DOC: re-use storage_options (#37953)

Author: twoertwein

pandas/core/frame.py

@@ -118,7 +118,7 @@
 )
 from pandas.core.dtypes.missing import isna, notna
 
-from pandas.core import algorithms, common as com, nanops, ops
+from pandas.core import algorithms, common as com, generic, nanops, ops
 from pandas.core.accessor import CachedAccessor
 from pandas.core.aggregation import (
     aggregate,
@@ -2066,6 +2066,7 @@ def _from_arrays(
         )
         return cls(mgr)
 
+    @doc(storage_options=generic._shared_docs["storage_options"])
     @deprecate_kwarg(old_arg_name="fname", new_arg_name="path")
     def to_stata(
         self,
@@ -2118,7 +2119,7 @@ def to_stata(
         variable_labels : dict
             Dictionary containing columns as keys and variable labels as
             values. Each label must be 80 characters or smaller.
-        version : {114, 117, 118, 119, None}, default 114
+        version : {{114, 117, 118, 119, None}}, default 114
             Version to use in the output dta file. Set to None to let pandas
             decide between 118 or 119 formats depending on the number of
             columns in the frame. Version 114 can be read by Stata 10 and
@@ -2147,23 +2148,17 @@ def to_stata(
         compression : str or dict, default 'infer'
             For on-the-fly compression of the output dta. If string, specifies
             compression mode. If dict, value at key 'method' specifies
-            compression mode. Compression mode must be one of {'infer', 'gzip',
-            'bz2', 'zip', 'xz', None}. If compression mode is 'infer' and
+            compression mode. Compression mode must be one of {{'infer', 'gzip',
+            'bz2', 'zip', 'xz', None}}. If compression mode is 'infer' and
             `fname` is path-like, then detect compression from the following
             extensions: '.gz', '.bz2', '.zip', or '.xz' (otherwise no
-            compression). If dict and compression mode is one of {'zip',
-            'gzip', 'bz2'}, or inferred as one of the above, other entries
+            compression). If dict and compression mode is one of {{'zip',
+            'gzip', 'bz2'}}, or inferred as one of the above, other entries
             passed as additional compression options.
 
             .. versionadded:: 1.1.0
 
-        storage_options : dict, optional
-            Extra options that make sense for a particular storage connection, e.g.
-            host, port, username, password, etc., if using a URL that will
-            be parsed by ``fsspec``, e.g., starting "s3://", "gcs://". An error
-            will be raised if providing this argument with a local path or
-            a file-like buffer. See the fsspec and backend storage implementation
-            docs for the set of allowed keys and values.
+        {storage_options}
 
             .. versionadded:: 1.2.0
 
@@ -2186,9 +2181,9 @@ def to_stata(
 
         Examples
         --------
-        >>> df = pd.DataFrame({'animal': ['falcon', 'parrot', 'falcon',
+        >>> df = pd.DataFrame({{'animal': ['falcon', 'parrot', 'falcon',
         ...                               'parrot'],
-        ...                    'speed': [350, 18, 361, 15]})
+        ...                    'speed': [350, 18, 361, 15]}})
         >>> df.to_stata('animals.dta')  # doctest: +SKIP
         """
         if version not in (114, 117, 118, 119, None):
@@ -2255,6 +2250,7 @@ def to_feather(self, path: FilePathOrBuffer[AnyStr], **kwargs) -> None:
     @doc(
         Series.to_markdown,
         klass=_shared_doc_kwargs["klass"],
+        storage_options=_shared_docs["storage_options"],
         examples="""Examples
         --------
         >>> df = pd.DataFrame(
@@ -2307,6 +2303,7 @@ def to_markdown(
             handles.handle.writelines(result)
         return None
 
+    @doc(storage_options=generic._shared_docs["storage_options"])
     @deprecate_kwarg(old_arg_name="fname", new_arg_name="path")
     def to_parquet(
         self,
@@ -2340,12 +2337,12 @@ def to_parquet(
 
             Previously this was "fname"
 
-        engine : {'auto', 'pyarrow', 'fastparquet'}, default 'auto'
+        engine : {{'auto', 'pyarrow', 'fastparquet'}}, default 'auto'
             Parquet library to use. If 'auto', then the option
             ``io.parquet.engine`` is used. The default ``io.parquet.engine``
             behavior is to try 'pyarrow', falling back to 'fastparquet' if
             'pyarrow' is unavailable.
-        compression : {'snappy', 'gzip', 'brotli', None}, default 'snappy'
+        compression : {{'snappy', 'gzip', 'brotli', None}}, default 'snappy'
             Name of the compression to use. Use ``None`` for no compression.
         index : bool, default None
             If ``True``, include the dataframe's index(es) in the file output.
@@ -2365,13 +2362,7 @@ def to_parquet(
 
             .. versionadded:: 0.24.0
 
-        storage_options : dict, optional
-            Extra options that make sense for a particular storage connection, e.g.
-            host, port, username, password, etc., if using a URL that will
-            be parsed by ``fsspec``, e.g., starting "s3://", "gcs://". An error
-            will be raised if providing this argument with a local path or
-            a file-like buffer. See the fsspec and backend storage implementation
-            docs for the set of allowed keys and values.
+        {storage_options}
 
             .. versionadded:: 1.2.0
 
@@ -2398,7 +2389,7 @@ def to_parquet(
 
         Examples
         --------
-        >>> df = pd.DataFrame(data={'col1': [1, 2], 'col2': [3, 4]})
+        >>> df = pd.DataFrame(data={{'col1': [1, 2], 'col2': [3, 4]}})
         >>> df.to_parquet('df.parquet.gzip',
         ...               compression='gzip')  # doctest: +SKIP
         >>> pd.read_parquet('df.parquet.gzip')  # doctest: +SKIP