Issue35925 remove more trailing commas (pandas-dev#35959)

* pandas/core/series.py

* pandas/core/window/ewm.py

* pandas/core/window/indexers.py

* pandas/core/window/numba_.py

* pandas/core/window/rolling.py

* pandas/io/formats/css.py

* pandas/io/formats/format.py

* pandas/io/orc.py

Author: jpribyl

pandas/core/series.py

@@ -962,12 +962,12 @@ def _get_values_tuple(self, key):
         # If key is contained, would have returned by now
         indexer, new_index = self.index.get_loc_level(key)
         return self._constructor(self._values[indexer], index=new_index).__finalize__(
-            self,
+            self
         )
 
     def _get_values(self, indexer):
         try:
-            return self._constructor(self._mgr.get_slice(indexer)).__finalize__(self,)
+            return self._constructor(self._mgr.get_slice(indexer)).__finalize__(self)
         except ValueError:
             # mpl compat if we look up e.g. ser[:, np.newaxis];
             #  see tests.series.timeseries.test_mpl_compat_hack

pandas/core/window/ewm.py

@@ -362,7 +362,7 @@ def var(self, bias: bool = False, *args, **kwargs):
 
         def f(arg):
             return window_aggregations.ewmcov(
-                arg, arg, self.com, self.adjust, self.ignore_na, self.min_periods, bias,
+                arg, arg, self.com, self.adjust, self.ignore_na, self.min_periods, bias
             )
 
         return self._apply(f)
@@ -458,7 +458,7 @@ def _get_corr(X, Y):
 
             def _cov(x, y):
                 return window_aggregations.ewmcov(
-                    x, y, self.com, self.adjust, self.ignore_na, self.min_periods, 1,
+                    x, y, self.com, self.adjust, self.ignore_na, self.min_periods, 1
                 )
 
             x_values = X._prep_values()

pandas/core/window/indexers.py

@@ -40,7 +40,7 @@ class BaseIndexer:
     """Base class for window bounds calculations."""
 
     def __init__(
-        self, index_array: Optional[np.ndarray] = None, window_size: int = 0, **kwargs,
+        self, index_array: Optional[np.ndarray] = None, window_size: int = 0, **kwargs
     ):
         """
         Parameters
@@ -105,7 +105,7 @@ def get_window_bounds(
     ) -> Tuple[np.ndarray, np.ndarray]:
 
         return calculate_variable_window_bounds(
-            num_values, self.window_size, min_periods, center, closed, self.index_array,
+            num_values, self.window_size, min_periods, center, closed, self.index_array
         )
 
 
@@ -316,7 +316,7 @@ def get_window_bounds(
             # Cannot use groupby_indicies as they might not be monotonic with the object
             # we're rolling over
             window_indicies = np.arange(
-                window_indicies_start, window_indicies_start + len(indices),
+                window_indicies_start, window_indicies_start + len(indices)
             )
             window_indicies_start += len(indices)
             # Extend as we'll be slicing window like [start, end)

pandas/core/window/numba_.py

@@ -57,7 +57,7 @@ def generate_numba_apply_func(
 
     @numba.jit(nopython=nopython, nogil=nogil, parallel=parallel)
     def roll_apply(
-        values: np.ndarray, begin: np.ndarray, end: np.ndarray, minimum_periods: int,
+        values: np.ndarray, begin: np.ndarray, end: np.ndarray, minimum_periods: int
     ) -> np.ndarray:
         result = np.empty(len(begin))
         for i in loop_range(len(result)):

pandas/core/window/rolling.py

@@ -2117,7 +2117,7 @@ def count(self):
     @Substitution(name="rolling")
     @Appender(_shared_docs["apply"])
     def apply(
-        self, func, raw=False, engine=None, engine_kwargs=None, args=None, kwargs=None,
+        self, func, raw=False, engine=None, engine_kwargs=None, args=None, kwargs=None
     ):
         return super().apply(
             func,

pandas/io/formats/css.py

@@ -20,9 +20,7 @@ def expand(self, prop, value: str):
         try:
             mapping = self.SIDE_SHORTHANDS[len(tokens)]
         except KeyError:
-            warnings.warn(
-                f'Could not expand "{prop}: {value}"', CSSWarning,
-            )
+            warnings.warn(f'Could not expand "{prop}: {value}"', CSSWarning)
             return
         for key, idx in zip(self.SIDES, mapping):
             yield prop_fmt.format(key), tokens[idx]
@@ -117,10 +115,7 @@ def __call__(self, declarations_str, inherited=None):
                 props[prop] = self.size_to_pt(
                     props[prop], em_pt=font_size, conversions=self.BORDER_WIDTH_RATIOS
                 )
-            for prop in [
-                f"margin-{side}",
-                f"padding-{side}",
-            ]:
+            for prop in [f"margin-{side}", f"padding-{side}"]:
                 if prop in props:
                     # TODO: support %
                     props[prop] = self.size_to_pt(

pandas/io/formats/format.py

@@ -80,7 +80,7 @@
 FloatFormatType = Union[str, Callable, "EngFormatter"]
 ColspaceType = Mapping[Label, Union[str, int]]
 ColspaceArgType = Union[
-    str, int, Sequence[Union[str, int]], Mapping[Label, Union[str, int]],
+    str, int, Sequence[Union[str, int]], Mapping[Label, Union[str, int]]
 ]
 
 common_docstring = """
@@ -741,7 +741,7 @@ def _to_str_columns(self) -> List[List[str]]:
             for i, c in enumerate(frame):
                 fmt_values = self._format_col(i)
                 fmt_values = _make_fixed_width(
-                    fmt_values, self.justify, minimum=col_space.get(c, 0), adj=self.adj,
+                    fmt_values, self.justify, minimum=col_space.get(c, 0), adj=self.adj
                 )
                 stringified.append(fmt_values)
         else:
@@ -1069,7 +1069,7 @@ def _get_formatted_index(self, frame: "DataFrame") -> List[str]:
         fmt_index = [
             tuple(
                 _make_fixed_width(
-                    list(x), justify="left", minimum=col_space.get("", 0), adj=self.adj,
+                    list(x), justify="left", minimum=col_space.get("", 0), adj=self.adj
                 )
             )
             for x in fmt_index

pandas/io/orc.py

@@ -12,7 +12,7 @@
 
 
 def read_orc(
-    path: FilePathOrBuffer, columns: Optional[List[str]] = None, **kwargs,
+    path: FilePathOrBuffer, columns: Optional[List[str]] = None, **kwargs
 ) -> "DataFrame":
     """
     Load an ORC object from the file path, returning a DataFrame.