DOC: Replace @doc decorator with inline docstring in pandas/core/algorithms.py and pandas/core/base.py

pandas/core/algorithms.py

@@ -7,7 +7,6 @@
 
 import decimal
 import operator
-from textwrap import dedent
 from typing import (
     TYPE_CHECKING,
     Literal,
@@ -35,10 +34,7 @@
     TakeIndexer,
     npt,
 )
-from pandas.util._decorators import (
-    doc,
-    set_module,
-)
+from pandas.util._decorators import set_module
 from pandas.util._exceptions import find_stack_level
 
 from pandas.core.dtypes.cast import (
@@ -654,28 +650,6 @@ def factorize_array(
 
 
 @set_module("pandas")
-@doc(
-    values=dedent(
-        """\
-    values : sequence
-        A 1-D sequence. Sequences that aren't pandas objects are
-        coerced to ndarrays before factorization.
-    """
-    ),
-    sort=dedent(
-        """\
-    sort : bool, default False
-        Sort `uniques` and shuffle `codes` to maintain the
-        relationship.
-    """
-    ),
-    size_hint=dedent(
-        """\
-    size_hint : int, optional
-        Hint to the hashtable sizer.
-    """
-    ),
-)
 def factorize(
     values,
     sort: bool = False,
@@ -692,12 +666,18 @@ def factorize(
 
     Parameters
     ----------
-    {values}{sort}
+    values : sequence
+        A 1-D sequence. Sequences that aren't pandas objects are
+        coerced to ndarrays before factorization.
+    sort : bool, default False
+        Sort `uniques` and shuffle `codes` to maintain the
+        relationship.
     use_na_sentinel : bool, default True
         If True, the sentinel -1 will be used for NaN values. If False,
         NaN values will be encoded as non-negative integers and will not drop the
         NaN from the uniques of the values.
-    {size_hint}\
+    size_hint : int, optional
+        Hint to the hashtable sizer.
 
     Returns
     -------

pandas/core/base.py

@@ -1279,9 +1279,7 @@ def _memory_usage(self, deep: bool = False) -> int:
 
     @doc(
         algorithms.factorize,
-        values="",
         order="",
-        size_hint="",
         sort=textwrap.dedent(
             """\
             sort : bool, default False

pandas/io/html.py

@@ -24,10 +24,7 @@
     AbstractMethodError,
     EmptyDataError,
 )
-from pandas.util._decorators import (
-    doc,
-    set_module,
-)
+from pandas.util._decorators import set_module
 from pandas.util._validators import check_dtype_backend
 
 from pandas.core.dtypes.common import is_list_like
@@ -36,7 +33,6 @@
 from pandas.core.indexes.base import Index
 from pandas.core.indexes.multi import MultiIndex
 from pandas.core.series import Series
-from pandas.core.shared_docs import _shared_docs
 
 from pandas.io.common import (
     get_handle,
@@ -1024,7 +1020,6 @@ def _parse(
 
 
 @set_module("pandas")
-@doc(storage_options=_shared_docs["storage_options"])
 def read_html(
     io: FilePath | ReadBuffer[str],
     *,
@@ -1155,7 +1150,15 @@ def read_html(
 
         .. versionadded:: 2.0
 
-    {storage_options}
+    storage_options : dict, optional
+        Extra options that make sense for a particular storage connection, e.g.
+        host, port, username, password, etc. For HTTP(S) URLs the key-value pairs
+        are forwarded to ``urllib.request.Request`` as header options. For other
+        URLs (e.g. starting with "s3://", and "gcs://") the key-value pairs are
+        forwarded to ``fsspec.open``. Please see ``fsspec`` and ``urllib`` for more
+        details, and for more examples on storage options refer `here
+        <https://pandas.pydata.org/docs/user_guide/io.html?
+        highlight=storage_options#reading-writing-remote-files>`_.
 
         .. versionadded:: 2.1.0