TST: Remove unused fixtures

pandas/tests/apply/test_str.py

@@ -55,7 +55,7 @@ def test_with_string_args(datetime_series):
 
 @pytest.mark.parametrize("op", ["mean", "median", "std", "var"])
 @pytest.mark.parametrize("how", ["agg", "apply"])
-def test_apply_np_reducer(float_frame, op, how):
+def test_apply_np_reducer(op, how):
     # GH 39116
     float_frame = DataFrame({"a": [1, 2], "b": [3, 4]})
     result = getattr(float_frame, how)(op)

pandas/tests/arrays/categorical/common.py

@@ -2,7 +2,7 @@
 
 
 class TestCategorical:
-    def setup_method(self, method):
+    def setup_method(self):
         self.factor = Categorical(
             ["a", "b", "b", "a", "a", "c", "c", "c"], ordered=True
         )

pandas/tests/arrays/categorical/test_indexing.py

@@ -370,7 +370,7 @@ def array(self, dtype=None):
         yield
 
 
-def test_series_at(non_coercible_categorical):
+def test_series_at():
     arr = Categorical(["a", "b", "c"])
     ser = Series(arr)
     result = ser.at[0]

pandas/tests/arrays/masked/test_arithmetic.py

@@ -173,7 +173,7 @@ def test_error_len_mismatch(data, all_arithmetic_operators):
 
 
 @pytest.mark.parametrize("op", ["__neg__", "__abs__", "__invert__"])
-def test_unary_op_does_not_propagate_mask(data, op, request):
+def test_unary_op_does_not_propagate_mask(data, op):
     # https://github.com/pandas-dev/pandas/issues/39943
     data, _ = data
     ser = pd.Series(data)

pandas/tests/arrays/sparse/test_array.py

@@ -17,7 +17,7 @@
 
 
 class TestSparseArray:
-    def setup_method(self, method):
+    def setup_method(self):
         self.arr_data = np.array([np.nan, np.nan, 1, 2, 3, np.nan, 4, 5, np.nan, 6])
         self.arr = SparseArray(self.arr_data)
         self.zarr = SparseArray([0, 0, 1, 2, 3, 0, 4, 5, 0, 6], fill_value=0)

pandas/tests/arrays/string_/test_string.py

@@ -554,7 +554,7 @@ def test_to_numpy_na_value(dtype, nulls_fixture):
     tm.assert_numpy_array_equal(result, expected)
 
 
-def test_isin(dtype, request, fixed_now_ts):
+def test_isin(dtype, fixed_now_ts):
     s = pd.Series(["a", "b", None], dtype=dtype)
 
     result = s.isin(["a", "c"])

pandas/tests/config/test_config.py

@@ -18,7 +18,7 @@ def setup_class(cls):
         cls.do = deepcopy(getattr(cls.cf, "_deprecated_options"))
         cls.ro = deepcopy(getattr(cls.cf, "_registered_options"))
 
-    def setup_method(self, method):
+    def setup_method(self):
         setattr(self.cf, "_global_config", {})
         setattr(self.cf, "options", self.cf.DictWrapper(self.cf._global_config))
         setattr(self.cf, "_deprecated_options", {})
@@ -30,7 +30,7 @@ def setup_method(self, method):
         # "chained_assignment" option, so re-register it.
         self.cf.register_option("chained_assignment", "raise")
 
-    def teardown_method(self, method):
+    def teardown_method(self):
         setattr(self.cf, "_global_config", self.gc)
         setattr(self.cf, "_deprecated_options", self.do)
         setattr(self.cf, "_registered_options", self.ro)

pandas/tests/dtypes/cast/test_promote.py

@@ -348,7 +348,7 @@ def test_maybe_promote_bytes_with_any(bytes_dtype, any_numpy_dtype_reduced):
     _check_promote(dtype, fill_value, expected_dtype, exp_val_for_scalar)
 
 
-def test_maybe_promote_any_with_bytes(any_numpy_dtype_reduced, bytes_dtype):
+def test_maybe_promote_any_with_bytes(any_numpy_dtype_reduced):
     dtype = np.dtype(any_numpy_dtype_reduced)
 
     # create array of given dtype
@@ -391,9 +391,7 @@ def test_maybe_promote_datetime64_with_any(datetime64_dtype, any_numpy_dtype_red
     ],
     ids=["pd.Timestamp", "np.datetime64", "datetime.datetime", "datetime.date"],
 )
-def test_maybe_promote_any_with_datetime64(
-    any_numpy_dtype_reduced, datetime64_dtype, fill_value
-):
+def test_maybe_promote_any_with_datetime64(any_numpy_dtype_reduced, fill_value):
     dtype = np.dtype(any_numpy_dtype_reduced)
 
     # filling datetime with anything but datetime casts to object
@@ -465,9 +463,7 @@ def test_maybe_promote_timedelta64_with_any(timedelta64_dtype, any_numpy_dtype_r
     [pd.Timedelta(days=1), np.timedelta64(24, "h"), datetime.timedelta(1)],
     ids=["pd.Timedelta", "np.timedelta64", "datetime.timedelta"],
 )
-def test_maybe_promote_any_with_timedelta64(
-    any_numpy_dtype_reduced, timedelta64_dtype, fill_value
-):
+def test_maybe_promote_any_with_timedelta64(any_numpy_dtype_reduced, fill_value):
     dtype = np.dtype(any_numpy_dtype_reduced)
 
     # filling anything but timedelta with timedelta casts to object
@@ -496,7 +492,7 @@ def test_maybe_promote_string_with_any(string_dtype, any_numpy_dtype_reduced):
     _check_promote(dtype, fill_value, expected_dtype, exp_val_for_scalar)
 
 
-def test_maybe_promote_any_with_string(any_numpy_dtype_reduced, string_dtype):
+def test_maybe_promote_any_with_string(any_numpy_dtype_reduced):
     dtype = np.dtype(any_numpy_dtype_reduced)
 
     # create array of given dtype
@@ -523,7 +519,7 @@ def test_maybe_promote_object_with_any(object_dtype, any_numpy_dtype_reduced):
     _check_promote(dtype, fill_value, expected_dtype, exp_val_for_scalar)
 
 
-def test_maybe_promote_any_with_object(any_numpy_dtype_reduced, object_dtype):
+def test_maybe_promote_any_with_object(any_numpy_dtype_reduced):
     dtype = np.dtype(any_numpy_dtype_reduced)
 
     # create array of object dtype from a scalar value (i.e. passing

pandas/tests/dtypes/test_dtypes.py

@@ -848,7 +848,7 @@ def test_categories(self):
         tm.assert_index_equal(result.categories, pd.Index(["a", "b", "c"]))
         assert result.ordered is False
 
-    def test_equal_but_different(self, ordered):
+    def test_equal_but_different(self):
         c1 = CategoricalDtype([1, 2, 3])
         c2 = CategoricalDtype([1.0, 2.0, 3.0])
         assert c1 is not c2

pandas/tests/extension/base/setitem.py

@@ -357,7 +357,7 @@ def test_setitem_series(self, data, full_indexer):
         )
         self.assert_series_equal(result, expected)
 
-    def test_setitem_frame_2d_values(self, data, request):
+    def test_setitem_frame_2d_values(self, data):
         # GH#44514
         df = pd.DataFrame({"A": data})
         orig = df.copy()

pandas/tests/extension/test_sparse.py

@@ -54,7 +54,7 @@ def data(request):
 
 
 @pytest.fixture
-def data_for_twos(request):
+def data_for_twos():
     return SparseArray(np.ones(100) * 2)
 
 

pandas/tests/frame/indexing/test_setitem.py

@@ -397,7 +397,7 @@ def test_setitem_frame_length_0_str_key(self, indexer):
         expected["A"] = expected["A"].astype("object")
         tm.assert_frame_equal(df, expected)
 
-    def test_setitem_frame_duplicate_columns(self, using_array_manager, request):
+    def test_setitem_frame_duplicate_columns(self, using_array_manager):
         # GH#15695
         cols = ["A", "B", "C"] * 2
         df = DataFrame(index=range(3), columns=cols)
@@ -1099,7 +1099,7 @@ def test_setitem_duplicate_columns_not_inplace(self):
     @pytest.mark.parametrize(
         "value", [1, np.array([[1], [1]], dtype="int64"), [[1], [1]]]
     )
-    def test_setitem_same_dtype_not_inplace(self, value, using_array_manager, request):
+    def test_setitem_same_dtype_not_inplace(self, value, using_array_manager):
         # GH#39510
         cols = ["A", "B"]
         df = DataFrame(0, index=[0, 1], columns=cols)

pandas/tests/frame/methods/test_interpolate.py

@@ -320,7 +320,7 @@ def test_interp_ignore_all_good(self):
         result = df[["B", "D"]].interpolate(downcast=None)
         tm.assert_frame_equal(result, df[["B", "D"]])
 
-    def test_interp_time_inplace_axis(self, axis):
+    def test_interp_time_inplace_axis(self):
         # GH 9687
         periods = 5
         idx = date_range(start="2014-01-01", periods=periods)

pandas/tests/frame/methods/test_quantile.py

@@ -673,7 +673,7 @@ def test_quantile_ea_with_na(self, obj, index):
 
     # TODO(GH#39763): filtering can be removed after GH#39763 is fixed
     @pytest.mark.filterwarnings("ignore:Using .astype to convert:FutureWarning")
-    def test_quantile_ea_all_na(self, obj, index, frame_or_series, request):
+    def test_quantile_ea_all_na(self, obj, index):
         obj.iloc[:] = index._na_value
 
         # TODO(ArrayManager): this casting should be unnecessary after GH#39763 is fixed

pandas/tests/frame/methods/test_tz_convert.py

@@ -104,17 +104,17 @@ def test_tz_convert_and_localize(self, fn):
         # Not DatetimeIndex / PeriodIndex
         with pytest.raises(TypeError, match="DatetimeIndex"):
             df = DataFrame(index=int_idx)
-            df = getattr(df, fn)("US/Pacific")
+            getattr(df, fn)("US/Pacific")
 
         # Not DatetimeIndex / PeriodIndex
         with pytest.raises(TypeError, match="DatetimeIndex"):
             df = DataFrame(np.ones(5), MultiIndex.from_arrays([int_idx, l0]))
-            df = getattr(df, fn)("US/Pacific", level=0)
+            getattr(df, fn)("US/Pacific", level=0)
 
         # Invalid level
         with pytest.raises(ValueError, match="not valid"):
             df = DataFrame(index=l0)
-            df = getattr(df, fn)("US/Pacific", level=1)
+            getattr(df, fn)("US/Pacific", level=1)
 
     @pytest.mark.parametrize("copy", [True, False])
     def test_tz_convert_copy_inplace_mutate(self, copy, frame_or_series):

pandas/tests/frame/test_query_eval.py

@@ -36,7 +36,7 @@ def skip_if_no_pandas_parser(parser):
 
 
 class TestCompat:
-    def setup_method(self, method):
+    def setup_method(self):
         self.df = DataFrame({"A": [1, 2, 3]})
         self.expected1 = self.df[self.df.A > 0]
         self.expected2 = self.df.A + 1
@@ -1090,10 +1090,10 @@ def test_query_string_scalar_variable(self, parser, engine):
 
 
 class TestDataFrameEvalWithFrame:
-    def setup_method(self, method):
+    def setup_method(self):
         self.frame = DataFrame(np.random.randn(10, 3), columns=list("abc"))
 
-    def teardown_method(self, method):
+    def teardown_method(self):
         del self.frame
 
     def test_simple_expr(self, parser, engine):

pandas/tests/frame/test_repr_info.py

@@ -62,7 +62,7 @@ def test_assign_index_sequences(self):
         df.index = index
         repr(df)
 
-    def test_repr_with_mi_nat(self, float_string_frame):
+    def test_repr_with_mi_nat(self):
         df = DataFrame({"X": [1, 2]}, index=[[NaT, Timestamp("20130101")], ["a", "b"]])
         result = repr(df)
         expected = "              X\nNaT        a  1\n2013-01-01 b  2"

pandas/tests/frame/test_ufunc.py

@@ -81,7 +81,7 @@ def test_binary_input_dispatch_binop(dtype):
         ),
     ],
 )
-def test_ufunc_passes_args(func, arg, expected, request):
+def test_ufunc_passes_args(func, arg, expected):
     # GH#40662
     arr = np.array([[1, 2], [3, 4]])
     df = pd.DataFrame(arr)

pandas/tests/groupby/test_apply.py

@@ -241,7 +241,7 @@ def test_apply_with_mixed_dtype():
     tm.assert_series_equal(result1, result2)
 
 
-def test_groupby_as_index_apply(df):
+def test_groupby_as_index_apply():
     # GH #4648 and #3417
     df = DataFrame(
         {

pandas/tests/groupby/test_categorical.py

@@ -1447,7 +1447,7 @@ def test_dataframe_groupby_on_2_categoricals_when_observed_is_true(reduction_fun
 
 @pytest.mark.parametrize("observed", [False, None])
 def test_dataframe_groupby_on_2_categoricals_when_observed_is_false(
-    reduction_func, observed, request
+    reduction_func, observed
 ):
     # GH 23865
     # GH 27075

pandas/tests/groupby/test_groupby.py

@@ -821,7 +821,7 @@ def test_groupby_as_index_corner(df, ts):
         df.groupby(lambda x: x.lower(), as_index=False, axis=1)
 
 
-def test_groupby_multiple_key(df):
+def test_groupby_multiple_key():
     df = tm.makeTimeDataFrame()
     grouped = df.groupby([lambda x: x.year, lambda x: x.month, lambda x: x.day])
     agged = grouped.sum()

pandas/tests/groupby/test_size.py

@@ -20,7 +20,7 @@ def test_size(df, by):
 
 @pytest.mark.parametrize("by", ["A", "B", ["A", "B"]])
 @pytest.mark.parametrize("sort", [True, False])
-def test_size_sort(df, sort, by):
+def test_size_sort(sort, by):
     df = DataFrame(np.random.choice(20, (1000, 3)), columns=list("ABC"))
     left = df.groupby(by=by, sort=sort).size()
     right = df.groupby(by=by, sort=sort)["C"].apply(lambda a: a.shape[0])

pandas/tests/indexes/categorical/test_category.py

@@ -25,7 +25,7 @@ def simple_index(self) -> CategoricalIndex:
         return self._index_cls(list("aabbca"), categories=list("cab"), ordered=False)
 
     @pytest.fixture
-    def index(self, request):
+    def index(self):
         return tm.makeCategoricalIndex(100)
 
     def create_index(self, *, categories=None, ordered=False):

pandas/tests/indexes/datetimes/test_setops.py

@@ -417,7 +417,7 @@ def test_intersection_non_tick_no_fastpath(self):
 
 
 class TestBusinessDatetimeIndex:
-    def setup_method(self, method):
+    def setup_method(self):
         self.rng = bdate_range(START, END)
 
     def test_union(self, sort):
@@ -555,7 +555,7 @@ def test_intersection_duplicates(self, sort):
 
 
 class TestCustomDatetimeIndex:
-    def setup_method(self, method):
+    def setup_method(self):
         self.rng = bdate_range(START, END, freq="C")
 
     def test_union(self, sort):

pandas/tests/indexes/multi/test_setops.py

@@ -368,7 +368,7 @@ def test_union_sort_other_empty(slice_):
 
 
 @pytest.mark.xfail(reason="Not implemented.")
-def test_union_sort_other_empty_sort(slice_):
+def test_union_sort_other_empty_sort():
     # TODO(GH#25151): decide on True behaviour
     # # sort=True
     idx = MultiIndex.from_product([[1, 0], ["a", "b"]])

pandas/tests/indexes/test_base.py

@@ -452,7 +452,7 @@ def test_empty_fancy_raises(self, index):
         with pytest.raises(IndexError, match=msg):
             index[empty_farr]
 
-    def test_union_dt_as_obj(self, sort, simple_index):
+    def test_union_dt_as_obj(self, simple_index):
         # TODO: Replace with fixturesult
         index = simple_index
         date_index = date_range("2019-01-01", periods=10)
@@ -792,7 +792,7 @@ def test_isin(self, values, index, expected):
         result = index.isin(values)
         tm.assert_numpy_array_equal(result, expected)
 
-    def test_isin_nan_common_object(self, request, nulls_fixture, nulls_fixture2):
+    def test_isin_nan_common_object(self, nulls_fixture, nulls_fixture2):
         # Test cartesian product of null fixtures and ensure that we don't
         # mangle the various types (save a corner case with PyPy)
 
@@ -820,7 +820,7 @@ def test_isin_nan_common_object(self, request, nulls_fixture, nulls_fixture2):
                 np.array([False, False]),
             )
 
-    def test_isin_nan_common_float64(self, request, nulls_fixture):
+    def test_isin_nan_common_float64(self, nulls_fixture):
 
         if nulls_fixture is pd.NaT or nulls_fixture is pd.NA:
             # Check 1) that we cannot construct a Float64Index with this value

pandas/tests/indexes/test_numpy_compat.py

@@ -96,7 +96,7 @@ def test_numpy_ufuncs_basic(index, func):
 @pytest.mark.parametrize(
     "func", [np.isfinite, np.isinf, np.isnan, np.signbit], ids=lambda x: x.__name__
 )
-def test_numpy_ufuncs_other(index, func, request):
+def test_numpy_ufuncs_other(index, func):
     # test ufuncs of numpy, see:
     # https://numpy.org/doc/stable/reference/ufuncs.html
     if isinstance(index, (DatetimeIndex, TimedeltaIndex)):

pandas/tests/indexes/test_setops.py

@@ -432,7 +432,7 @@ def test_difference_preserves_type_empty(self, index, sort):
         expected = index[:0]
         tm.assert_index_equal(result, expected, exact=True)
 
-    def test_difference_name_retention_equals(self, index, sort, names):
+    def test_difference_name_retention_equals(self, index, names):
         if isinstance(index, MultiIndex):
             names = [[x] * index.nlevels for x in names]
         index = index.rename(names[0])

pandas/tests/indexing/common.py

@@ -43,7 +43,7 @@ class Base:
         "multi",
     }
 
-    def setup_method(self, method):
+    def setup_method(self):
 
         self.series_ints = Series(np.random.rand(4), index=np.arange(0, 8, 2))
         self.frame_ints = DataFrame(

pandas/tests/indexing/multiindex/test_sorted.py

@@ -64,7 +64,7 @@ def test_frame_getitem_not_sorted2(self, key):
         assert result.index.is_monotonic_increasing
         tm.assert_frame_equal(result, expected)
 
-    def test_sort_values_key(self, multiindex_dataframe_random_data):
+    def test_sort_values_key(self):
         arrays = [
             ["bar", "bar", "baz", "baz", "qux", "qux", "foo", "foo"],
             ["one", "two", "one", "two", "one", "two", "one", "two"],

pandas/tests/indexing/test_categorical.py

@@ -21,7 +21,7 @@
 
 
 class TestCategoricalIndex:
-    def setup_method(self, method):
+    def setup_method(self):
 
         self.df = DataFrame(
             {

pandas/tests/indexing/test_coercion.py

@@ -265,7 +265,7 @@ def test_insert_index_float64(self, insert, coerced_val, coerced_dtype):
         "insert_value",
         [pd.Timestamp("2012-01-01"), pd.Timestamp("2012-01-01", tz="Asia/Tokyo"), 1],
     )
-    def test_insert_index_datetimes(self, request, fill_val, exp_dtype, insert_value):
+    def test_insert_index_datetimes(self, fill_val, exp_dtype, insert_value):
 
         obj = pd.DatetimeIndex(
             ["2011-01-01", "2011-01-02", "2011-01-03", "2011-01-04"], tz=fill_val.tz