
             Whether to unbox the result before returning.  Note: unbox=False
             skips the setitem compatibility check.
@@ -735,14 +732,6 @@ def _validate_listlike(self, value, allow_object: bool = False):
 
         return value
 
-    def _validate_searchsorted_value(self, value):
-        if not is_list_like(value):
-            return self._validate_scalar(value, allow_listlike=True, setitem=False)
-        else:
-            value = self._validate_listlike(value)
-
-        return self._unbox(value)
-
     def _validate_setitem_value(self, value):
         if is_list_like(value):
             value = self._validate_listlike(value)
@@ -1363,10 +1352,7 @@ def _addsub_object_array(self, other: np.ndarray, op):
         # Caller is responsible for broadcasting if necessary
         assert self.shape == other.shape, (self.shape, other.shape)
 
-        with warnings.catch_warnings():
-            # filter out warnings about Timestamp.freq
-            warnings.filterwarnings("ignore", category=FutureWarning)
-            res_values = op(self.astype("O"), np.asarray(other))
+        res_values = op(self.astype("O"), np.asarray(other))
 
         result = pd_array(res_values.ravel())
         result = extract_array(result, extract_numpy=True).reshape(self.shape)

pandas/core/arrays/datetimes.py

@@ -751,7 +751,6 @@ def _add_offset(self, offset) -> DatetimeArray:
         else:
             result = DatetimeArray._simple_new(result, dtype=result.dtype)
             if self.tz is not None:
-                # FIXME: tz_localize with non-nano
                 result = result.tz_localize(self.tz)
 
         return result

pandas/core/arrays/period.py

@@ -692,7 +692,7 @@ def searchsorted(
         side: Literal["left", "right"] = "left",
         sorter: NumpySorter = None,
     ) -> npt.NDArray[np.intp] | np.intp:
-        npvalue = self._validate_searchsorted_value(value).view("M8[ns]")
+        npvalue = self._validate_setitem_value(value).view("M8[ns]")
 
         # Cast to M8 to get datetime-like NaT placement
         m8arr = self._ndarray.view("M8[ns]")

pandas/core/dtypes/cast.py

@@ -1029,15 +1029,12 @@ def soft_convert_objects(
     if datetime or timedelta:
         # GH 20380, when datetime is beyond year 2262, hence outside
         # bound of nanosecond-resolution 64-bit integers.
-        try:
-            converted = lib.maybe_convert_objects(
-                values,
-                convert_datetime=datetime,
-                convert_timedelta=timedelta,
-                convert_period=period,
-            )
-        except (OutOfBoundsDatetime, ValueError):
-            return values
+        converted = lib.maybe_convert_objects(
+            values,
+            convert_datetime=datetime,
+            convert_timedelta=timedelta,
+            convert_period=period,
+        )
         if converted is not values:
             return converted
 

pandas/core/indexes/base.py

@@ -3500,13 +3500,7 @@ def _assert_can_do_setop(self, other) -> bool:
 
     def _convert_can_do_setop(self, other) -> tuple[Index, Hashable]:
         if not isinstance(other, Index):
-            # TODO(2.0): no need to special-case here once _with_infer
-            #  deprecation is enforced
-            if hasattr(other, "dtype"):
-                other = Index(other, name=self.name, dtype=other.dtype)
-            else:
-                # e.g. list
-                other = Index(other, name=self.name)
+            other = Index(other, name=self.name)
             result_name = self.name
         else:
             result_name = get_op_result_name(self, other)

pandas/core/internals/blocks.py

@@ -1920,15 +1920,11 @@ def _catch_deprecated_value_error(err: Exception) -> None:
     which will no longer be raised in version.2.0.
     """
     if isinstance(err, ValueError):
-        # TODO(2.0): once DTA._validate_setitem_value deprecation
-        #  is enforced, stop catching ValueError here altogether
         if isinstance(err, IncompatibleFrequency):
             pass
         elif "'value.closed' is" in str(err):
             # IntervalDtype mismatched 'closed'
             pass
-        elif "Timezones don't match" not in str(err):
-            raise err
 
 
 class DatetimeLikeBlock(NDArrayBackedExtensionBlock):

pandas/plotting/_matplotlib/core.py

@@ -1180,11 +1180,7 @@ def _plot_colorbar(self, ax: Axes, **kwds):
         # use the last one which contains the latest information
         # about the ax
         img = ax.collections[-1]
-        with warnings.catch_warnings():
-            # https://github.com/matplotlib/matplotlib/issues/23614
-            # False positive deprecation warning until matplotlib=3.6
-            warnings.filterwarnings("ignore", "Auto-removal of grids")
-            return self.fig.colorbar(img, ax=ax, **kwds)
+        return self.fig.colorbar(img, ax=ax, **kwds)
 
 
 class ScatterPlot(PlanePlot):

pandas/tests/apply/test_frame_transform.py

@@ -130,6 +130,10 @@ def func(x):
 frame_kernels_raise = [x for x in frame_transform_kernels if x not in wont_fail]
 
 
+@pytest.mark.filterwarnings(
+    "ignore:Calling Series.rank with numeric_only:FutureWarning"
+)
+@pytest.mark.filterwarnings("ignore:Dropping of nuisance:FutureWarning")
 @pytest.mark.parametrize("op", [*frame_kernels_raise, lambda x: x + 1])
 def test_transform_bad_dtype(op, frame_or_series, request):
     # GH 35964
@@ -162,6 +166,12 @@ def test_transform_bad_dtype(op, frame_or_series, request):
         obj.transform({"A": [op]})
 
 
+@pytest.mark.filterwarnings(
+    "ignore:Dropping of nuisance columns in Series.rank:FutureWarning"
+)
+@pytest.mark.filterwarnings(
+    "ignore:Calling Series.rank with numeric_only:FutureWarning"
+)
 @pytest.mark.parametrize("op", frame_kernels_raise)
 def test_transform_failure_typeerror(request, op):
     # GH 35964

pandas/tests/apply/test_series_apply.py

@@ -275,6 +275,8 @@ def test_transform(string_series):
         tm.assert_series_equal(result.reindex_like(expected), expected)
 
 
+@pytest.mark.filterwarnings("ignore:Calling Series.rank:FutureWarning")
+@pytest.mark.filterwarnings("ignore:Dropping of nuisance:FutureWarning")
 @pytest.mark.parametrize("op", series_transform_kernels)
 def test_transform_partial_failure(op, request):
     # GH 35964

pandas/tests/arithmetic/test_datetime64.py

@@ -649,7 +649,6 @@ def test_comparison_tzawareness_compat_scalars(self, comparison_op, box_with_arr
     # Raising in __eq__ will fallback to NumPy, which warns, fails,
     # then re-raises the original exception. So we just need to ignore.
     @pytest.mark.filterwarnings("ignore:elementwise comp:DeprecationWarning")
-    @pytest.mark.filterwarnings("ignore:Converting timezone-aware:FutureWarning")
     def test_scalar_comparison_tzawareness(
         self, comparison_op, other, tz_aware_fixture, box_with_array
     ):

pandas/tests/arithmetic/test_timedelta64.py

@@ -1730,6 +1730,7 @@ def test_td64arr_floordiv_td64arr_with_nat(
         result = np.asarray(left) // right
         tm.assert_equal(result, expected)
 
+    @pytest.mark.filterwarnings("ignore:invalid value encountered:RuntimeWarning")
     def test_td64arr_floordiv_tdscalar(self, box_with_array, scalar_td):
         # GH#18831, GH#19125
         box = box_with_array

pandas/tests/arrays/test_datetimes.py

@@ -81,7 +81,7 @@ def test_non_nano(self, unit, reso, dtype):
     def test_fields(self, unit, reso, field, dtype, dta_dti):
         dta, dti = dta_dti
 
-        # FIXME: assert (dti == dta).all()
+        assert (dti == dta).all()
 
         res = getattr(dta, field)
         expected = getattr(dti._data, field)

pandas/tests/extension/base/dim2.py

@@ -200,7 +200,7 @@ def test_reductions_2d_axis0(self, data, method):
             kwargs["ddof"] = 0
 
         try:
-            if method == "mean" and hasattr(data, "_mask"):
+            if method in ["mean", "var"] and hasattr(data, "_mask"):
                 # Empty slices produced by the mask cause RuntimeWarnings by numpy
                 with tm.assert_produces_warning(RuntimeWarning, check_stacklevel=False):
                     result = getattr(arr2d, method)(axis=0, **kwargs)

pandas/tests/extension/test_arrow.py

@@ -499,6 +499,9 @@ def test_in_numeric_groupby(self, data_for_grouping, request):
             )
         super().test_in_numeric_groupby(data_for_grouping)
 
+    @pytest.mark.filterwarnings(
+        "ignore:The default value of numeric_only:FutureWarning"
+    )
     @pytest.mark.parametrize("as_index", [True, False])
     def test_groupby_extension_agg(self, as_index, data_for_grouping, request):
         pa_dtype = data_for_grouping.dtype.pyarrow_dtype

pandas/tests/frame/methods/test_quantile.py

@@ -751,9 +751,6 @@ def test_quantile_empty_no_rows_ints(self, interp_method):
         exp = Series([np.nan, np.nan], index=["a", "b"], name=0.5)
         tm.assert_series_equal(res, exp)
 
-    @pytest.mark.filterwarnings(
-        "ignore:The behavior of DatetimeArray._from_sequence:FutureWarning"
-    )
     def test_quantile_empty_no_rows_dt64(self, interp_method):
         interpolation, method = interp_method
         # datetimes

pandas/tests/frame/methods/test_shift.py

@@ -564,8 +564,6 @@ def test_shift_dt64values_int_fill_deprecated(self):
         ],
         ids=lambda x: str(x.dtype),
     )
-    # TODO(2.0): remove filtering
-    @pytest.mark.filterwarnings("ignore:Index.ravel.*:FutureWarning")
     def test_shift_dt64values_axis1_invalid_fill(self, vals, as_cat):
         # GH#44564
         ser = Series(vals)

pandas/tests/generic/test_finalize.py

@@ -482,6 +482,9 @@ def test_finalize_called_eval_numexpr():
 # Binary operations
 
 
+@pytest.mark.filterwarnings(
+    "ignore:Automatic reindexing on DataFrame vs Series:FutureWarning"
+)
 @pytest.mark.parametrize("annotate", ["left", "right", "both"])
 @pytest.mark.parametrize(
     "args",

pandas/tests/groupby/aggregate/test_other.py

@@ -25,6 +25,7 @@
 from pandas.io.formats.printing import pprint_thing
 
 
+@pytest.mark.filterwarnings("ignore:Dropping invalid columns:FutureWarning")
 def test_agg_partial_failure_raises():
     # GH#43741
 

pandas/tests/indexes/datetimes/methods/test_snap.py

@@ -26,7 +26,6 @@ def astype_non_nano(dti_nano, unit):
     return dti
 
 
-@pytest.mark.filterwarnings("ignore::DeprecationWarning")
 @pytest.mark.parametrize("tz", [None, "Asia/Shanghai", "Europe/Berlin"])
 @pytest.mark.parametrize("name", [None, "my_dti"])
 @pytest.mark.parametrize("unit", ["ns", "us", "ms", "s"])

pandas/tests/indexes/test_any_index.py

@@ -133,8 +133,6 @@ def test_slice_keeps_name(self, index):
         assert index.name == index[1:].name
 
     @pytest.mark.parametrize("item", [101, "no_int", 2.5])
-    # FutureWarning from non-tuple sequence of nd indexing
-    @pytest.mark.filterwarnings("ignore::FutureWarning")
     def test_getitem_error(self, index, item):
         msg = "|".join(
             [
@@ -145,8 +143,6 @@ def test_getitem_error(self, index, item):
                     "are valid indices"
                 ),
                 "index out of bounds",  # string[pyarrow]
-                "Only integers, slices and integer or "
-                "boolean arrays are valid indices.",  # string[pyarrow]
             ]
         )
         with pytest.raises(IndexError, match=msg):

pandas/tests/indexes/test_base.py

@@ -230,7 +230,6 @@ def test_constructor_simple_new(self, vals, dtype):
         result = index._simple_new(index.values, dtype)
         tm.assert_index_equal(result, index)
 
-    @pytest.mark.filterwarnings("ignore:Passing keywords other:FutureWarning")
     @pytest.mark.parametrize("attr", ["values", "asi8"])
     @pytest.mark.parametrize("klass", [Index, DatetimeIndex])
     def test_constructor_dtypes_datetime(self, tz_naive_fixture, attr, klass):
@@ -1498,7 +1497,6 @@ def test_index_subclass_constructor_wrong_kwargs(index_maker):
         index_maker(foo="bar")
 
 
-@pytest.mark.filterwarnings("ignore:Passing keywords other:FutureWarning")
 def test_deprecated_fastpath():
     msg = "[Uu]nexpected keyword argument"
     with pytest.raises(TypeError, match=msg):

pandas/tests/series/accessors/test_dt_accessor.py

@@ -731,7 +731,6 @@ def test_dt_timetz_accessor(self, tz_naive_fixture):
             [["2016-01-07", "2016-01-01"], [[2016, 1, 4], [2015, 53, 5]]],
         ],
     )
-    @pytest.mark.filterwarnings("ignore:Inferring datetime64:FutureWarning")
     def test_isocalendar(self, input_series, expected_output):
         result = pd.to_datetime(Series(input_series)).dt.isocalendar()
         expected_frame = DataFrame(

pandas/tests/test_downstream.py

@@ -156,7 +156,6 @@ def test_oo_optimized_datetime_index_unpickle():
 @pytest.mark.network
 @tm.network
 # Cython import warning
-@pytest.mark.filterwarnings("ignore:pandas.util.testing is deprecated")
 @pytest.mark.filterwarnings("ignore:can't:ImportWarning")
 @pytest.mark.filterwarnings("ignore:.*64Index is deprecated:FutureWarning")
 @pytest.mark.filterwarnings(