diff --git a/examples/api/two_scales.py b/examples/api/two_scales.py
index a22f64bbbdc4..45b5fea722a6 100644
--- a/examples/api/two_scales.py
+++ b/examples/api/two_scales.py
@@ -3,21 +3,16 @@
 Plots with different scales
 ===========================
 
-Demonstrate how to do two plots on the same axes with different left
+Demonstrate how to do two plots on the same axes with different left and
 right scales.
 
+The trick is to use *two different axes* that share the same *x* axis.
+You can use separate `matplotlib.ticker` formatters and locators as
+desired since the two axes are independent.
 
-The trick is to use *2 different axes*.  Turn the axes rectangular
-frame off on the 2nd axes to keep it from obscuring the first.
-Manually set the tick locs and labels as desired.  You can use
-separate matplotlib.ticker formatters and locators as desired since
-the two axes are independent.
-
-This is achieved in the following example by calling the Axes.twinx()
-method, which performs this work. See the source of twinx() in
-axes.py for an example of how to do it for different x scales. (Hint:
-use the xaxis instance and call tick_bottom and tick_top in place of
-tick_left and tick_right.)
+Such axes are generated by calling the `Axes.twinx` method.  Likewise,
+`Axes.twiny` is available to generate axes that share a *y* axis but
+have different top and bottom scales.
 
 The twinx and twiny methods are also exposed as pyplot functions.
 
@@ -31,16 +26,15 @@
 s1 = np.exp(t)
 ax1.plot(t, s1, 'b-')
 ax1.set_xlabel('time (s)')
-# Make the y-axis label and tick labels match the line color.
+# Make the y-axis label, ticks and tick labels match the line color.
 ax1.set_ylabel('exp', color='b')
-for tl in ax1.get_yticklabels():
-    tl.set_color('b')
-
+ax1.tick_params('y', colors='b')
 
 ax2 = ax1.twinx()
-s2 = np.sin(2*np.pi*t)
+s2 = np.sin(2 * np.pi * t)
 ax2.plot(t, s2, 'r.')
 ax2.set_ylabel('sin', color='r')
-for tl in ax2.get_yticklabels():
-    tl.set_color('r')
+ax2.tick_params('y', colors='r')
+
+fig.tight_layout()
 plt.show()