second docs update

AUTHORS.rst

@@ -2,6 +2,8 @@
 Credits
 =======
 
+This package was created with [Cookiecutter](https://github.com/audreyr/cookiecutter) and the [audreyr/cookiecutter-pypackage](https://github.com/audreyr/cookiecutter-pypackage) project template.
+
 Development Lead
 ----------------
 

README.rst

@@ -1,38 +1,56 @@
-Henchman
+Overview
 =============
 A collection of utility functions for making demo notebooks.
 
-* Free software: GNU General Public License v3
-* Documentation: https://notebook-utilities.readthedocs.io.
+* Free software: BSD-3
 
-To install the development version with pip: 
+The Henchman package is a collection of frequently used utility functions for Featuretools demos. There are a number of functions which appear in multiple `utils.py` files in multiple demos. This project consolidates those into 4 categories of reusable functions: `dataframe diagnostics <documentation.html#diagnostics>`_, `feature selection
+<documentation.html#selection>`_, `machine learning <documentation.html#learning>`_ and `bokeh plotting <documentation.html#plotting>`_.
 
-1. download the repository 
-2. open a terminal and navigate to the downloaded folder
-3. run ``pip install -e .``
+Install
+~~~~~~~~~
+To install Henchman, run this command in your terminal:
+
+.. code-block:: console
+
+    $ pip install henchman
+
+This is the preferred method to install Henchman, as it will always install the most recent stable release.
+
+If you don't have `pip`_ installed, this `Python installation guide`_ can guide
+you through the process.
+
+.. _pip: https://pip.pypa.io
+.. _Python installation guide: http://docs.python-guide.org/en/latest/starting/installation/
+
+The sources for Henchman can be downloaded from the `Github repo`_.
+
+You can either clone the public repository:
+
+.. code-block:: console
+
+    $ git clone git://github.com/featurelabs/henchman
+
+Or download the `tarball`_:
+
+.. code-block:: console
+
+    $ curl  -OL https://github.com/featurelabs/henchman/tarball/master
+
+Once you have a copy of the source, you can install it with:
+
+.. code-block:: console
+
+    $ python setup.py install
+
+
+.. _Github repo: https://github.com/featurelabs/henchman
+.. _tarball: https://github.com/featurelabs/henchman/tarball/master
 
-Functionality
-~~~~~~~~~~~~~
 
-The Henchman package is a collection of frequently used utility functions for Featuretools demos. There are a number of functions which appear in multiple `utils.py` files in multiple demos. This project consolidates those into 4 categories of reusable functions.
 
-Diagnostics
------------
-It's often useful to have an all-at-once overview of what is going on in a particular dataframe or feature matrix. The diagnostics module gives basic print functionality for many commonly asked questions. You can import the ``profile`` function with ``from henchman.diagnostics import profile``.
 
-Selection
----------
-Given the number of features that Featuretools is capable of creating, it's worthwhile having some easily usable feature selection techniques. This module provides a wrapper around some scikit-learn methods.
 
-Learning
---------
-We reuse the same workflow in multiple demos once we have transformed our feature matrix into an ``X`` and ``y``. The ``create_model`` function gives a basic validation split and scores according to a provided model and metric. To use, import with ``from henchman.learning import create_model``.
 
-Plotting
---------
-It's usually preferable to look at a plot than a dataframe, but it can take a lot of time to make a perfect looking plot. This module gives a simple interface for certain plots that we know we'll need often.
 
-Credits
-~~~~~~~
 
-This package was created with [Cookiecutter](https://github.com/audreyr/cookiecutter) and the [audreyr/cookiecutter-pypackage](https://github.com/audreyr/cookiecutter-pypackage) project template.

docs/conf.py

@@ -36,7 +36,7 @@
               'sphinx.ext.autosummary',
               'sphinx.ext.napoleon',
               'sphinx.ext.viewcode',
-              'sphinx.ext.autosummary',
+              'nbsphinx',
               'IPython.sphinxext.ipython_console_highlighting',
               'IPython.sphinxext.ipython_directive']
 
@@ -50,7 +50,7 @@
 # You can specify multiple suffix as a list of string:
 #
 # source_suffix = ['.rst']
-source_suffix = '.rst'
+source_suffix = ['.rst', '.ipynb']
 
 # The master toctree document.
 master_doc = 'index'

docs/documentation.rst

@@ -8,8 +8,8 @@ The ``Henchman`` package has reusable functionality in four areas:
 We'll demonstrate some of that functionality here in the documentaion.
 
 To get started, we'll use a premade feature matrix
-from the Featuretools package ``ft.demo.load_flight``.
-We'll load in the package using pandas.
+from the Featuretools ``ft.demo.load_flight()`` function.
+We'll load in the csv using pandas.
 
 .. ipython:: python
 
@@ -201,7 +201,10 @@ from which you can copy and paste the ones you want.
     from henchman.plotting import show
     hplot.show_template()
 
-**Module Contents**
+See the `plotting examples <plotting_examples.html>`_ page
+for some example bokeh plots.
+
+ **Module Contents**
 
 .. currentmodule:: henchman.plotting
 

docs/functionality_examples.ipynb

@@ -6022,7 +6022,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython2",
-   "version": "2.7.14"
+   "version": "2.7.10"
   }
  },
  "nbformat": 4,

docs/index.rst

@@ -7,6 +7,7 @@ Welcome to the Henchman documentation!
 
    readme
    documentation
+   plotting_examples
    contributing
    authors