Update documentation (#31)

* Add an API Reference

* Add google analytics tracking to docs

* Streamline README.rst for github

* Add install to toctree

* Update dendrogram docstrings

* Add captions for different sections

Author: Seth-Rothschild

README.rst

@@ -20,6 +20,8 @@ learning with ``henchman.selection`` and
 
 For more information, visit the Henchman `documentation <https://henchman.featurelabs.com>`_.
 
+
+
 Why?
 ~~~~~~~
 Life is full of reusable functions. Here's what separates
@@ -28,20 +30,16 @@ Henchman:
 - **Easy Interactive Plotting**: We bypass the flexible Bokeh
   API in favor of a small, rigid collection of standard data
   analysis plots. With sliders and checkboxes, finding the
-  right plot parameters is as easy as a single function call.
+  right plot parameters can be done with a `single function call <https://henchman.featurelabs.com/plotting_gallery.html>`_.
 
-.. image:: http://henchman.featurelabs.com/_images/piechart.gif
-   :width: 47%
-   :height: 300px
-.. image:: http://henchman.featurelabs.com/_images/histogram.gif
-   :width: 47%
-   :height: 300px
+.. image:: https://henchman.featurelabs.com/_images/timeseries.gif
+   :align: center
 
 - **Memorable API, Extensive documentation**: We have a
   heavy emphasis on ease of use. That means all the
   functions are sorted into one of 4 semantically named
   modules and names should be easy to remember inside that
-  module. On top of that, every function has a docstring, an
+  module. Additionally, every function has a docstring, an
   example and a `documentation <https://henchman.featurelabs.com>`_
   page.
 
@@ -52,20 +50,9 @@ Henchman:
 - **Novel Functionality**: We provide a few functions built
   from scratch to add to your data science workflow. There
   are methods to systematically find dataset attributes with
-  ``overview`` and ``warnings`` from `henchman.diagnostics` and classes to
-  select features in novel ways with ``RandomSelect`` and
-  ``Dendrogram`` in `henchman.selection`.
-
-.. image:: http://henchman.featurelabs.com/_images/overview.png
-   :width: 47%
-   :height: 300px
-.. image:: http://henchman.featurelabs.com/_images/warnings.png
-   :width: 47%
-   :height: 300px
-
-.. image:: http://henchman.featurelabs.com/_images/dendrogram.gif
-   :align: center
-
+  `overview <https://henchman.featurelabs.com/documentation.html#diagnostics>`_ and `warnings <https://henchman.featurelabs.com/generated/henchman.diagnostics.warnings.html>`_ from ``henchman.diagnostics`` and classes to
+  select features in novel ways with `RandomSelect <https://henchman.featurelabs.com/documentation.html#selection>`_ and
+  `Dendrogram <https://henchman.featurelabs.com/generated/henchman.selection.Dendrogram.html>`_ in ``henchman.selection``.
 
 
 Install
@@ -82,11 +69,10 @@ If you are using conda, you can download the most recent build from our channel
 
     $ conda install -c featurelabs henchman
 
-These are the preferred methods 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.
+These are the preferred methods to install Henchman, as it will always install the most recent stable release. You can download miniconda `from this page`_.
+
+.. _from this page: https://github.com/conda/conda
 
-.. _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`_.
 
@@ -108,7 +94,6 @@ Once you have a copy of the source, you can install it with:
 
     $ python setup.py install
 
-
 .. _Github repo: https://github.com/featurelabs/henchman
 .. _tarball: https://github.com/featurelabs/henchman/tarball/master
 

docs/_source/api_ref.rst

@@ -0,0 +1,72 @@
+.. _api_ref:
+
+API Reference
+===============
+
+Diagnostics API
+~~~~~~~~~~~~~~~~
+
+.. currentmodule:: henchman.diagnostics
+
+.. autosummary::
+    :toctree: generated/
+
+    overview
+    warnings
+    column_report
+    profile
+
+
+Selection API
+~~~~~~~~~~~~~~
+
+.. currentmodule:: henchman.selection
+
+
+.. autosummary::
+    :toctree: generated/
+
+    RandomSelect
+    Dendrogram
+    Dendrogram.fit
+    Dendrogram.transform
+    Dendrogram.set_params
+    Dendrogram.features_at_step
+    Dendrogram.find_set_of_size
+    Dendrogram.score_at_point
+    Dendrogram.shuffle_score_at_point
+
+Learning API
+~~~~~~~~~~~~~~
+
+.. currentmodule:: henchman.learning
+
+
+.. autosummary::
+    :toctree: generated/
+
+    create_model
+    inplace_encoder
+    feature_importances
+    create_holdout
+
+Plotting API
+~~~~~~~~~~~~~
+
+.. currentmodule:: henchman.plotting
+
+
+.. autosummary::
+    :toctree: generated/
+
+    show
+    show_template
+    piechart
+    histogram
+    timeseries
+    scatter
+    dendrogram
+    feature_importances
+    roc_auc
+    f1
+

docs/_source/conf.py

@@ -75,7 +75,7 @@
 # Usually you set "language" from the command line for these cases.
 language = None
 
-autosummary_generate = ["documentation.rst", "generated/henchman.selection.Dendrogram.rst"]
+autosummary_generate = ["api_ref.rst"]
 
 # List of patterns, relative to source directory, that match files and
 # directories to ignore when looking for source files.

docs/_source/documentation.rst

@@ -1,7 +1,5 @@
-.. _api_ref:
+.. _documentation:
 
-Documentation
-=============
 The ``Henchman`` package has reusable functionality in four areas: 
 `dataframe diagnostics <#diagnostics>`_, `feature selection
 <#selection>`_, `machine learning <#learning>`_ and `bokeh plotting <#plotting>`_.
@@ -23,7 +21,7 @@ We'll load in the csv using pandas.
 .. _diagnostics:
 
 Diagnostics
-~~~~~~~~~~~
+============
 It can sometimes be hard to find information about a dataframe by inspection.
 Frequent questions such as "how large is this dataframe" and "are there duplicates"
 usually require copying code from one notebook to another. In this module, we give easy
@@ -87,7 +85,7 @@ about every column in the dataframe.
 .. _selection:
 
 Selection
-~~~~~~~~~
+==========
 
 There are some lightweight feature selection packages
 provided as well. There is
@@ -147,7 +145,7 @@ can be shuffled to return a similarly connected feature set.
 .. _learning:
 
 Learning
-~~~~~~~~
+==========
 The learning module exists to simplify some frequent machine
 learning calls. For instance, given a feature matrix ``X``
 and a column of labels ``y``, it's nice to be able to
@@ -184,10 +182,11 @@ We can check :func:`feature importances
     feature_importances
     create_holdout
 
+
 .. _plotting:
 
 Plotting 
-~~~~~~~~~
+=========
 
 The plotting module gives a collection of useful dataset
 agnostic plots. Plots have the ability to be *dynamic* or

docs/_source/index.rst

@@ -1,14 +1,24 @@
 .. include:: readme.rst
 
 .. toctree::
-   :maxdepth: 2
-   :caption: Contents:
+   :caption: Overview
+   :titlesonly:
 
    readme
-   documentation
    plotting_gallery
+
+.. toctree::
+   :caption: Documentation
+   :maxdepth: 2
+
+   documentation
+
+.. toctree::
+   :caption: Reference
+
    contributing
    authors
+   api_ref
 
 Indices and tables
 ==================

docs/_source/readme.rst

@@ -1,16 +1,18 @@
-Welcome to Henchman!
-=====================
-Henchman is a collection of open source python
-utility functions for working in a jupyter notebook. With
-Henchman, you can rapidly prototype end-to-end data science
-workflows. You can explore data with
-:ref:`diagnostics`, make interesting plots with
-:ref:`plotting`, and do feature selection and machine
-learning with :ref:`selection` and 
+Welcome to Henchman! 
+===================== 
+
+Henchman is a collection of `open source
+<https://github.com/featurelabs/henchman>`_ python utility
+functions for working in a jupyter notebook. With Henchman,
+you can rapidly prototype end-to-end data science workflows.
+You can explore data with :ref:`diagnostics`, make
+interesting plots with :ref:`plotting`, and do feature
+selection and machine learning with :ref:`selection` and
 :ref:`learning`.
 
 Why?
-~~~~~~~
+~~~~~
+
 Life is full of reusable functions. Here's what separates
 Henchman:
 
@@ -30,11 +32,12 @@ Henchman:
    :height: 400px
    :align: center
 
-- **Memorable API, Extensive documentation**: We have a heavy
-  emphasis on ease of use. That means all the functions are
-  sorted into one of 4 semantically named modules and names
-  should be easy to remember inside that module. On top of
-  that, every function has a docstring, an example and a documentation page.
+- **Memorable API, Extensive documentation**: We have a
+  heavy emphasis on ease of use. That means all the
+  functions are sorted into one of 4 semantically named
+  modules and names should be easy to remember inside that
+  module. Additionally, every function has a docstring, an
+  example and a documentation page.
 
 .. image:: img/create_model_docs.png
    :width: 75%
@@ -60,7 +63,7 @@ Henchman:
 
 
 Install
-~~~~~~~~~
+========
 To install Henchman, run this command in your terminal:
 
 .. code-block:: console
@@ -73,11 +76,10 @@ If you are using conda, you can download the most recent build from our channel
 
     $ conda install -c featurelabs henchman
 
-These are the preferred methods 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.
+These are the preferred methods to install Henchman, as it will always install the most recent stable release. You can download miniconda `from this page`_.
+
+.. _from this page: https://github.com/conda/conda
 
-.. _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`_.
 

docs/_source/templates/layout.html

@@ -0,0 +1,11 @@
+{% extends "!layout.html" %}
+{% set css_files = css_files + ['_static/style.css'] %}
+
+{%- block extrahead %}
+<script>
+  !function(){var analytics=window.analytics=window.analytics||[];if(!analytics.initialize)if(analytics.invoked)window.console&&console.error&&console.error("Segment snippet included twice.");else{analytics.invoked=!0;analytics.methods=["trackSubmit","trackClick","trackLink","trackForm","pageview","identify","reset","group","track","ready","alias","debug","page","once","off","on"];analytics.factory=function(t){return function(){var e=Array.prototype.slice.call(arguments);e.unshift(t);analytics.push(e);return analytics}};for(var t=0;t<analytics.methods.length;t++){var e=analytics.methods[t];analytics[e]=analytics.factory(e)}analytics.load=function(t,e){var n=document.createElement("script");n.type="text/javascript";n.async=!0;n.src="https://cdn.segment.com/analytics.js/v1/"+t+"/analytics.min.js";var a=document.getElementsByTagName("script")[0];a.parentNode.insertBefore(n,a);analytics._loadOptions=e};analytics.SNIPPET_VERSION="4.1.0";
+  analytics.load("OIv3wkryIhVtrOQJCHicFvpNgmLGtr0o");
+  analytics.page();
+  }}();
+</script>
+{% endblock %}