Merge pull request #1480 from arokem/intersphinx

Add intersphinx links to other packages

doc/conf.py

@@ -35,6 +35,7 @@
     'sphinx.ext.coverage',
     'sphinx.ext.mathjax',
     'sphinx.ext.autosummary',
+    'sphinx.ext.intersphinx',
     'matplotlib.sphinxext.plot_directive',
     'gallery_generator',
     'numpydoc',
@@ -283,3 +284,12 @@
 def setup(app):
     app.add_javascript('copybutton.js')
     app.add_stylesheet('style.css')
+
+
+# -- Intersphinx ------------------------------------------------
+
+intersphinx_mapping = {'numpy': ('http://docs.scipy.org/doc/numpy/', None),
+                       'scipy': ('http://docs.scipy.org/doc/scipy/reference/', None),
+                       'matplotlib': ('http://matplotlib.org/', None),
+                       'pandas': ('https://pandas.pydata.org/pandas-docs/stable/', None),
+                       'statsmodels': ('http://www.statsmodels.org/stable/', None)}

doc/introduction.ipynb

@@ -86,7 +86,7 @@
    "cell_type": "raw",
    "metadata": {},
    "source": [
-    "Behind the scenes, seaborn uses matplotlib to draw plots. Many tasks can be accomplished with only seaborn functions, but further customization might require using matplotlib directly. This is explained in more detail :ref:`below <intro_plot_customization>`. For interactive work, it's recommended to use a Jupyter/IPython interface in `matplotlib mode <https://ipython.readthedocs.io/en/stable/interactive/plotting.html>`_, or else you'll have to call ``matplotlib.pyplot.show`` when you want to see the plot.\n",
+    "Behind the scenes, seaborn uses matplotlib to draw plots. Many tasks can be accomplished with only seaborn functions, but further customization might require using matplotlib directly. This is explained in more detail :ref:`below <intro_plot_customization>`. For interactive work, it's recommended to use a Jupyter/IPython interface in `matplotlib mode <https://ipython.readthedocs.io/en/stable/interactive/plotting.html>`_, or else you'll have to call :ref:`matplotlib.pyplot.show` when you want to see the plot.\n",
     "\n",
     "2. We apply the default default seaborn theme, scaling, and color palette."
    ]
@@ -130,7 +130,7 @@
    "cell_type": "raw",
    "metadata": {},
    "source": [
-    "Most code in the docs will use the :func:`load_dataset` function to get quick access to an example dataset. There's nothing particularly special about these datasets; they are just pandas dataframes, and we could have loaded them with ``pandas.read_csv`` or build them by hand. Many examples use the \"tips\" dataset, which is very boring but quite useful for demonstration. The tips dataset illustrates the \"tidy\" approach to organizing a dataset. You'll get the most out of seaborn if your datasets are organized this way, and it is explained in more detail :ref:`below <intro_tidy_data>`.\n",
+    "Most code in the docs will use the :func:`load_dataset` function to get quick access to an example dataset. There's nothing particularly special about these datasets; they are just pandas dataframes, and we could have loaded them with :ref:`pandas.read_csv` or build them by hand. Many examples use the \"tips\" dataset, which is very boring but quite useful for demonstration. The tips dataset illustrates the \"tidy\" approach to organizing a dataset. You'll get the most out of seaborn if your datasets are organized this way, and it is explained in more detail :ref:`below <intro_tidy_data>`.\n",
     "\n",
     "4. We draw a faceted scatter plot with multiple semantic variables."
    ]