CLN removing trailing commas (pandas-dev#36101)

pandas/tests/io/test_sql.py

@@ -2349,9 +2349,6 @@ def date_format(dt):
 
 
 def format_query(sql, *args):
-    """
-
-    """
     processed_args = []
     for arg in args:
         if isinstance(arg, float) and isna(arg):

pandas/tests/io/test_stata.py

@@ -1153,7 +1153,7 @@ def test_read_chunks_117(
             from_frame = parsed.iloc[pos : pos + chunksize, :].copy()
             from_frame = self._convert_categorical(from_frame)
             tm.assert_frame_equal(
-                from_frame, chunk, check_dtype=False, check_datetimelike_compat=True,
+                from_frame, chunk, check_dtype=False, check_datetimelike_compat=True
             )
 
             pos += chunksize
@@ -1251,7 +1251,7 @@ def test_read_chunks_115(
             from_frame = parsed.iloc[pos : pos + chunksize, :].copy()
             from_frame = self._convert_categorical(from_frame)
             tm.assert_frame_equal(
-                from_frame, chunk, check_dtype=False, check_datetimelike_compat=True,
+                from_frame, chunk, check_dtype=False, check_datetimelike_compat=True
             )
 
             pos += chunksize

pandas/tests/plotting/test_frame.py

@@ -1321,7 +1321,7 @@ def test_scatter_with_c_column_name_with_colors(self, cmap):
 
     def test_plot_scatter_with_s(self):
         # this refers to GH 32904
-        df = DataFrame(np.random.random((10, 3)) * 100, columns=["a", "b", "c"],)
+        df = DataFrame(np.random.random((10, 3)) * 100, columns=["a", "b", "c"])
 
         ax = df.plot.scatter(x="a", y="b", s="c")
         tm.assert_numpy_array_equal(df["c"].values, right=ax.collections[0].get_sizes())
@@ -1716,7 +1716,7 @@ def test_hist_df(self):
     def test_hist_weights(self, weights):
         # GH 33173
         np.random.seed(0)
-        df = pd.DataFrame(dict(zip(["A", "B"], np.random.randn(2, 100,))))
+        df = pd.DataFrame(dict(zip(["A", "B"], np.random.randn(2, 100))))
 
         ax1 = _check_plot_works(df.plot, kind="hist", weights=weights)
         ax2 = _check_plot_works(df.plot, kind="hist")

pandas/tests/resample/test_datetime_index.py

@@ -124,7 +124,7 @@ def test_resample_integerarray():
 
     result = ts.resample("3T").mean()
     expected = Series(
-        [1, 4, 7], index=pd.date_range("1/1/2000", periods=3, freq="3T"), dtype="Int64",
+        [1, 4, 7], index=pd.date_range("1/1/2000", periods=3, freq="3T"), dtype="Int64"
     )
     tm.assert_series_equal(result, expected)
 
@@ -764,7 +764,7 @@ def test_resample_origin():
 
 
 @pytest.mark.parametrize(
-    "origin", ["invalid_value", "epch", "startday", "startt", "2000-30-30", object()],
+    "origin", ["invalid_value", "epch", "startday", "startt", "2000-30-30", object()]
 )
 def test_resample_bad_origin(origin):
     rng = date_range("2000-01-01 00:00:00", "2000-01-01 02:00", freq="s")
@@ -777,9 +777,7 @@ def test_resample_bad_origin(origin):
         ts.resample("5min", origin=origin)
 
 
-@pytest.mark.parametrize(
-    "offset", ["invalid_value", "12dayys", "2000-30-30", object()],
-)
+@pytest.mark.parametrize("offset", ["invalid_value", "12dayys", "2000-30-30", object()])
 def test_resample_bad_offset(offset):
     rng = date_range("2000-01-01 00:00:00", "2000-01-01 02:00", freq="s")
     ts = Series(np.random.randn(len(rng)), index=rng)
@@ -1595,7 +1593,7 @@ def test_downsample_dst_at_midnight():
         "America/Havana", ambiguous=True
     )
     dti = pd.DatetimeIndex(dti, freq="D")
-    expected = DataFrame([7.5, 28.0, 44.5], index=dti,)
+    expected = DataFrame([7.5, 28.0, 44.5], index=dti)
     tm.assert_frame_equal(result, expected)
 
 

pandas/tests/reshape/merge/test_merge_index_as_string.py

@@ -29,7 +29,7 @@ def df2():
 
 @pytest.fixture(params=[[], ["outer"], ["outer", "inner"]])
 def left_df(request, df1):
-    """ Construct left test DataFrame with specified levels
+    """Construct left test DataFrame with specified levels
     (any of 'outer', 'inner', and 'v1')
     """
     levels = request.param
@@ -41,7 +41,7 @@ def left_df(request, df1):
 
 @pytest.fixture(params=[[], ["outer"], ["outer", "inner"]])
 def right_df(request, df2):
-    """ Construct right test DataFrame with specified levels
+    """Construct right test DataFrame with specified levels
     (any of 'outer', 'inner', and 'v2')
     """
     levels = request.param

pandas/tests/reshape/test_crosstab.py

@@ -354,7 +354,7 @@ def test_crosstab_normalize(self):
             crosstab(df.a, df.b, normalize="columns"),
         )
         tm.assert_frame_equal(
-            crosstab(df.a, df.b, normalize=0), crosstab(df.a, df.b, normalize="index"),
+            crosstab(df.a, df.b, normalize=0), crosstab(df.a, df.b, normalize="index")
         )
 
         row_normal_margins = DataFrame(
@@ -377,7 +377,7 @@ def test_crosstab_normalize(self):
             crosstab(df.a, df.b, normalize="index", margins=True), row_normal_margins
         )
         tm.assert_frame_equal(
-            crosstab(df.a, df.b, normalize="columns", margins=True), col_normal_margins,
+            crosstab(df.a, df.b, normalize="columns", margins=True), col_normal_margins
         )
         tm.assert_frame_equal(
             crosstab(df.a, df.b, normalize=True, margins=True), all_normal_margins

pandas/tests/reshape/test_get_dummies.py

@@ -161,7 +161,7 @@ def test_get_dummies_unicode(self, sparse):
         s = [e, eacute, eacute]
         res = get_dummies(s, prefix="letter", sparse=sparse)
         exp = DataFrame(
-            {"letter_e": [1, 0, 0], f"letter_{eacute}": [0, 1, 1]}, dtype=np.uint8,
+            {"letter_e": [1, 0, 0], f"letter_{eacute}": [0, 1, 1]}, dtype=np.uint8
         )
         if sparse:
             exp = exp.apply(SparseArray, fill_value=0)