DOC: Correct grammatical issues with a/an usage

doc/make.py

@@ -105,7 +105,7 @@ def _process_single_doc(self, single_doc):
     @staticmethod
     def _run_os(*args) -> None:
         """
-        Execute a command as a OS terminal.
+        Execute a command as an OS terminal.
 
         Parameters
         ----------

pandas/_config/localization.py

@@ -79,7 +79,7 @@ def can_set_locale(lc: str, lc_var: int = locale.LC_ALL) -> bool:
         with set_locale(lc, lc_var=lc_var):
             pass
     except (ValueError, locale.Error):
-        # horrible name for a Exception subclass
+        # horrible name for an Exception subclass
         return False
     else:
         return True

pandas/core/arrays/categorical.py

@@ -269,7 +269,7 @@ class Categorical(NDArrayBackedExtensionArray, PandasObject, ObjectStringArrayMi
         categories are assumed to be the unique values of `values` (sorted, if
         possible, otherwise in the order in which they appear).
     ordered : bool, default False
-        Whether or not this categorical is treated as a ordered categorical.
+        Whether or not this categorical is treated as an ordered categorical.
         If True, the resulting categorical will be ordered.
         An ordered categorical respects, when sorted, the order of its
         `categories` attribute (which in turn is the `categories` argument, if
@@ -1103,7 +1103,7 @@ def set_categories(
         new_categories : Index-like
            The categories in new order.
         ordered : bool, default None
-           Whether or not the categorical is treated as a ordered categorical.
+           Whether or not the categorical is treated as an ordered categorical.
            If not given, do not change the ordered information.
         rename : bool, default False
            Whether or not the new_categories should be considered as a rename
@@ -1277,7 +1277,7 @@ def reorder_categories(self, new_categories, ordered=None) -> Self:
         new_categories : Index-like
            The categories in new order.
         ordered : bool, optional
-           Whether or not the categorical is treated as a ordered categorical.
+           Whether or not the categorical is treated as an ordered categorical.
            If not given, do not change the ordered information.
 
         Returns

pandas/core/arrays/timedeltas.py

@@ -1212,7 +1212,7 @@ def _objects_to_td64ns(
     data, unit=None, errors: DateTimeErrorChoices = "raise"
 ) -> np.ndarray:
     """
-    Convert a object-dtyped or string-dtyped array into an
+    Convert an object-dtyped or string-dtyped array into a
     timedelta64[ns]-dtyped array.
 
     Parameters

pandas/core/dtypes/base.py

@@ -517,7 +517,7 @@ class Registry:
     """
     Registry for dtype inference.
 
-    The registry allows one to map a string repr of a extension
+    The registry allows one to map a string repr of an extension
     dtype to an extension dtype. The string alias can be used in several
     places, including
 

pandas/core/dtypes/dtypes.py

@@ -176,7 +176,7 @@ class CategoricalDtype(PandasExtensionDtype, ExtensionDtype):
         The categories are stored in an Index,
         and if an index is provided the dtype of that index will be used.
     ordered : bool or None, default False
-        Whether or not this categorical is treated as a ordered categorical.
+        Whether or not this categorical is treated as an ordered categorical.
         None can be used to maintain the ordered value of existing categoricals when
         used in operations that combine categoricals, e.g. astype, and will resolve to
         False if there is no existing ordered to maintain.

pandas/core/internals/construction.py

@@ -215,7 +215,7 @@ def ndarray_to_mgr(
         # GH#19157
 
         if isinstance(values, (np.ndarray, ExtensionArray)) and values.ndim > 1:
-            # GH#12513 a EA dtype passed with a 2D array, split into
+            # GH#12513 an EA dtype passed with a 2D array, split into
             #  multiple EAs that view the values
             # error: No overload variant of "__getitem__" of "ExtensionArray"
             # matches argument type "Tuple[slice, int]"

pandas/core/window/expanding.py

@@ -1454,7 +1454,7 @@ def corr(
 
 class ExpandingGroupby(BaseWindowGroupby, Expanding):
     """
-    Provide a expanding groupby implementation.
+    Provide an expanding groupby implementation.
     """
 
     __module__ = "pandas.api.typing"

pandas/core/window/numba_.py

@@ -189,7 +189,7 @@ def generate_numba_table_func(
     """
     Generate a numba jitted function to apply window calculations table-wise.
 
-    Func will be passed a M window size x N number of columns array, and
+    Func will be passed an M window size x N number of columns array, and
     must return a 1 x N number of columns array.
 
     1. jit the user's function

pandas/io/excel/_odswriter.py

@@ -246,7 +246,7 @@ def _process_style(self, style: dict[str, Any]) -> str: ...
     def _process_style(self, style: None) -> None: ...
 
     def _process_style(self, style: dict[str, Any] | None) -> str | None:
-        """Convert a style dictionary to a OpenDocument style sheet
+        """Convert a style dictionary to an OpenDocument style sheet
 
         Parameters
         ----------

pandas/io/json/_normalize.py

@@ -219,7 +219,7 @@ def _simple_json_normalize(
     sep: str = ".",
 ) -> dict | list[dict] | Any:
     """
-    A optimized basic json_normalize
+    An optimized basic json_normalize
 
     Converts a nested dict into a flat dict ("record"), unlike
     json_normalize and nested_to_record it doesn't do anything clever.

pandas/plotting/_misc.py

@@ -282,12 +282,12 @@ def radviz(
     """
     Plot a multidimensional dataset in 2D.
 
-    Each Series in the DataFrame is represented as a evenly distributed
+    Each Series in the DataFrame is represented as an evenly distributed
     slice on a circle. Each data point is rendered in the circle according to
     the value on each Series. Highly correlated `Series` in the `DataFrame`
     are placed closer on the unit circle.
 
-    RadViz allow to project a N-dimensional data set into a 2D space where the
+    RadViz allow to project an N-dimensional data set into a 2D space where the
     influence of each dimension can be interpreted as a balance between the
     influence of all dimensions.
 

pandas/tests/indexes/datetimes/test_date_range.py

@@ -215,7 +215,7 @@ def test_date_range_multiplication_overflow(self):
         # check that overflows in calculating `addend = periods * stride`
         #  are caught
         with tm.assert_produces_warning(None):
-            # we should _not_ be seeing a overflow RuntimeWarning
+            # we should _not_ be seeing an overflow RuntimeWarning
             dti = date_range(start="1677-09-22", periods=213503, freq="D")
 
         assert dti[0] == Timestamp("1677-09-22")

pandas/tests/reshape/test_melt.py

@@ -933,7 +933,7 @@ def test_character_overlap(self):
         tm.assert_frame_equal(result.sort_index(axis=1), expected.sort_index(axis=1))
 
     def test_invalid_separator(self):
-        # if an invalid separator is supplied a empty data frame is returned
+        # if an invalid separator is supplied an empty data frame is returned
         sep = "nope!"
         df = DataFrame(
             {

pandas/tests/scalar/timestamp/test_constructors.py

@@ -49,7 +49,7 @@ def test_constructor_int_float_with_YM_unit(self, typ):
 
     @pytest.mark.parametrize("typ", [int, float])
     def test_construct_from_int_float_with_unit_out_of_bound_raises(self, typ):
-        # GH#50870  make sure we get a OutOfBoundsDatetime instead of OverflowError
+        # GH#50870  make sure we get an OutOfBoundsDatetime instead of OverflowError
         val = typ(150000000000000)
 
         msg = f"cannot convert input {val} with the unit 'D'"