DOC: fix SA01, ES01 for pandas.Series.sparse.sp_values

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

@@ -603,6 +603,18 @@ def sp_values(self) -> np.ndarray:
         """
         An ndarray containing the non- ``fill_value`` values.
 
+        This property returns the actual data values stored in the sparse
+        representation, excluding the values that are equal to the ``fill_value``.
+        The result is an ndarray of the underlying values, preserving the sparse
+        structure by omitting the default ``fill_value`` entries.
+
+        See Also
+        --------
+        Series.sparse.to_dense : Convert a Series from sparse values to dense.
+        Series.sparse.fill_value : Elements in `data` that are `fill_value` are
+            not stored.
+        Series.sparse.density : The percent of non- ``fill_value`` points, as decimal.
+
         Examples
         --------
         >>> from pandas.arrays import SparseArray