@takluyver's suggested changes

Add links

Add another kernel-spec link

Address @takluyver 's comments

docs/source/install/kernel_install.rst

@@ -1,16 +1,15 b''
 .. _kernel_install:
 
 Kernel Installation
 -------------------
 
-IPython can be installed (different python versions, virtualenv or conda environments) can
-be installed as a kernel by following these steps:
+IPython can be installed (different python versions, virtualenv or conda 
+environments) as a kernel by following these steps:
 
 * make sure that the desired python installation is active (e.g. activate the environment)
   and ipython is installed
 * run once ``ipython kernelspec install-self --user`` (or ``ipython2 ...`` or ``ipython3 ...``
   if you want to install specific python versions)
 
-The last command installs a kernel spec file for the current python installation in
-``~/.jupyter/kernels/``. Kernel spec files are JSON files, which can be viewed and changed with a
+The last command installs a :ref:`kernel spec <jupyterclient:kernelspecs>` file for the current python installation. Kernel spec files are JSON files, which can be viewed and changed with a
 normal text editor.

docs/source/interactive/index.rst

@@ -1,17 +1,18 b''
 ==================================
 Using IPython for interactive work
 ==================================
 
 .. toctree::
    :maxdepth: 2
 
    tutorial
-   tips
-   reference
    magics
-   shell
+   plotting
    qtconsole
+   reference
+   shell
+   tips
 
 .. seealso::
 
     `The Jupyter Notebook <http://jupyter-notebook.readthedocs.org/en/latest/>`__

docs/source/interactive/plotting.rst

@@ -1,34 +1,36 b''
 .. _plotting:
 
 Plotting
 --------
-One major feature of the Jupyter notebook is the ability to display plots that 
+One major feature of the IPython kernel is the ability to display plots that 
 are the output of running code cells. The IPython kernel is designed to work 
 seamlessly with the matplotlib_ plotting library to provide this functionality.
 
 To set this up, before any plotting is performed you must execute the
 ``%matplotlib``  :ref:`magic command <magics_explained>`. This performs the
 necessary behind-the-scenes setup for IPython to work correctly hand in hand
 with ``matplotlib``; it does *not*, however, actually execute any Python
 ``import`` commands, that is, no names are added to the namespace.
 
 If the ``%matplotlib`` magic is called without an argument, the
 output of a plotting command is displayed using the default ``matplotlib``
 backend in a separate window. Alternatively, the backend can be explicitly
 requested using, for example::
 
   %matplotlib gtk
 
 A particularly interesting backend, provided by IPython, is the ``inline``
 backend.  This is available only for the Jupyter Notebook and the
-:ref:`IPython QtConsole <qtconsole>`.  It can be invoked as follows::
+:ref:`Jupyter QtConsole <qtconsole>`.  It can be invoked as follows::
 
   %matplotlib inline
 
 With this backend, the output of plotting commands is displayed *inline*
 within the notebook, directly below the code cell that produced it. The
 resulting plots will then also be stored in the notebook document.
 
 .. seealso::
 
     `Plotting with Matplotlib`_  example notebook
+
+.. include:: ../links.txt