diff --git a/examples/cluster/plot_dbscan.py b/examples/cluster/plot_dbscan.py
index f4293941569ce..620ee6bdcb86e 100644
--- a/examples/cluster/plot_dbscan.py
+++ b/examples/cluster/plot_dbscan.py
@@ -16,8 +16,9 @@
 from sklearn.preprocessing import StandardScaler
 
 
-# #############################################################################
+# %%
 # Generate sample data
+# --------------------
 centers = [[1, 1], [-1, -1], [1, -1]]
 X, labels_true = make_blobs(
     n_samples=750, centers=centers, cluster_std=0.4, random_state=0
@@ -25,8 +26,9 @@
 
 X = StandardScaler().fit_transform(X)
 
-# #############################################################################
+# %%
 # Compute DBSCAN
+# --------------
 db = DBSCAN(eps=0.3, min_samples=10).fit(X)
 core_samples_mask = np.zeros_like(db.labels_, dtype=bool)
 core_samples_mask[db.core_sample_indices_] = True
@@ -48,8 +50,9 @@
 )
 print("Silhouette Coefficient: %0.3f" % metrics.silhouette_score(X, labels))
 
-# #############################################################################
+# %%
 # Plot result
+# -----------
 import matplotlib.pyplot as plt
 
 # Black removed and is used for noise instead.