diff --git a/ci/code_checks.sh b/ci/code_checks.sh
index 66f6bfd7195f9..d9d603f73f2dd 100755
--- a/ci/code_checks.sh
+++ b/ci/code_checks.sh
@@ -108,11 +108,7 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.DataFrame.reorder_levels SA01" \
         -i "pandas.DataFrame.sem PR01,RT03,SA01" \
         -i "pandas.DataFrame.skew RT03,SA01" \
-        -i "pandas.DataFrame.sparse PR01,SA01" \
-        -i "pandas.DataFrame.sparse.density SA01" \
-        -i "pandas.DataFrame.sparse.from_spmatrix SA01" \
-        -i "pandas.DataFrame.sparse.to_coo SA01" \
-        -i "pandas.DataFrame.sparse.to_dense SA01" \
+        -i "pandas.DataFrame.sparse PR01" \
         -i "pandas.DataFrame.std PR01,RT03,SA01" \
         -i "pandas.DataFrame.sum RT03" \
         -i "pandas.DataFrame.swaplevel SA01" \
diff --git a/pandas/core/arrays/sparse/accessor.py b/pandas/core/arrays/sparse/accessor.py
index 58199701647d1..1f82285e3e40e 100644
--- a/pandas/core/arrays/sparse/accessor.py
+++ b/pandas/core/arrays/sparse/accessor.py
@@ -243,6 +243,10 @@ class SparseFrameAccessor(BaseAccessor, PandasDelegate):
     """
     DataFrame accessor for sparse data.
 
+    See Also
+    --------
+    DataFrame.sparse.density : Ratio of non-sparse points to total (dense) data points.
+
     Examples
     --------
     >>> df = pd.DataFrame({"a": [1, 2, 0, 0], "b": [3, 0, 0, 4]}, dtype="Sparse[int]")
@@ -274,6 +278,11 @@ def from_spmatrix(cls, data, index=None, columns=None) -> DataFrame:
             Each column of the DataFrame is stored as a
             :class:`arrays.SparseArray`.
 
+        See Also
+        --------
+        DataFrame.sparse.to_coo : Return the contents of the frame as a
+            sparse SciPy COO matrix.
+
         Examples
         --------
         >>> import scipy.sparse
@@ -319,6 +328,11 @@ def to_dense(self) -> DataFrame:
         DataFrame
             A DataFrame with the same values stored as dense arrays.
 
+        See Also
+        --------
+        DataFrame.sparse.density : Ratio of non-sparse points to total
+            (dense) data points.
+
         Examples
         --------
         >>> df = pd.DataFrame({"A": pd.arrays.SparseArray([0, 1, 0])})
@@ -343,6 +357,10 @@ def to_coo(self) -> spmatrix:
             If the caller is heterogeneous and contains booleans or objects,
             the result will be of dtype=object. See Notes.
 
+        See Also
+        --------
+        DataFrame.sparse.to_dense : Convert a DataFrame with sparse values to dense.
+
         Notes
         -----
         The dtype will be the lowest-common-denominator type (implicit
@@ -388,6 +406,11 @@ def density(self) -> float:
         """
         Ratio of non-sparse points to total (dense) data points.
 
+        See Also
+        --------
+        DataFrame.sparse.from_spmatrix : Create a new DataFrame from a
+            scipy sparse matrix.
+
         Examples
         --------
         >>> df = pd.DataFrame({"A": pd.arrays.SparseArray([0, 1, 0, 1])})