diff --git a/examples/animation/pause_resume.py b/examples/animation/pause_resume.py
index 0a8c2f7c549a..7bed65140263 100644
--- a/examples/animation/pause_resume.py
+++ b/examples/animation/pause_resume.py
@@ -7,6 +7,14 @@
 
 - using the Animation.pause() method to pause an animation.
 - using the Animation.resume() method to resume an animation.
+
+.. note::
+    This example exercises the interactive capabilities of Matplotlib, and this
+    will not appear in the static documentation. Please run this code on your
+    machine to see the interactivity.
+
+    You can copy and paste individual parts, or download the entire example
+    using the link at the bottom of the page.
 """
 
 import matplotlib.pyplot as plt
diff --git a/examples/event_handling/close_event.py b/examples/event_handling/close_event.py
index 9566167bdc6c..24b45b74ea48 100644
--- a/examples/event_handling/close_event.py
+++ b/examples/event_handling/close_event.py
@@ -4,6 +4,14 @@
 ===========
 
 Example to show connecting events that occur when the figure closes.
+
+.. note::
+    This example exercises the interactive capabilities of Matplotlib, and this
+    will not appear in the static documentation. Please run this code on your
+    machine to see the interactivity.
+
+    You can copy and paste individual parts, or download the entire example
+    using the link at the bottom of the page.
 """
 import matplotlib.pyplot as plt
 
diff --git a/examples/event_handling/coords_demo.py b/examples/event_handling/coords_demo.py
index 171ec6317d2c..70b42ad4b1bd 100644
--- a/examples/event_handling/coords_demo.py
+++ b/examples/event_handling/coords_demo.py
@@ -5,6 +5,14 @@
 
 An example of how to interact with the plotting canvas by connecting to move
 and click events.
+
+.. note::
+    This example exercises the interactive capabilities of Matplotlib, and this
+    will not appear in the static documentation. Please run this code on your
+    machine to see the interactivity.
+
+    You can copy and paste individual parts, or download the entire example
+    using the link at the bottom of the page.
 """
 
 from matplotlib.backend_bases import MouseButton
diff --git a/examples/event_handling/data_browser.py b/examples/event_handling/data_browser.py
index 6d2c68a3741d..71c72d34854d 100644
--- a/examples/event_handling/data_browser.py
+++ b/examples/event_handling/data_browser.py
@@ -8,6 +8,14 @@
 This example covers how to interact data with multiple canvases. This
 let's you select and highlight a point on one axis, and generating the
 data of that point on the other axis.
+
+.. note::
+    This example exercises the interactive capabilities of Matplotlib, and this
+    will not appear in the static documentation. Please run this code on your
+    machine to see the interactivity.
+
+    You can copy and paste individual parts, or download the entire example
+    using the link at the bottom of the page.
 """
 import numpy as np
 
diff --git a/examples/event_handling/figure_axes_enter_leave.py b/examples/event_handling/figure_axes_enter_leave.py
index 8526346610f8..d55fb6e69d6a 100644
--- a/examples/event_handling/figure_axes_enter_leave.py
+++ b/examples/event_handling/figure_axes_enter_leave.py
@@ -5,6 +5,14 @@
 
 Illustrate the figure and Axes enter and leave events by changing the
 frame colors on enter and leave.
+
+.. note::
+    This example exercises the interactive capabilities of Matplotlib, and this
+    will not appear in the static documentation. Please run this code on your
+    machine to see the interactivity.
+
+    You can copy and paste individual parts, or download the entire example
+    using the link at the bottom of the page.
 """
 import matplotlib.pyplot as plt
 
diff --git a/examples/event_handling/ginput_manual_clabel_sgskip.py b/examples/event_handling/ginput_manual_clabel_sgskip.py
index 72140fddc142..00e548bfccb4 100644
--- a/examples/event_handling/ginput_manual_clabel_sgskip.py
+++ b/examples/event_handling/ginput_manual_clabel_sgskip.py
@@ -6,10 +6,13 @@
 This provides examples of uses of interactive functions, such as ginput,
 waitforbuttonpress and manual clabel placement.
 
-This script must be run interactively using a backend that has a
-graphical user interface (for example, using GTK3Agg backend, but not
-PS backend).
+.. note::
+    This example exercises the interactive capabilities of Matplotlib, and this
+    will not appear in the static documentation. Please run this code on your
+    machine to see the interactivity.
 
+    You can copy and paste individual parts, or download the entire example
+    using the link at the bottom of the page.
 """
 
 import time
diff --git a/examples/event_handling/image_slices_viewer.py b/examples/event_handling/image_slices_viewer.py
index 96cf8f64a3a0..6431d38ac541 100644
--- a/examples/event_handling/image_slices_viewer.py
+++ b/examples/event_handling/image_slices_viewer.py
@@ -4,6 +4,14 @@
 ===================
 
 Scroll through 2D image slices of a 3D array.
+
+.. note::
+    This example exercises the interactive capabilities of Matplotlib, and this
+    will not appear in the static documentation. Please run this code on your
+    machine to see the interactivity.
+
+    You can copy and paste individual parts, or download the entire example
+    using the link at the bottom of the page.
 """
 
 import numpy as np
diff --git a/examples/event_handling/keypress_demo.py b/examples/event_handling/keypress_demo.py
index 6aff3b617ca3..e71e7ad3dfc4 100644
--- a/examples/event_handling/keypress_demo.py
+++ b/examples/event_handling/keypress_demo.py
@@ -4,6 +4,14 @@
 ==============
 
 Show how to connect to keypress events.
+
+.. note::
+    This example exercises the interactive capabilities of Matplotlib, and this
+    will not appear in the static documentation. Please run this code on your
+    machine to see the interactivity.
+
+    You can copy and paste individual parts, or download the entire example
+    using the link at the bottom of the page.
 """
 import sys
 import numpy as np
diff --git a/examples/event_handling/lasso_demo.py b/examples/event_handling/lasso_demo.py
index b5f29b2fe3a6..de55537011d7 100644
--- a/examples/event_handling/lasso_demo.py
+++ b/examples/event_handling/lasso_demo.py
@@ -9,6 +9,14 @@
 
 This is currently a proof-of-concept implementation (though it is
 usable as is).  There will be some refinement of the API.
+
+.. note::
+    This example exercises the interactive capabilities of Matplotlib, and this
+    will not appear in the static documentation. Please run this code on your
+    machine to see the interactivity.
+
+    You can copy and paste individual parts, or download the entire example
+    using the link at the bottom of the page.
 """
 
 from matplotlib import colors as mcolors, path
diff --git a/examples/event_handling/legend_picking.py b/examples/event_handling/legend_picking.py
index 5f8a3d1bb779..8c050d472d7a 100644
--- a/examples/event_handling/legend_picking.py
+++ b/examples/event_handling/legend_picking.py
@@ -4,6 +4,14 @@
 ==============
 
 Enable picking on the legend to toggle the original line on and off
+
+.. note::
+    This example exercises the interactive capabilities of Matplotlib, and this
+    will not appear in the static documentation. Please run this code on your
+    machine to see the interactivity.
+
+    You can copy and paste individual parts, or download the entire example
+    using the link at the bottom of the page.
 """
 
 import numpy as np
diff --git a/examples/event_handling/looking_glass.py b/examples/event_handling/looking_glass.py
index 139afab106f3..70fe4651f79d 100644
--- a/examples/event_handling/looking_glass.py
+++ b/examples/event_handling/looking_glass.py
@@ -4,6 +4,14 @@
 =============
 
 Example using mouse events to simulate a looking glass for inspecting data.
+
+.. note::
+    This example exercises the interactive capabilities of Matplotlib, and this
+    will not appear in the static documentation. Please run this code on your
+    machine to see the interactivity.
+
+    You can copy and paste individual parts, or download the entire example
+    using the link at the bottom of the page.
 """
 import numpy as np
 import matplotlib.pyplot as plt
diff --git a/examples/event_handling/path_editor.py b/examples/event_handling/path_editor.py
index 9fe1a1470e64..be8d79935db9 100644
--- a/examples/event_handling/path_editor.py
+++ b/examples/event_handling/path_editor.py
@@ -7,6 +7,14 @@
 
 This example demonstrates a cross-GUI application using Matplotlib event
 handling to interact with and modify objects on the canvas.
+
+.. note::
+    This example exercises the interactive capabilities of Matplotlib, and this
+    will not appear in the static documentation. Please run this code on your
+    machine to see the interactivity.
+
+    You can copy and paste individual parts, or download the entire example
+    using the link at the bottom of the page.
 """
 
 import numpy as np
diff --git a/examples/event_handling/pick_event_demo.py b/examples/event_handling/pick_event_demo.py
index 84c635c27ca8..3b1b3662660d 100644
--- a/examples/event_handling/pick_event_demo.py
+++ b/examples/event_handling/pick_event_demo.py
@@ -3,7 +3,6 @@
 Pick Event Demo
 ===============
 
-
 You can enable picking by setting the "picker" property of an artist
 (for example, a matplotlib Line2D, Text, Patch, Polygon, AxesImage,
 etc...)
@@ -59,6 +58,14 @@ def pick_handler(event):
 the specified epsilon tolerance)
 
 The examples below illustrate each of these methods.
+
+.. note::
+    These examples exercises the interactive capabilities of Matplotlib, and
+    this will not appear in the static documentation. Please run this code on
+    your machine to see the interactivity.
+
+    You can copy and paste individual parts, or download the entire example
+    using the link at the bottom of the page.
 """
 
 import matplotlib.pyplot as plt
@@ -74,114 +81,125 @@ def pick_handler(event):
 np.random.seed(19680801)
 
 
-def pick_simple():
-    # simple picking, lines, rectangles and text
-    fig, (ax1, ax2) = plt.subplots(2, 1)
-    ax1.set_title('click on points, rectangles or text', picker=True)
-    ax1.set_ylabel('ylabel', picker=True, bbox=dict(facecolor='red'))
-    line, = ax1.plot(rand(100), 'o', picker=True, pickradius=5)
-
-    # pick the rectangle
-    ax2.bar(range(10), rand(10), picker=True)
-    for label in ax2.get_xticklabels():  # make the xtick labels pickable
-        label.set_picker(True)
-
-    def onpick1(event):
-        if isinstance(event.artist, Line2D):
-            thisline = event.artist
-            xdata = thisline.get_xdata()
-            ydata = thisline.get_ydata()
-            ind = event.ind
-            print('onpick1 line:', np.column_stack([xdata[ind], ydata[ind]]))
-        elif isinstance(event.artist, Rectangle):
-            patch = event.artist
-            print('onpick1 patch:', patch.get_path())
-        elif isinstance(event.artist, Text):
-            text = event.artist
-            print('onpick1 text:', text.get_text())
-
-    fig.canvas.mpl_connect('pick_event', onpick1)
-
-
-def pick_custom_hit():
-    # picking with a custom hit test function
-    # you can define custom pickers by setting picker to a callable
-    # function.  The function has the signature
-    #
-    #  hit, props = func(artist, mouseevent)
-    #
-    # to determine the hit test.  if the mouse event is over the artist,
-    # return hit=True and props is a dictionary of
-    # properties you want added to the PickEvent attributes
-
-    def line_picker(line, mouseevent):
-        """
-        Find the points within a certain distance from the mouseclick in
-        data coords and attach some extra attributes, pickx and picky
-        which are the data points that were picked.
-        """
-        if mouseevent.xdata is None:
-            return False, dict()
-        xdata = line.get_xdata()
-        ydata = line.get_ydata()
-        maxd = 0.05
-        d = np.sqrt(
-            (xdata - mouseevent.xdata)**2 + (ydata - mouseevent.ydata)**2)
-
-        ind, = np.nonzero(d <= maxd)
-        if len(ind):
-            pickx = xdata[ind]
-            picky = ydata[ind]
-            props = dict(ind=ind, pickx=pickx, picky=picky)
-            return True, props
-        else:
-            return False, dict()
-
-    def onpick2(event):
-        print('onpick2 line:', event.pickx, event.picky)
-
-    fig, ax = plt.subplots()
-    ax.set_title('custom picker for line data')
-    line, = ax.plot(rand(100), rand(100), 'o', picker=line_picker)
-    fig.canvas.mpl_connect('pick_event', onpick2)
-
-
-def pick_scatter_plot():
-    # picking on a scatter plot (matplotlib.collections.RegularPolyCollection)
-
-    x, y, c, s = rand(4, 100)
-
-    def onpick3(event):
+#############################################################################
+# Simple picking, lines, rectangles and text
+# ------------------------------------------
+
+fig, (ax1, ax2) = plt.subplots(2, 1)
+ax1.set_title('click on points, rectangles or text', picker=True)
+ax1.set_ylabel('ylabel', picker=True, bbox=dict(facecolor='red'))
+line, = ax1.plot(rand(100), 'o', picker=True, pickradius=5)
+
+# Pick the rectangle.
+ax2.bar(range(10), rand(10), picker=True)
+for label in ax2.get_xticklabels():  # Make the xtick labels pickable.
+    label.set_picker(True)
+
+
+def onpick1(event):
+    if isinstance(event.artist, Line2D):
+        thisline = event.artist
+        xdata = thisline.get_xdata()
+        ydata = thisline.get_ydata()
         ind = event.ind
-        print('onpick3 scatter:', ind, x[ind], y[ind])
-
-    fig, ax = plt.subplots()
-    ax.scatter(x, y, 100*s, c, picker=True)
-    fig.canvas.mpl_connect('pick_event', onpick3)
-
-
-def pick_image():
-    # picking images (matplotlib.image.AxesImage)
-    fig, ax = plt.subplots()
-    ax.imshow(rand(10, 5), extent=(1, 2, 1, 2), picker=True)
-    ax.imshow(rand(5, 10), extent=(3, 4, 1, 2), picker=True)
-    ax.imshow(rand(20, 25), extent=(1, 2, 3, 4), picker=True)
-    ax.imshow(rand(30, 12), extent=(3, 4, 3, 4), picker=True)
-    ax.set(xlim=(0, 5), ylim=(0, 5))
-
-    def onpick4(event):
-        artist = event.artist
-        if isinstance(artist, AxesImage):
-            im = artist
-            A = im.get_array()
-            print('onpick4 image', A.shape)
-
-    fig.canvas.mpl_connect('pick_event', onpick4)
-
-
-if __name__ == '__main__':
-    pick_simple()
-    pick_custom_hit()
-    pick_scatter_plot()
-    pick_image()
-    plt.show()
+        print('onpick1 line:', np.column_stack([xdata[ind], ydata[ind]]))
+    elif isinstance(event.artist, Rectangle):
+        patch = event.artist
+        print('onpick1 patch:', patch.get_path())
+    elif isinstance(event.artist, Text):
+        text = event.artist
+        print('onpick1 text:', text.get_text())
+
+
+fig.canvas.mpl_connect('pick_event', onpick1)
+
+
+#############################################################################
+# Picking with a custom hit test function
+# ---------------------------------------
+# You can define custom pickers by setting picker to a callable function. The
+# function has the signature::
+#
+#  hit, props = func(artist, mouseevent)
+#
+# to determine the hit test. If the mouse event is over the artist, return
+# ``hit=True`` and ``props`` is a dictionary of properties you want added to
+# the `.PickEvent` attributes.
+
+def line_picker(line, mouseevent):
+    """
+    Find the points within a certain distance from the mouseclick in
+    data coords and attach some extra attributes, pickx and picky
+    which are the data points that were picked.
+    """
+    if mouseevent.xdata is None:
+        return False, dict()
+    xdata = line.get_xdata()
+    ydata = line.get_ydata()
+    maxd = 0.05
+    d = np.sqrt(
+        (xdata - mouseevent.xdata)**2 + (ydata - mouseevent.ydata)**2)
+
+    ind, = np.nonzero(d <= maxd)
+    if len(ind):
+        pickx = xdata[ind]
+        picky = ydata[ind]
+        props = dict(ind=ind, pickx=pickx, picky=picky)
+        return True, props
+    else:
+        return False, dict()
+
+
+def onpick2(event):
+    print('onpick2 line:', event.pickx, event.picky)
+
+
+fig, ax = plt.subplots()
+ax.set_title('custom picker for line data')
+line, = ax.plot(rand(100), rand(100), 'o', picker=line_picker)
+fig.canvas.mpl_connect('pick_event', onpick2)
+
+
+#############################################################################
+# Picking on a scatter plot
+# -------------------------
+# A scatter plot is backed by a `~matplotlib.collections.PathCollection`.
+
+x, y, c, s = rand(4, 100)
+
+
+def onpick3(event):
+    ind = event.ind
+    print('onpick3 scatter:', ind, x[ind], y[ind])
+
+
+fig, ax = plt.subplots()
+ax.scatter(x, y, 100*s, c, picker=True)
+fig.canvas.mpl_connect('pick_event', onpick3)
+
+
+#############################################################################
+# Picking images
+# --------------
+# Images plotted using `.Axes.imshow` are `~matplotlib.image.AxesImage`
+# objects.
+
+fig, ax = plt.subplots()
+ax.imshow(rand(10, 5), extent=(1, 2, 1, 2), picker=True)
+ax.imshow(rand(5, 10), extent=(3, 4, 1, 2), picker=True)
+ax.imshow(rand(20, 25), extent=(1, 2, 3, 4), picker=True)
+ax.imshow(rand(30, 12), extent=(3, 4, 3, 4), picker=True)
+ax.set(xlim=(0, 5), ylim=(0, 5))
+
+
+def onpick4(event):
+    artist = event.artist
+    if isinstance(artist, AxesImage):
+        im = artist
+        A = im.get_array()
+        print('onpick4 image', A.shape)
+
+
+fig.canvas.mpl_connect('pick_event', onpick4)
+
+plt.show()
diff --git a/examples/event_handling/pick_event_demo2.py b/examples/event_handling/pick_event_demo2.py
index 162fbdf65ade..93b7a6c92287 100644
--- a/examples/event_handling/pick_event_demo2.py
+++ b/examples/event_handling/pick_event_demo2.py
@@ -6,6 +6,14 @@
 Compute the mean (mu) and standard deviation (sigma) of 100 data sets and plot
 mu vs. sigma.  When you click on one of the (mu, sigma) points, plot the raw
 data from the dataset that generated this point.
+
+.. note::
+    This example exercises the interactive capabilities of Matplotlib, and this
+    will not appear in the static documentation. Please run this code on your
+    machine to see the interactivity.
+
+    You can copy and paste individual parts, or download the entire example
+    using the link at the bottom of the page.
 """
 import numpy as np
 import matplotlib.pyplot as plt
diff --git a/examples/event_handling/poly_editor.py b/examples/event_handling/poly_editor.py
index 2d7051685f43..b156b9c662bd 100644
--- a/examples/event_handling/poly_editor.py
+++ b/examples/event_handling/poly_editor.py
@@ -5,6 +5,14 @@
 
 This is an example to show how to build cross-GUI applications using
 Matplotlib event handling to interact with objects on the canvas.
+
+.. note::
+    This example exercises the interactive capabilities of Matplotlib, and this
+    will not appear in the static documentation. Please run this code on your
+    machine to see the interactivity.
+
+    You can copy and paste individual parts, or download the entire example
+    using the link at the bottom of the page.
 """
 import numpy as np
 from matplotlib.lines import Line2D
diff --git a/examples/event_handling/pong_sgskip.py b/examples/event_handling/pong_sgskip.py
index 74e15aa9c369..53fe957225f6 100644
--- a/examples/event_handling/pong_sgskip.py
+++ b/examples/event_handling/pong_sgskip.py
@@ -5,6 +5,14 @@
 
 A Matplotlib based game of Pong illustrating one way to write interactive
 animations that are easily ported to multiple backends.
+
+.. note::
+    This example exercises the interactive capabilities of Matplotlib, and this
+    will not appear in the static documentation. Please run this code on your
+    machine to see the interactivity.
+
+    You can copy and paste individual parts, or download the entire example
+    using the link at the bottom of the page.
 """
 
 import time
diff --git a/examples/event_handling/resample.py b/examples/event_handling/resample.py
index 542e84f13c71..30d61debbbf9 100644
--- a/examples/event_handling/resample.py
+++ b/examples/event_handling/resample.py
@@ -6,6 +6,14 @@
 Downsampling lowers the sample rate or sample size of a signal. In
 this tutorial, the signal is downsampled when the plot is adjusted
 through dragging and zooming.
+
+.. note::
+    This example exercises the interactive capabilities of Matplotlib, and this
+    will not appear in the static documentation. Please run this code on your
+    machine to see the interactivity.
+
+    You can copy and paste individual parts, or download the entire example
+    using the link at the bottom of the page.
 """
 
 import numpy as np
diff --git a/examples/event_handling/timers.py b/examples/event_handling/timers.py
index ac064b261bcb..43330097cf87 100644
--- a/examples/event_handling/timers.py
+++ b/examples/event_handling/timers.py
@@ -5,6 +5,14 @@
 
 Simple example of using general timer objects. This is used to update
 the time placed in the title of the figure.
+
+.. note::
+    This example exercises the interactive capabilities of Matplotlib, and this
+    will not appear in the static documentation. Please run this code on your
+    machine to see the interactivity.
+
+    You can copy and paste individual parts, or download the entire example
+    using the link at the bottom of the page.
 """
 import matplotlib.pyplot as plt
 import numpy as np
diff --git a/examples/event_handling/trifinder_event_demo.py b/examples/event_handling/trifinder_event_demo.py
index 6678003ab189..991c5c9a3a82 100644
--- a/examples/event_handling/trifinder_event_demo.py
+++ b/examples/event_handling/trifinder_event_demo.py
@@ -6,6 +6,14 @@
 Example showing the use of a TriFinder object.  As the mouse is moved over the
 triangulation, the triangle under the cursor is highlighted and the index of
 the triangle is displayed in the plot title.
+
+.. note::
+    This example exercises the interactive capabilities of Matplotlib, and this
+    will not appear in the static documentation. Please run this code on your
+    machine to see the interactivity.
+
+    You can copy and paste individual parts, or download the entire example
+    using the link at the bottom of the page.
 """
 import matplotlib.pyplot as plt
 from matplotlib.tri import Triangulation
diff --git a/examples/event_handling/viewlims.py b/examples/event_handling/viewlims.py
index d6bdf99787d3..134419300a68 100644
--- a/examples/event_handling/viewlims.py
+++ b/examples/event_handling/viewlims.py
@@ -5,6 +5,14 @@
 
 Creates two identical panels.  Zooming in on the right panel will show
 a rectangle in the first panel, denoting the zoomed region.
+
+.. note::
+    This example exercises the interactive capabilities of Matplotlib, and this
+    will not appear in the static documentation. Please run this code on your
+    machine to see the interactivity.
+
+    You can copy and paste individual parts, or download the entire example
+    using the link at the bottom of the page.
 """
 import numpy as np
 import matplotlib.pyplot as plt
diff --git a/examples/event_handling/zoom_window.py b/examples/event_handling/zoom_window.py
index 9afe60ce935c..c10cd820aa47 100644
--- a/examples/event_handling/zoom_window.py
+++ b/examples/event_handling/zoom_window.py
@@ -12,6 +12,14 @@
 
 Note the diameter of the circles in the scatter are defined in points**2, so
 their size is independent of the zoom.
+
+.. note::
+    This example exercises the interactive capabilities of Matplotlib, and this
+    will not appear in the static documentation. Please run this code on your
+    machine to see the interactivity.
+
+    You can copy and paste individual parts, or download the entire example
+    using the link at the bottom of the page.
 """
 
 import matplotlib.pyplot as plt
@@ -21,8 +29,8 @@
 # Fixing random state for reproducibility
 np.random.seed(19680801)
 
-figsrc, axsrc = plt.subplots()
-figzoom, axzoom = plt.subplots()
+figsrc, axsrc = plt.subplots(figsize=(3.7, 3.7))
+figzoom, axzoom = plt.subplots(figsize=(3.7, 3.7))
 axsrc.set(xlim=(0, 1), ylim=(0, 1), autoscale_on=False,
           title='Click to zoom')
 axzoom.set(xlim=(0.45, 0.55), ylim=(0.4, 0.6), autoscale_on=False,