tlamadon / bipartitepandas

Python tools for bipartite labor data
MIT License
4 stars 1 forks source link

BipartitePandas

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

.. image:: https://anaconda.org/tlamadon/bipartitepandas/badges/version.svg :target: https://anaconda.org/tlamadon/bipartitepandas

.. image:: https://anaconda.org/tlamadon/pytwoway/badges/platforms.svg :target: https://anaconda.org/tlamadon/pytwoway

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

.. image:: https://codecov.io/gh/tlamadon/bipartitepandas/branch/master/graph/badge.svg?token=NqS9Dwufxv :target: https://codecov.io/gh/tlamadon/bipartitepandas

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

.. image:: https://badgen.net/badge//gh/bipartitepandas?icon=github :target: https://github.com/tlamadon/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%2Fsource%2Fnotebooks%2Fsimple_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.

BipartitePandas is used in PyTwoWay <https://github.com/tlamadon/pytwoway/>_.

The package provides a Python interface. Installation is handled by pip or Conda. 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/>.

Installation

To install via pip, from the command line run::

pip install bipartitepandas

To install via Conda, from the command line run::

conda install -c tlamadon bipartitepandas

Authors

Thibaut Lamadon, Assistant Professor in Economics, University of Chicago, lamadon@uchicago.edu

Adam A. Oppenheimer, Graduate Student, University of Minnesota - Twin Cities, oppen040@umn.edu