ShapKa 1.1.1
Key Satisfaction Drivers Analysis based on Shapley values and Kano model
License: MIT license
Requires Python: >=3.7.*
Keywords: ShapKa

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ShapKa: an open source python library to identify customer satisfaction drivers based on Shapley values and Kano model
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Installation
------------
Use the following command to install the package:

.. code-block:: python

   pip install ShapKa


Usage
-----
Use the following command for a key dissatisfaction drivers analysis (kda) :

.. code-block:: python 

    import pandas as pd
    from ShapKa.kanomodel import KanoModel

    # Load data
    df = pd.read_csv('data/example_03.csv')

    # Define X and Y variables names
    y_varname = 'Overall Satisfaction'
    weight_varname = 'Weight'
    X_varnames = df.columns.values.tolist()
    X_varnames.remove(y_varname)
    X_varnames.remove(weight_varname)

    # Run analysis to identify key dissatisfiers
    model = KanoModel(df, 
                      y_varname, X_varnames, 
                      analysis = 'kda',
                      y_dissat_upperbound = 6, y_sat_lowerbound = 9,
                      X_dissat_upperbound = 6, X_sat_lowerbound = 9,
                      weight_varname = weight_varname)

    kda = model.key_drivers() ;kda


Here is the ouput :

.. image:: img/output_ShapKa.png
        :width: 600

Replace 'kda' by 'kea' in the analysis parameter if you want to identify key enhancers (kea) instead of key dissatisfiers


Documentation
-------------
* Documentation: https://shapleykano.readthedocs.io.


Credits
-------

* The ShapKa package is based on the methodology developped by `W. Michael Conklin, Ken Powaga and Stan Lipovetsky`_

* Some parts of the code are based on functions implemented in the `Open Source Sage Mathematical Software`_


References
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* Conklin, Michael & Powaga, Ken & Lipovetsky, Stan. (2004). Customer satisfaction analysis: Identification of key drivers. European Journal of Operational Research. 154. 819-827. 10.1016/S0377-2217(02)00877-9. 

* Sage - Open Source Mathematical Software : `https://github.com/sagemath/sage`_

.. _`W. Michael Conklin, Ken Powaga and Stan Lipovetsky`: https://www.researchgate.net/publication/222399844_Customer_satisfaction_analysis_Identification_of_key_drivers

.. _`https://github.com/sagemath/sage`: https://github.com/sagemath/sage

.. _`Open Source Sage Mathematical Software`: https://github.com/sagemath/sage


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History
=======

1.1.1 (2020-06-03)
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* Minor Bug Correction.

1.1.0 (2020-06-03)
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* Add weighting data functionnality.

1.0.0 (2019-10-25)
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* First release on PyPI.