Metadata-Version: 1.1
Name: bandicoot
Version: 0.5.1
Summary: A toolbox to analyze mobile phone metadata.
Home-page: https://github.com/yvesalexandre/bandicoot
Author: Yves-Alexandre de Montjoye
Author-email: yvesalexandre@demontjoye.com
License: MIT
Description: .. raw:: html
        
           <h1>
        
        bandicoot
        
        .. raw:: html
        
           </h1>
        
        **bandicoot** (http://bandicoot.mit.edu ) is Python toolbox to analyze
        mobile phone metadata. It provides a complete, easy-to-use environment
        for data-scientist to analyze mobile phone metadata. With only a few
        lines of code, load your datasets, visualize the data, perform analyses,
        and export the results.
        
        .. raw:: html
        
           <p align="center">
        
        Bandicoot interactive visualization
        
        .. raw:: html
        
           </p>
        
        Where to get it
        ---------------
        
        The source code is currently hosted on Github at
        https://github.com/yvesalexandre/bandicoot. Binary installers for the
        latest released version are available at the Python package index:
        
        ::
        
            http://pypi.python.org/pypi/bandicoot/
        
        And via ``easy_install``:
        
        .. code:: sh
        
            easy_install bandicoot
        
        or ``pip``:
        
        .. code:: sh
        
            pip install bandicoot
        
        Dependencies
        ------------
        
        bandicoot has no dependencies, which allows users to easily compute
        indicators on a production machine. To run tests and compile the
        visualization, optional dependencies are needed:
        
        -  `numpy <http://www.numpy.org/>`__,
           `scipy <https://www.scipy.org/>`__, and
           `networkx <https://networkx.github.io/>`__ for tests,
        -  `npm <http://npmjs.com>`__ to compile the js and css files of the
           dashboard.
        
        Licence
        -------
        
        MIT
        
        Documentation
        -------------
        
        The official documentation is hosted on
        `bandicoot.mit.edu/docs <http://bandicoot.mit.edu/docs>`__. It includes
        a quickstart tutorial, a detailed reference for all functions, and
        guides on how to use and extend bandicoot.
        
Platform: UNKNOWN
Classifier: Environment :: Plugins
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Scientific/Engineering :: Mathematics
