DOCS: fix docstring validation errors for pandas.Series pandas-dev#59595

Author: d-urbonas

ci/code_checks.sh

@@ -104,7 +104,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.Series.dt.tz_localize PR01,PR02" \
         -i "pandas.Series.dt.unit GL08" \
         -i "pandas.Series.pad PR01,SA01" \
-        -i "pandas.Series.sparse.fill_value SA01" \
         -i "pandas.Series.sparse.from_coo PR07,SA01" \
         -i "pandas.Series.sparse.npoints SA01" \
         -i "pandas.Series.sparse.sp_values SA01" \

pandas/core/arrays/sparse/array.py

@@ -623,6 +623,12 @@ def fill_value(self):
 
         For memory savings, this should be the most common value in the array.
 
+        See Also
+        --------
+        Series.sparse : Accessor for handling sparse data.
+        Series.sparse.npoints : The number of non- ``fill_value`` points.
+        Series.sparse.sp_values : An ndarray containing the non- ``fill_value`` values.
+
         Examples
         --------
         >>> ser = pd.Series([0, 0, 2, 2, 2], dtype="Sparse[int]")

pandas/core/strings/accessor.py

@@ -1363,6 +1363,14 @@ def match(self, pat: str, case: bool = True, flags: int = 0, na=None):
         """
         Determine if each string starts with a match of a regular expression.
 
+        This method checks if the start of each string in the Series or
+        Index matches the specified regular expression (Regex) pattern,
+        allowing for complex string matching rules.
+
+        Additionally, case sensitivity can be specified, Regex module flags can
+        be used to modify matching behavior, and a fill value for missing values
+        can be provided.
+
         Parameters
         ----------
         pat : str