Package for Data Rhapsody's UniversityHack 2018 Challenge solution.
Project description
================================
Data Rhapsody UniversityHack2018
================================
.. image:: https://img.shields.io/pypi/v/universityhack2018.svg
:target: https://pypi.python.org/pypi/universityhack2018
.. image:: https://img.shields.io/travis/cabadsanchez/universityhack2018.svg
:target: https://travis-ci.org/cabadsanchez/universityhack2018
.. image:: https://readthedocs.org/projects/universityhack2018/badge/?version=latest
:target: https://universityhack2018.readthedocs.io/en/latest/?badge=latest
:alt: Documentation Status
Package for Data Rhapsody's UniversityHack 2018 Challenge solution.
* Free software: MIT license
* Documentation: https://universityhack2018.readthedocs.io.
Usage
-----
.. code-block:: python
from universityhack2018.feature_engineering import FeatureEngineering
from universityhack2018.prediction import Model
import pandas as pd
clients_df = pd.read_csv('/path/to/Dataset_Salesforce_Predictive_Modelling_TEST.txt')
clients = client_df_train.iloc[0:5, :]
model = Model(clients)
predictions = model.predict(as_df=True)
print(predictions.head())
# Output:
# ID_Customer PA_Est
# 0 TE000001 26926.541016
# 1 TE000002 15267.800781
# 2 TE000003 19499.935547
# 3 TE000004 12799.532227
# 4 TE000005 11262.253906
Features
--------
* TODO
Credits
-------
This package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.
.. _Cookiecutter: https://github.com/audreyr/cookiecutter
.. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage
=======
History
=======
0.1.0 (2018-03-11)
------------------
* First release on PyPI.
Data Rhapsody UniversityHack2018
================================
.. image:: https://img.shields.io/pypi/v/universityhack2018.svg
:target: https://pypi.python.org/pypi/universityhack2018
.. image:: https://img.shields.io/travis/cabadsanchez/universityhack2018.svg
:target: https://travis-ci.org/cabadsanchez/universityhack2018
.. image:: https://readthedocs.org/projects/universityhack2018/badge/?version=latest
:target: https://universityhack2018.readthedocs.io/en/latest/?badge=latest
:alt: Documentation Status
Package for Data Rhapsody's UniversityHack 2018 Challenge solution.
* Free software: MIT license
* Documentation: https://universityhack2018.readthedocs.io.
Usage
-----
.. code-block:: python
from universityhack2018.feature_engineering import FeatureEngineering
from universityhack2018.prediction import Model
import pandas as pd
clients_df = pd.read_csv('/path/to/Dataset_Salesforce_Predictive_Modelling_TEST.txt')
clients = client_df_train.iloc[0:5, :]
model = Model(clients)
predictions = model.predict(as_df=True)
print(predictions.head())
# Output:
# ID_Customer PA_Est
# 0 TE000001 26926.541016
# 1 TE000002 15267.800781
# 2 TE000003 19499.935547
# 3 TE000004 12799.532227
# 4 TE000005 11262.253906
Features
--------
* TODO
Credits
-------
This package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.
.. _Cookiecutter: https://github.com/audreyr/cookiecutter
.. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage
=======
History
=======
0.1.0 (2018-03-11)
------------------
* First release on PyPI.
Project details
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