diff --git a/galleries/examples/ticks/colorbar_tick_labelling_demo.py b/galleries/examples/ticks/colorbar_tick_labelling_demo.py
index 56294c6abbb3..8a1e5b28043d 100644
--- a/galleries/examples/ticks/colorbar_tick_labelling_demo.py
+++ b/galleries/examples/ticks/colorbar_tick_labelling_demo.py
@@ -3,45 +3,62 @@
 Colorbar Tick Labelling
 =======================
 
-Produce custom labelling for a colorbar.
-
-Contributed by Scott Sinclair
+Vertical colorbars have ticks, tick labels, and labels visible on the *y* axis,
+horizontal colorbars on the *x* axis. The ``ticks`` parameter can be used to
+set the ticks and the ``format`` parameter can be used to format the tick labels
+of the visible colorbar axes. For further adjustments, the ``yaxis`` or
+``xaxis`` axes of the colorbar can be retrieved using its ``ax`` property.
 """
-
 import matplotlib.pyplot as plt
 import numpy as np
-from numpy.random import randn
 
-from matplotlib import cm
+import matplotlib.ticker as mticker
 
 # Fixing random state for reproducibility
-np.random.seed(19680801)
+rng = np.random.default_rng(seed=19680801)
 
 # %%
 # Make plot with vertical (default) colorbar
 
 fig, ax = plt.subplots()
 
-data = np.clip(randn(250, 250), -1, 1)
+data = rng.standard_normal((250, 250))
 
-cax = ax.imshow(data, cmap=cm.coolwarm)
+cax = ax.imshow(data, vmin=-1, vmax=1, cmap='coolwarm')
 ax.set_title('Gaussian noise with vertical colorbar')
 
 # Add colorbar, make sure to specify tick locations to match desired ticklabels
-cbar = fig.colorbar(cax, ticks=[-1, 0, 1])
-cbar.ax.set_yticklabels(['< -1', '0', '> 1'])  # vertically oriented colorbar
+cbar = fig.colorbar(cax,
+                    ticks=[-1, 0, 1],
+                    format=mticker.FixedFormatter(['< -1', '0', '> 1']),
+                    extend='both'
+                    )
+labels = cbar.ax.get_yticklabels()
+labels[0].set_verticalalignment('top')
+labels[-1].set_verticalalignment('bottom')
 
 # %%
 # Make plot with horizontal colorbar
 
 fig, ax = plt.subplots()
 
-data = np.clip(randn(250, 250), -1, 1)
+data = np.clip(data, -1, 1)
 
-cax = ax.imshow(data, cmap=cm.afmhot)
+cax = ax.imshow(data, cmap='afmhot')
 ax.set_title('Gaussian noise with horizontal colorbar')
 
-cbar = fig.colorbar(cax, ticks=[-1, 0, 1], orientation='horizontal')
-cbar.ax.set_xticklabels(['Low', 'Medium', 'High'])  # horizontal colorbar
+# Add colorbar and adjust ticks afterwards
+cbar = fig.colorbar(cax, orientation='horizontal')
+cbar.set_ticks(ticks=[-1, 0, 1], labels=['Low', 'Medium', 'High'])
 
 plt.show()
+
+# %%
+#
+# .. admonition:: References
+#
+#    The use of the following functions, methods, classes and modules is shown
+#    in this example:
+#
+#    - `matplotlib.colorbar.Colorbar.set_ticks`
+#    - `matplotlib.figure.Figure.colorbar` / `matplotlib.pyplot.colorbar`