diff --git a/examples/ticks_and_spines/auto_ticks.py b/examples/ticks_and_spines/auto_ticks.py
new file mode 100644
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+++ b/examples/ticks_and_spines/auto_ticks.py
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+"""
+=================================
+Automatically setting tick labels
+=================================
+
+Setting the behavior of tick auto-placement.
+
+If you don't explicitly set tick positions / labels, Matplotlib will attempt
+to choose them both automatically based on the displayed data and its limits.
+
+By default, this attempts to choose tick positions that are distributed
+along the axis:
+"""
+import matplotlib.pyplot as plt
+import numpy as np
+np.random.seed(19680801)
+
+fig, ax = plt.subplots()
+dots = np.arange(10) / 100. + .03
+x, y = np.meshgrid(dots, dots)
+data = [x.ravel(), y.ravel()]
+ax.scatter(*data, c=data[1])
+
+################################################################################
+# Sometimes choosing evenly-distributed ticks results in strange tick numbers.
+# If you'd like Matplotlib to keep ticks located at round numbers, you can
+# change this behavior with the following rcParams value:
+
+print(plt.rcParams['axes.autolimit_mode'])
+
+# Now change this value and see the results
+with plt.rc_context({'axes.autolimit_mode': 'round_numbers'}):
+    fig, ax = plt.subplots()
+    ax.scatter(*data, c=data[1])
+
+################################################################################
+# You can also alter the margins of the axes around the data by
+# with ``axes.(x,y)margin``:
+
+with plt.rc_context({'axes.autolimit_mode': 'round_numbers',
+                     'axes.xmargin': .8,
+                     'axes.ymargin': .8}):
+    fig, ax = plt.subplots()
+    ax.scatter(*data, c=data[1])
+
+plt.show()