CLN clearing unnecessary trailing commas

pandas/tests/scalar/test_na_scalar.py

@@ -111,7 +111,7 @@ def test_pow_special(value, asarray):
 
 
 @pytest.mark.parametrize(
-    "value", [1, 1.0, True, np.bool_(True), np.int_(1), np.float_(1)],
+    "value", [1, 1.0, True, np.bool_(True), np.int_(1), np.float_(1)]
 )
 @pytest.mark.parametrize("asarray", [True, False])
 def test_rpow_special(value, asarray):
@@ -128,9 +128,7 @@ def test_rpow_special(value, asarray):
     assert result == value
 
 
-@pytest.mark.parametrize(
-    "value", [-1, -1.0, np.int_(-1), np.float_(-1)],
-)
+@pytest.mark.parametrize("value", [-1, -1.0, np.int_(-1), np.float_(-1)])
 @pytest.mark.parametrize("asarray", [True, False])
 def test_rpow_minus_one(value, asarray):
     if asarray:
@@ -193,9 +191,7 @@ def test_logical_not():
     assert ~NA is NA
 
 
-@pytest.mark.parametrize(
-    "shape", [(3,), (3, 3), (1, 2, 3)],
-)
+@pytest.mark.parametrize("shape", [(3,), (3, 3), (1, 2, 3)])
 def test_arithmetic_ndarray(shape, all_arithmetic_functions):
     op = all_arithmetic_functions
     a = np.zeros(shape)

pandas/tests/scalar/timestamp/test_arithmetic.py

@@ -213,7 +213,7 @@ def test_add_int_with_freq(self, ts, other):
         with pytest.raises(TypeError, match=msg):
             other - ts
 
-    @pytest.mark.parametrize("shape", [(6,), (2, 3,)])
+    @pytest.mark.parametrize("shape", [(6,), (2, 3)])
     def test_addsub_m8ndarray(self, shape):
         # GH#33296
         ts = Timestamp("2020-04-04 15:45")
@@ -237,7 +237,7 @@ def test_addsub_m8ndarray(self, shape):
         with pytest.raises(TypeError, match=msg):
             other - ts
 
-    @pytest.mark.parametrize("shape", [(6,), (2, 3,)])
+    @pytest.mark.parametrize("shape", [(6,), (2, 3)])
     def test_addsub_m8ndarray_tzaware(self, shape):
         # GH#33296
         ts = Timestamp("2020-04-04 15:45", tz="US/Pacific")

pandas/tests/series/methods/test_argsort.py

@@ -9,7 +9,7 @@ class TestSeriesArgsort:
     def _check_accum_op(self, name, ser, check_dtype=True):
         func = getattr(np, name)
         tm.assert_numpy_array_equal(
-            func(ser).values, func(np.array(ser)), check_dtype=check_dtype,
+            func(ser).values, func(np.array(ser)), check_dtype=check_dtype
         )
 
         # with missing values

pandas/tests/series/methods/test_convert_dtypes.py

@@ -219,10 +219,10 @@ class TestSeriesConvertDtypes:
                 pd.to_datetime(["2020-01-14 10:00", "2020-01-15 11:11"]),
                 object,
                 {
-                    ((True,), (True, False), (True, False), (True, False),): np.dtype(
+                    ((True,), (True, False), (True, False), (True, False)): np.dtype(
                         "datetime64[ns]"
                     ),
-                    ((False,), (True, False), (True, False), (True, False),): np.dtype(
+                    ((False,), (True, False), (True, False), (True, False)): np.dtype(
                         "O"
                     ),
                 },

pandas/tests/series/methods/test_drop_duplicates.py

@@ -141,7 +141,7 @@ def test_drop_duplicates_categorical_non_bool(self, dtype, ordered):
     def test_drop_duplicates_categorical_bool(self, ordered):
         tc = Series(
             Categorical(
-                [True, False, True, False], categories=[True, False], ordered=ordered,
+                [True, False, True, False], categories=[True, False], ordered=ordered
             )
         )
 

pandas/tests/series/methods/test_interpolate.py

@@ -30,7 +30,7 @@
     ]
 )
 def nontemporal_method(request):
-    """ Fixture that returns an (method name, required kwargs) pair.
+    """Fixture that returns an (method name, required kwargs) pair.
 
     This fixture does not include method 'time' as a parameterization; that
     method requires a Series with a DatetimeIndex, and is generally tested
@@ -60,7 +60,7 @@ def nontemporal_method(request):
     ]
 )
 def interp_methods_ind(request):
-    """ Fixture that returns a (method name, required kwargs) pair to
+    """Fixture that returns a (method name, required kwargs) pair to
     be tested for various Index types.
 
     This fixture does not include methods - 'time', 'index', 'nearest',

pandas/tests/series/methods/test_unstack.py

@@ -75,9 +75,7 @@ def test_unstack_tuplename_in_multiindex():
 
     expected = pd.DataFrame(
         [[1, 1, 1], [1, 1, 1], [1, 1, 1]],
-        columns=pd.MultiIndex.from_tuples(
-            [("a",), ("b",), ("c",)], names=[("A", "a")],
-        ),
+        columns=pd.MultiIndex.from_tuples([("a",), ("b",), ("c",)], names=[("A", "a")]),
         index=pd.Index([1, 2, 3], name=("B", "b")),
     )
     tm.assert_frame_equal(result, expected)
@@ -115,7 +113,7 @@ def test_unstack_mixed_type_name_in_multiindex(
     result = ser.unstack(unstack_idx)
 
     expected = pd.DataFrame(
-        expected_values, columns=expected_columns, index=expected_index,
+        expected_values, columns=expected_columns, index=expected_index
     )
     tm.assert_frame_equal(result, expected)
 

pandas/tests/series/test_cumulative.py

@@ -17,7 +17,7 @@
 def _check_accum_op(name, series, check_dtype=True):
     func = getattr(np, name)
     tm.assert_numpy_array_equal(
-        func(series).values, func(np.array(series)), check_dtype=check_dtype,
+        func(series).values, func(np.array(series)), check_dtype=check_dtype
     )
 
     # with missing values

pandas/tests/test_algos.py

@@ -970,7 +970,7 @@ def test_isin_int_df_string_search(self):
     @pytest.mark.xfail(reason="problem related with issue #34125")
     def test_isin_nan_df_string_search(self):
         """Comparing df with nan value (np.nan,2) with a string at isin() ("NaN")
-        -> should not match values because np.nan is not equal str NaN """
+        -> should not match values because np.nan is not equal str NaN"""
         df = pd.DataFrame({"values": [np.nan, 2]})
         result = df.isin(["NaN"])
         expected_false = pd.DataFrame({"values": [False, False]})