Correct some typos in the repository (#52254)

Signed-off-by: Alexander Seiler <seileralex@gmail.com>

Author: goggle

doc/source/getting_started/index.rst

@@ -533,7 +533,7 @@ Data sets do not only contain numerical data. pandas provides a wide range of fu
 Coming from...
 --------------
 
-Are you familiar with other software for manipulating tablular data? Learn
+Are you familiar with other software for manipulating tabular data? Learn
 the pandas-equivalent operations compared to software you already know:
 
 .. panels::

doc/source/user_guide/advanced.rst

@@ -322,7 +322,7 @@ As usual, **both sides** of the slicers are included as this is label indexing.
 .. warning::
 
    You should specify all axes in the ``.loc`` specifier, meaning the indexer for the **index** and
-   for the **columns**. There are some ambiguous cases where the passed indexer could be mis-interpreted
+   for the **columns**. There are some ambiguous cases where the passed indexer could be misinterpreted
    as indexing *both* axes, rather than into say the ``MultiIndex`` for the rows.
 
    You should do this:

doc/source/user_guide/groupby.rst

@@ -149,7 +149,7 @@ the columns except the one we specify:
    grouped.sum()
 
 The above GroupBy will split the DataFrame on its index (rows). To split by columns, first do
-a tranpose:
+a transpose:
 
 .. ipython::
 

pandas/core/apply.py

@@ -1491,7 +1491,7 @@ def validate_func_kwargs(
     Returns
     -------
     columns : List[str]
-        List of user-provied keys.
+        List of user-provided keys.
     func : List[Union[str, callable[...,Any]]]
         List of user-provided aggfuncs
 

pandas/core/config_init.py

@@ -711,13 +711,13 @@ def register_converter_cb(key) -> None:
 styler_max_rows = """
 : int, optional
     The maximum number of rows that will be rendered. May still be reduced to
-    satsify ``max_elements``, which takes precedence.
+    satisfy ``max_elements``, which takes precedence.
 """
 
 styler_max_columns = """
 : int, optional
     The maximum number of columns that will be rendered. May still be reduced to
-    satsify ``max_elements``, which takes precedence.
+    satisfy ``max_elements``, which takes precedence.
 """
 
 styler_precision = """

pandas/core/dtypes/common.py

@@ -1697,7 +1697,7 @@ def pandas_dtype(dtype) -> DtypeObj:
     try:
         with warnings.catch_warnings():
             # GH#51523 - Series.astype(np.integer) doesn't show
-            # numpy deprication warning of np.integer
+            # numpy deprecation warning of np.integer
             # Hence enabling DeprecationWarning
             warnings.simplefilter("always", DeprecationWarning)
             npdtype = np.dtype(dtype)

pandas/core/dtypes/dtypes.py

@@ -901,7 +901,7 @@ def _parse_dtype_strict(cls, freq: str_type) -> BaseOffset:
                 return freq_offset
 
         raise TypeError(
-            "PeriodDtype argument should be string or BaseOffet, "
+            "PeriodDtype argument should be string or BaseOffset, "
             f"got {type(freq).__name__}"
         )
 

pandas/core/generic.py

@@ -6559,7 +6559,7 @@ def infer_objects(self, copy: bool_t | None = None) -> Self:
         Parameters
         ----------
         copy : bool, default True
-            Whether to make a copy for non-object or non-inferrable columns
+            Whether to make a copy for non-object or non-inferable columns
             or Series.
 
         Returns

pandas/io/excel/_pyxlsb.py

@@ -89,7 +89,7 @@ def get_sheet_data(
         file_rows_needed: int | None = None,
     ) -> list[list[Scalar]]:
         data: list[list[Scalar]] = []
-        prevous_row_number = -1
+        previous_row_number = -1
         # When sparse=True the rows can have different lengths and empty rows are
         # not returned. The cells are namedtuples of row, col, value (r, c, v).
         for row in sheet.rows(sparse=True):
@@ -99,9 +99,9 @@ def get_sheet_data(
                 # trim trailing empty elements
                 converted_row.pop()
             if converted_row:
-                data.extend([[]] * (row_number - prevous_row_number - 1))
+                data.extend([[]] * (row_number - previous_row_number - 1))
                 data.append(converted_row)
-                prevous_row_number = row_number
+                previous_row_number = row_number
             if file_rows_needed is not None and len(data) >= file_rows_needed:
                 break
         if data:

pandas/io/formats/format.py

@@ -740,7 +740,7 @@ def _calc_max_rows_fitted(self) -> int | None:
             _, height = get_terminal_size()
             if self.max_rows == 0:
                 # rows available to fill with actual data
-                return height - self._get_number_of_auxillary_rows()
+                return height - self._get_number_of_auxiliary_rows()
 
             if self._is_screen_short(height):
                 max_rows = height
@@ -775,7 +775,7 @@ def _is_screen_narrow(self, max_width) -> bool:
     def _is_screen_short(self, max_height) -> bool:
         return bool(self.max_rows == 0 and len(self.frame) > max_height)
 
-    def _get_number_of_auxillary_rows(self) -> int:
+    def _get_number_of_auxiliary_rows(self) -> int:
         """Get number of rows occupied by prompt, dots and dimension info."""
         dot_row = 1
         prompt_row = 1