CLN remove unnecessary trailing commas to get ready for new version of black: _testing -> generic

pandas/_testing.py

@@ -939,7 +939,7 @@ def assert_categorical_equal(
     if check_category_order:
         assert_index_equal(left.categories, right.categories, obj=f"{obj}.categories")
         assert_numpy_array_equal(
-            left.codes, right.codes, check_dtype=check_dtype, obj=f"{obj}.codes",
+            left.codes, right.codes, check_dtype=check_dtype, obj=f"{obj}.codes"
         )
     else:
         try:
@@ -948,9 +948,7 @@ def assert_categorical_equal(
         except TypeError:
             # e.g. '<' not supported between instances of 'int' and 'str'
             lc, rc = left.categories, right.categories
-        assert_index_equal(
-            lc, rc, obj=f"{obj}.categories",
-        )
+        assert_index_equal(lc, rc, obj=f"{obj}.categories")
         assert_index_equal(
             left.categories.take(left.codes),
             right.categories.take(right.codes),
@@ -1092,7 +1090,7 @@ def _raise(left, right, err_msg):
         if err_msg is None:
             if left.shape != right.shape:
                 raise_assert_detail(
-                    obj, f"{obj} shapes are different", left.shape, right.shape,
+                    obj, f"{obj} shapes are different", left.shape, right.shape
                 )
 
             diff = 0
@@ -1559,7 +1557,7 @@ def assert_frame_equal(
     # shape comparison
     if left.shape != right.shape:
         raise_assert_detail(
-            obj, f"{obj} shape mismatch", f"{repr(left.shape)}", f"{repr(right.shape)}",
+            obj, f"{obj} shape mismatch", f"{repr(left.shape)}", f"{repr(right.shape)}"
         )
 
     if check_like:
@@ -2884,7 +2882,7 @@ def convert_rows_list_to_csv_str(rows_list: List[str]):
     return expected
 
 
-def external_error_raised(expected_exception: Type[Exception],) -> ContextManager:
+def external_error_raised(expected_exception: Type[Exception]) -> ContextManager:
     """
     Helper function to mark pytest.raises that have an external error message.
 

pandas/core/algorithms.py

@@ -462,7 +462,7 @@ def isin(comps: AnyArrayLike, values: AnyArrayLike) -> np.ndarray:
 
 
 def _factorize_array(
-    values, na_sentinel: int = -1, size_hint=None, na_value=None, mask=None,
+    values, na_sentinel: int = -1, size_hint=None, na_value=None, mask=None
 ) -> Tuple[np.ndarray, np.ndarray]:
     """
     Factorize an array-like to codes and uniques.

pandas/core/arrays/_mixins.py

@@ -40,7 +40,7 @@ def take(
             fill_value = self._validate_fill_value(fill_value)
 
         new_data = take(
-            self._ndarray, indices, allow_fill=allow_fill, fill_value=fill_value,
+            self._ndarray, indices, allow_fill=allow_fill, fill_value=fill_value
         )
         return self._from_backing_data(new_data)
 

pandas/core/arrays/categorical.py

@@ -1505,7 +1505,7 @@ def argsort(self, ascending=True, kind="quicksort", **kwargs):
         return super().argsort(ascending=ascending, kind=kind, **kwargs)
 
     def sort_values(
-        self, inplace: bool = False, ascending: bool = True, na_position: str = "last",
+        self, inplace: bool = False, ascending: bool = True, na_position: str = "last"
     ):
         """
         Sort the Categorical by category value returning a new

pandas/core/arrays/integer.py

@@ -138,7 +138,7 @@ def __from_arrow__(
         return IntegerArray._concat_same_type(results)
 
 
-def integer_array(values, dtype=None, copy: bool = False,) -> "IntegerArray":
+def integer_array(values, dtype=None, copy: bool = False) -> "IntegerArray":
     """
     Infer and return an integer array of the values.
 
@@ -182,7 +182,7 @@ def safe_cast(values, dtype, copy: bool):
 
 
 def coerce_to_array(
-    values, dtype, mask=None, copy: bool = False,
+    values, dtype, mask=None, copy: bool = False
 ) -> Tuple[np.ndarray, np.ndarray]:
     """
     Coerce the input values array to numpy arrays with a mask

pandas/core/arrays/masked.py

@@ -126,7 +126,7 @@ def __invert__(self: BaseMaskedArrayT) -> BaseMaskedArrayT:
         return type(self)(~self._data, self._mask)
 
     def to_numpy(
-        self, dtype=None, copy: bool = False, na_value: Scalar = lib.no_default,
+        self, dtype=None, copy: bool = False, na_value: Scalar = lib.no_default
     ) -> np.ndarray:
         """
         Convert to a NumPy Array.

pandas/core/arrays/numpy_.py

@@ -280,7 +280,7 @@ def isna(self) -> np.ndarray:
         return isna(self._ndarray)
 
     def fillna(
-        self, value=None, method: Optional[str] = None, limit: Optional[int] = None,
+        self, value=None, method: Optional[str] = None, limit: Optional[int] = None
     ) -> "PandasArray":
         # TODO(_values_for_fillna): remove this
         value, method = validate_fillna_kwargs(value, method)

pandas/core/arrays/period.py

@@ -634,7 +634,7 @@ def _sub_period_array(self, other):
         return new_values
 
     def _addsub_int_array(
-        self, other: np.ndarray, op: Callable[[Any, Any], Any],
+        self, other: np.ndarray, op: Callable[[Any, Any], Any]
     ) -> "PeriodArray":
         """
         Add or subtract array of integers; equivalent to applying

pandas/core/construction.py

@@ -514,9 +514,7 @@ def sanitize_array(
     return subarr
 
 
-def _try_cast(
-    arr, dtype: Optional[DtypeObj], copy: bool, raise_cast_failure: bool,
-):
+def _try_cast(arr, dtype: Optional[DtypeObj], copy: bool, raise_cast_failure: bool):
     """
     Convert input to numpy ndarray and optionally cast to a given dtype.
 

pandas/core/generic.py

@@ -315,17 +315,13 @@ def _data(self):
     @property
     def _AXIS_NUMBERS(self) -> Dict[str, int]:
         """.. deprecated:: 1.1.0"""
-        warnings.warn(
-            "_AXIS_NUMBERS has been deprecated.", FutureWarning, stacklevel=3,
-        )
+        warnings.warn("_AXIS_NUMBERS has been deprecated.", FutureWarning, stacklevel=3)
         return {"index": 0}
 
     @property
     def _AXIS_NAMES(self) -> Dict[int, str]:
         """.. deprecated:: 1.1.0"""
-        warnings.warn(
-            "_AXIS_NAMES has been deprecated.", FutureWarning, stacklevel=3,
-        )
+        warnings.warn("_AXIS_NAMES has been deprecated.", FutureWarning, stacklevel=3)
         return {0: "index"}
 
     def _construct_axes_dict(self, axes=None, **kwargs):
@@ -5128,7 +5124,7 @@ def pipe(self, func, *args, **kwargs):
         ...    .pipe(g, arg1=a)
         ...    .pipe((func, 'arg2'), arg1=a, arg3=c)
         ...  )  # doctest: +SKIP
-    """
+        """
         return com.pipe(self, func, *args, **kwargs)
 
     _shared_docs["aggregate"] = dedent(
@@ -5630,7 +5626,7 @@ def astype(
 
         else:
             # else, only a single dtype is given
-            new_data = self._mgr.astype(dtype=dtype, copy=copy, errors=errors,)
+            new_data = self._mgr.astype(dtype=dtype, copy=copy, errors=errors)
             return self._constructor(new_data).__finalize__(self, method="astype")
 
         # GH 33113: handle empty frame or series
@@ -6520,7 +6516,7 @@ def replace(
         3     b
         4     b
         dtype: object
-    """
+        """
         if not (
             is_scalar(to_replace)
             or is_re_compilable(to_replace)
@@ -7772,7 +7768,7 @@ def between_time(
             raise TypeError("Index must be DatetimeIndex")
 
         indexer = index.indexer_between_time(
-            start_time, end_time, include_start=include_start, include_end=include_end,
+            start_time, end_time, include_start=include_start, include_end=include_end
         )
         return self._take_with_is_copy(indexer, axis=axis)
 
@@ -8939,7 +8935,7 @@ def _where(
 
             self._check_inplace_setting(other)
             new_data = self._mgr.putmask(
-                mask=cond, new=other, align=align, axis=block_axis,
+                mask=cond, new=other, align=align, axis=block_axis
             )
             result = self._constructor(new_data)
             return self._update_inplace(result)