matplotlib
diff --git a/‎examples/pylab_examples/hist2d_demo.py
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diff --git a/‎examples/pylab_examples/hist_colormapped.py
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diff --git a/‎examples/pylab_examples/histogram_percent_demo.py
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diff --git a/‎examples/statistics/plot_hist.py
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diff --git a/‎examples/tests/backend_driver.py
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diff --git a/‎lib/matplotlib/axes/_axes.py
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@@ -0,0 +1,101 @@
+"""
+==========
+Histograms
+==========
+
+Demonstrates how to plot histograms with matplotlib.
+"""
+
+import matplotlib.pyplot as plt
+import numpy as np
+from matplotlib import colors
+from matplotlib.ticker import PercentFormatter
+
+# Fixing random state for reproducibility
+np.random.seed(19680801)
+
+
+###############################################################################
+# Generate data and plot a simple histogram
+# -----------------------------------------
+#
+# To generate a 1D histogram we only need a single vector of numbers. For a 2D
+# histogram we'll need a second vector. We'll generate both below, and show
+# the histogram for each vector
+
+N_points = 100000
+n_bins = 20
+
+# Generate a normal distribution, center at x=0 and y=5
+x = np.random.randn(N_points)
+y = .4 * x + np.random.randn(100000) + 5
+
+fig, axs = plt.subplots(1, 2, sharey=True, tight_layout=True)
+
+# We can set the number of bins with the `bins` kwarg
+axs[0].hist(x, bins=n_bins)
+axs[1].hist(y, bins=n_bins)
+
+
+###############################################################################
+# Updating histogram colors
+# -------------------------
+#
+# The histogram method returns (among other things) a `patches` object. This
+# gives us access to the properties of the objects drawn. Using this, we can
+# edit the histogram to our liking. Let's change the color of each bar
+# based on its y value
+
+fig, axs = plt.subplots(1, 2, figsize=(10, 5), tight_layout=True)
+
+# N is the count in each bin, bins is the lower-limit of the bin
+N, bins, patches = axs[0].hist(x, bins=n_bins)
+
+# We'll color code by height, but you could use any scalar
+fracs = N.astype(float) / N.max()
+
+# we need to normalize the data to 0..1 for the full range of the colormap
+norm = colors.Normalize(fracs.min(), fracs.max())
+
+# Now, we'll loop through our objects and set the color of each accordingly
+for thisfrac, thispatch in zip(fracs, patches):
+    color = plt.cm.viridis(norm(thisfrac))
+    thispatch.set_facecolor(color)
+
+# We can also normalize our inputs by the total number of counts.
+axs[1].hist(x, bins=n_bins, normed=True)
+
+# Now we format the y-axis to display percentage
+axs[1].yaxis.set_major_formatter(PercentFormatter(xmax=1))
+
+
+###############################################################################
+# Plot a 2D histogram
+# -------------------
+#
+# To plot a 2D histogram, one only needs two vectors of the same length,
+# corresponding to each axis of the histogram.
+
+fig, ax = plt.subplots(tight_layout=True)
+hist = ax.hist2d(x, y)
+
+###############################################################################
+# Customizing your histogram
+# --------------------------
+#
+# Customizing a 2D histogram is similar to the 1D case, you can control
+# visual components such as the bin size or color normalization
+
+fig, axs = plt.subplots(1, 3, figsize=(15, 5), sharex=True, sharey=True,
+                        tight_layout=True)
+
+# We can increase the number of bins on each axis
+axs[0].hist2d(x, y, bins=40)
+
+# As well as define normalization of the colors
+axs[1].hist2d(x, y, bins=40, norm=colors.LogNorm())
+
+# We can also define custom numbers of bins for each axis
+axs[2].hist2d(x, y, bins=(80, 10), norm=colors.LogNorm())
+
+plt.show()
@@ -173,7 +173,6 @@
     'hatch_demo.py',
     'hexbin_demo.py',
     'hexbin_demo2.py',
-    'hist_colormapped.py',
     'vline_hline_demo.py',
 
     'image_clip_path.py',
 
@@ -6499,7 +6499,7 @@ def hist2d(self, x, y, bins=10, range=None, normed=False, weights=None,
 
         Examples
         --------
-        .. plot:: mpl_examples/pylab_examples/hist2d_demo.py
+        .. plot:: mpl_examples/statistics/plot_hist.py
         """
 
         # xrange becomes range after 2to3