Add files remove in https://github.com/jupyter/notebook/pull/124

docs/source/install/kernel_install.rst

@@ -0,0 +1,16 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:
+
+* 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
+normal text editor.

docs/source/notebook/plotting.rst

@@ -0,0 +1,34 b''
+.. _plotting:
+
+Plotting
+--------
+One major feature of the Jupyter notebook 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::
+
+  %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

docs/source/install/index.rst

@@ -8,4 +8,5 b' Installation'
    :maxdepth: 2
 
    install
+   kernel_install