Metadata-Version: 2.1
Name: bipartitepandas
Version: 0.0.2
Summary: Python tools for bipartite labor data
Home-page: https://github.com/tlamadon/bipartitepandas
Author: Thibaut Lamadon
Author-email: thibaut.lamadon@gmail.com
License: UNKNOWN
Project-URL: Documentation, https://tlamadon.github.io/bipartitepandas/
Project-URL: GitHub, https://github.com/tlamadon/bipartitepandas
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/x-rst
Requires-Dist: numpy
Requires-Dist: numpy-groupies
Requires-Dist: pandas
Requires-Dist: scipy
Requires-Dist: scikit-learn
Requires-Dist: networkx
Requires-Dist: tqdm

bipartitepandas
---------------

.. image:: https://badge.fury.io/py/bipartitepandas.svg
    :target: https://badge.fury.io/py/bipartitepandas

.. image:: https://travis-ci.com/tlamadon/bipartitepandas.svg?branch=master
    :target: https://travis-ci.com/tlamadon/bipartitepandas

.. image:: https://img.shields.io/codecov/c/github/tlamadon/bipartitepandas.svg?maxAge=2592000
    :target: https://codecov.io/github/tlamadon/bipartitepandas?branch=master

.. image:: https://img.shields.io/badge/doc-latest-blue
    :target: https://tlamadon.github.io/bipartitepandas/

`bipartitepandas` is a python package for handling bipartite labor data.

.. |binder| image:: https://mybinder.org/badge_logo.svg 
    :target: https://mybinder.org/v2/gh/tlamadon/bipartitepandas/HEAD?filepath=docs%2Fnotebooks%2Fbipartitepandas_example.ipynb

If you want to give it a try, you can start the example notebook here: |binder|. This starts a fully interactive notebook with a simple example that generates data and demonstrates some useful functions.

The package provides a python interface. Installation is handled by `pip` or `conda` (TBD). The source of the package is available on github at `bipartitepandas <https://github.com/tlamadon/bipartitepandas>`_. The online documentation is hosted  `here <https://tlamadon.github.io/bipartitepandas/>`_.

Quick Start
-----------

To install from pip, run::

    pip install bipartitepandas


