Working sphiunx build

docs/_build/html/.buildinfo

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+# Sphinx build info version 1
+# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
+config: 19bbadb7a81fa723ab573d8e34479952
+tags: 645f666f9bcd5a90fca523b33c5a78b7

docs/_build/html/_sources/index.rst.txt

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+.. keras-pandas documentation master file, created by
+   sphinx-quickstart on Fri May 25 16:33:06 2018.
+   You can adapt this file completely to your liking, but it should at least
+   contain the root `toctree` directive.
+
+Welcome to keras-pandas's documentation!
+========================================
+
+.. toctree::
+   :maxdepth: 2
+   :caption: Contents:
+
+.. automodule:: Automater
+    :members:
+    :undoc-members:
+    :show-inheritance:
+
+
+Indices and tables
+==================
+
+* :ref:`genindex`
+* :ref:`modindex`
+* :ref:`search`

docs/_build/html/_sources/planning/POC_notes.md.txt

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+# Backlog 
+
+ - Interface: Need to determine options (SKLearn transformer, custom interface, etc)
+ - Interface: Need to outline functionality
+ - Boolean: Need to determine if it'll be handled as numerical or categorical
+ - Pip installable: Need to determine level of effort
+
+# Interface: Need to determine options (SKLearn transformer, custom interface, etc)
+
+Options: 
+
+ - SKLearn transformer
+ - Pandas-SKLearn style module
+ - Custom module
+
+Requirements:
+
+ - Be able to expand one column to many columns (datetime)
+ - Abilityt o use SKLearn transformers
+
+## SKLearn transformer
+
+ - Inputs would have to be Numpy arrays
+ - Inputs can be Numpy arrays
+ - Tighter integration to SKLearn infrastructure
+
+## Pandas-SKLearn style module
+
+ - Can have pandas dataframe inputs
+ - Can have multipel column inputs
+ - Can apply multiple transformations to the same column (many to one relationship)
+ - Can not apply transformations to some columns
+ - Can use default transformer
+
+## Custom module
+
+ - Can sit on top of Pandas-SKLearn
+ - Can mimic SKLearn `fit` and `transform` interface
+
+#  Need to determine if it'll be handled as numerical or categorical
+
+## Numerical 
+
+ - Less compute time
+ - Reduced complexity
+
+## Categorical
+
+ - Embedding representing different values
+
+# Pip installable: Need to determine level of effort
+
+## Lit review
+
+ - PMOTW: Setuptools
+ - Common library: setuptools
+ - PMOTW: distutils
+ - Common library: distutils
+ - Blog review
+
+## PMOTW: Setuptools
+
+ - Unavailable
+
+## [Common library: setuptools](https://setuptools.readthedocs.io/en/latest/)
+
+ - Designed to facilitate packaging Python projects
+ - Enhancement to distutils
+
+Highlights
+
+ - Dependency resolution & downloading
+ - Create eggs
+ - Automatically create wrapper scripts & .exe files
+ - [Decent getting started guide](https://setuptools.readthedocs.io/en/latest/setuptools.html#basic-use)
+
+Superset of of distutils
+
+## PMOTW: distutils
+
+ - Unavailable
+
+## [Common library: distutils](https://docs.python.org/2/distutils/)
+
+[Intro](https://docs.python.org/2/distutils/introduction.html)
+
+ - Setup script
+ - Source distribution
+ - Binary distributions
+
+Setup script
+
+ - Handles packaging
+ - Not aware of package managers
+
+[PyPi](https://docs.python.org/2/distutils/packageindex.html#pypi-overview)
+
+ - Registering
+ - Upload
+
+## Blogs
+
+ - [Marthall](https://marthall.github.io/blog/how-to-package-a-python-app/)
+ - [so](https://stackoverflow.com/questions/9411494/how-do-i-create-a-pip-installable-project)
+
+## [Marthall](https://marthall.github.io/blog/how-to-package-a-python-app/)
+
+ - Strong, convenient walk through
+
+## [so](https://stackoverflow.com/questions/9411494/how-do-i-create-a-pip-installable-project)
+
+ - Rambling
+
+## [Scott Torborg](http://python-packaging.readthedocs.io/en/latest/)
+
+- Strong advanced discussion
+- How to declare dependencies
+
+## [PyPI docs](https://packaging.python.org/tutorials/distributing-packages/#uploading-your-project-to-pypi)
+
+## [twine quickstart](https://packaging.python.org/tutorials/distributing-packages/)
+
+# Decisions
+
+ - Interface: Will use custom interface, similar to SKLearn, with Pandas-SKLearn under the hood.
+ - Pip installable: Will move forward w/ setuptools

docs/_build/html/_sources/planning/brainstorming.md.txt

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+# Elevator pitch
+
+# Audience
+
+ - Semi-technical
+ - ML background, new to deep learning
+ - Familiarity with Python data ecosystem (Pandas, SKLearn, numpy)
+ - Interested in getting started in deep learning
+ - Interested in quickly prototyping models
+
+# Goals
+
+ - Easy to use interface
+ - Sensible default actions
+ - Low barrier to entry to create Keras input / output layers
+
+# Requirements
+
+## Backlog
+
+ - Numerical inputs: Null handling, Z score normalizaiton
+ - Categorical inputs: Create embedding, handle unseen levels
+ - Boolean inputs: Handle appropriately
+ - Datetime: Extract categorical fields, treat as epoch time if possible. 
+ - Test run: train on random sample of data
+ - Convenient interface
+ - Logging
+ - Unit tests
+ - Appropriate exceptions
+ - Pip installable 
+
+## Prioritized backlog
+
+ - Unit tests
+ - Logging
+ - Numerical inputs: Null handling, Z score normalizaiton
+ - Categorical inputs: Create embedding, handle unseen levels
+ - Boolean inputs: Handle appropriately
+ - Datetime: Extract categorical fields, treat as epoch time if possible. 
+ - Appropriate exceptions
+ - Pip installable 
+
+## POC items
+
+ - Interface: Need to determine options (SKLearn transformer, custom interface, etc)
+ - Interface: Need to outline functionality
+ - Boolean: Need to determine if it'll be handled as numerical or categorical
+ - Pip installable: Need to determine level of effort

docs/_build/html/_sources/planning/interface.md.txt

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+# Public API
+
+## Methods
+
+ - init
+ - fit
+ - transform
+ - datetime_expansion_method_dict
+ - constants
+ - set_embedding_size_function
+ - set_embedding_size_for_variable
+ - get_tranformers
+ - get_transformer
+ - list_default_transformation_pipelines
+ - list_input_variables
+ - list_output_variables
+
+## Attributes
+
+(no public attributes)
+
+
+# Internal API
+
+## Methods
+
+ - check_variable_lists
+ - check_input_dataframe_columns
+ - check_output_dataframe_columns
+ - datetime expansion
+ - get_input_nub
+ - get_output_nub
+
+## Attributes
+
+ - sklearn_pandas_object
+ - datetime_expansion_method_dict
+ - embedding_size_function
+ - variable_transformer_dict
+ - input_variables
+ - output variables
+ - input_numb
+ - output_nub

docs/_build/html/_sources/planning/new_var_type.md.txt

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+Workflow for new variable type: 
+
+ - Add default transformation type
+ - Add input layer handler
+ - Add output layer handler