Fix Docstring Issues for pandas.Series.sparse.sp_values and pandas.Series.str.match (Issue #59592)

ci/code_checks.sh

@@ -100,7 +100,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -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" \
         -i "pandas.Timedelta.max PR02" \
         -i "pandas.Timedelta.min PR02" \
         -i "pandas.Timedelta.resolution PR02" \

pandas/core/arrays/sparse/array.py

@@ -601,7 +601,22 @@ def sp_index(self) -> SparseIndex:
     @property
     def sp_values(self) -> np.ndarray:
         """
-        An ndarray containing the non- ``fill_value`` values.
+        An ndarray containing the non-``fill_value`` values.
+
+        This method retrieves the non-fill values from a SparseArray. SparseArrays
+        are designed to efficiently store large arrays of data where most of the
+        elements are the same (the fill value). This method allows you to access
+        the actual data points that differ from the fill value.
+
+        Returns
+        -------
+        ndarray
+            An array containing the non-fill values.
+
+        See Also
+        --------
+        Series.sparse.fill_value : The fill value for the SparseArray.
+        arrays.SparseArray : Represents an array with sparse data.
 
         Examples
         --------
@@ -610,6 +625,7 @@ def sp_values(self) -> np.ndarray:
         >>> s.sp_values
         array([1, 2])
         """
+
         return self._sparse_values
 
     @property

pandas/core/strings/accessor.py

@@ -1366,6 +1366,10 @@ 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 each string in the Series starts with a substring
+        that matches the given regular expression pattern. It returns a boolean
+        Series indicating whether each string meets the condition.
+
         Parameters
         ----------
         pat : str
@@ -1402,6 +1406,7 @@ def match(self, pat: str, case: bool = True, flags: int = 0, na=None):
         2   False
         dtype: bool
         """
+
         result = self._data.array._str_match(pat, case=case, flags=flags, na=na)
         return self._wrap_result(result, fill_value=na, returns_string=False)