diff --git a/dev/_sources/auto_examples/inspection/plot_permutation_importance.rst.txt b/dev/_sources/auto_examples/inspection/plot_permutation_importance.rst.txt
index 46001bf1492c8..82b6d6dd5e3d9 100644
--- a/dev/_sources/auto_examples/inspection/plot_permutation_importance.rst.txt
+++ b/dev/_sources/auto_examples/inspection/plot_permutation_importance.rst.txt
@@ -48,6 +48,7 @@ can mitigate those limitations.
 
     print(__doc__)
     import matplotlib.pyplot as plt
+    import matplotlib.ticker as mticker
     import numpy as np
 
     from sklearn.datasets import fetch_openml
@@ -222,6 +223,7 @@ importances:
     y_ticks = np.arange(0, len(feature_names))
     fig, ax = plt.subplots()
     ax.barh(y_ticks, tree_feature_importances[sorted_idx])
+    ax.yaxis.set_major_locator(mticker.FixedLocator(feature_names[sorted_idx]))
     ax.set_yticklabels(feature_names[sorted_idx])
     ax.set_yticks(y_ticks)
     ax.set_title("Random Forest Feature Importances (MDI)")