diff --git a/doc/_static/mpl.css b/doc/_static/mpl.css
index d7bc46446c7f..1c75454512bf 100644
--- a/doc/_static/mpl.css
+++ b/doc/_static/mpl.css
@@ -19,7 +19,7 @@ body {
 }
 
 a {
-    color: #CA7900;
+    color: #CA7900 !important;
     text-decoration: none;
 }
 
diff --git a/doc/conf.py b/doc/conf.py
index 57ea9e99357d..5e5dba666a17 100644
--- a/doc/conf.py
+++ b/doc/conf.py
@@ -29,7 +29,7 @@
 extensions = ['matplotlib.sphinxext.mathmpl', 'sphinxext.math_symbol_table',
               'sphinx.ext.autodoc', 'matplotlib.sphinxext.only_directives',
               'sphinx.ext.doctest', 'sphinx.ext.autosummary',
-              'sphinx.ext.inheritance_diagram',
+              'sphinx.ext.inheritance_diagram', 'sphinx.ext.intersphinx',
               'sphinx_gallery.gen_gallery',
               'matplotlib.sphinxext.plot_directive',
               'sphinxext.github',
@@ -88,6 +88,13 @@ def _check_deps():
 
 autodoc_docstring_signature = True
 
+intersphinx_mapping = {
+  'python': ('https://docs.python.org/', None),
+  'numpy': ('https://docs.scipy.org/doc/numpy/', None),
+  'scipy': ('https://docs.scipy.org/doc/scipy/reference/', None),
+  'pandas': ('http://pandas.pydata.org/pandas-docs/stable', None)
+  }
+
 
 # Sphinx gallery configuration
 sphinx_gallery_conf = {
diff --git a/examples/misc/keyword_plotting.py b/examples/misc/keyword_plotting.py
new file mode 100644
index 000000000000..c7aa93e0f7b8
--- /dev/null
+++ b/examples/misc/keyword_plotting.py
@@ -0,0 +1,28 @@
+"""
+======================
+Plotting with keywords
+======================
+
+There are some instances where you have data in a format that lets you
+access particular variables with strings. For example, with
+:class:`numpy.recarray` or :class:`pandas.DataFrame`.
+
+Matplotlib allows you provide such an object with the ``data`` keyword
+argument. If provided, then you may generate plots with the strings
+corresponding to these variables.
+"""
+
+import numpy as np
+import matplotlib.pyplot as plt
+np.random.seed(19680801)
+
+data = {'a': np.arange(50),
+        'c': np.random.randint(0, 50, 50),
+        'd': np.random.randn(50)}
+data['b'] = data['a'] + 10 * np.random.randn(50)
+data['d'] = np.abs(data['d']) * 100
+
+fig, ax = plt.subplots()
+ax.scatter('a', 'b', c='c', s='d', data=data)
+ax.set(xlabel='entry a', ylabel='entry b')
+plt.show()
diff --git a/tutorials/01_introductory/pyplot.py b/tutorials/01_introductory/pyplot.py
index 236226153c26..36642516dfbb 100644
--- a/tutorials/01_introductory/pyplot.py
+++ b/tutorials/01_introductory/pyplot.py
@@ -93,6 +93,31 @@
 plt.plot(t, t, 'r--', t, t**2, 'bs', t, t**3, 'g^')
 plt.show()
 
+###############################################################################
+# .. _plotting-with-keywords:
+#
+# Plotting with keyword strings
+# =============================
+#
+# There are some instances where you have data in a format that lets you
+# access particular variables with strings. For example, with
+# :class:`numpy.recarray` or :class:`pandas.DataFrame`.
+#
+# Matplotlib allows you provide such an object with
+# the ``data`` keyword argument. If provided, then you may generate plots with
+# the strings corresponding to these variables.
+
+data = {'a': np.arange(50),
+        'c': np.random.randint(0, 50, 50),
+        'd': np.random.randn(50)}
+data['b'] = data['a'] + 10 * np.random.randn(50)
+data['d'] = np.abs(data['d']) * 100
+
+plt.scatter('a', 'b', c='c', s='d', data=data)
+plt.xlabel('entry a')
+plt.ylabel('entry b')
+plt.show()
+
 ###############################################################################
 # .. _controlling-line-properties:
 #