Python library for interactive topic model visualization. Port of the R LDAvis package.
BSD-3-CLAUSE License
Python library for interactive topic model visualization.
This is a port of the fabulous R package <https://github.com/cpsievert/LDAvis>
_ by Carson Sievert <https://cpsievert.me/>
__ and Kenny Shirley <http://www.kennyshirley.com/>
__.
.. figure:: http://www.kennyshirley.com/figures/ldavis-pic.png :alt: LDAvis icon
pyLDAvis is designed to help users interpret the topics in a topic model that has been fit to a corpus of text data. The package extracts information from a fitted LDA topic model to inform an interactive web-based visualization.
The visualization is intended to be used within an IPython notebook but can also be saved to a stand-alone HTML file for easy sharing.
Note: LDA stands for latent Dirichlet allocation <https://en.wikipedia.org/wiki/Latent_Dirichlet_allocation>
_.
|version status| |build status| |docs|
Installation
- Stable version using pip:
::
pip install pyldavis
- Development version on GitHub
Clone the repository and run ``python setup.py``
Usage
The best way to learn how to use pyLDAvis is to see it in action.
Check out this notebook for an overview <http://nbviewer.ipython.org/github/bmabey/pyLDAvis/blob/master/notebooks/pyLDAvis_overview.ipynb>
.
Refer to the documentation <https://pyLDAvis.readthedocs.org>
for details.
For a concise explanation of the visualization see this
vignette <http://cran.r-project.org/web/packages/LDAvis/vignettes/details.pdf>
__ from the LDAvis R package.
Video demos
Ben Mabey walked through the visualization in this short talk using a Hacker News corpus:
- `Visualizing Topic Models <https://www.youtube.com/watch?v=tGxW2BzC_DU&index=4&list=PLykRMO7ZuHwP5cWnbEmP_mUIVgzd5DZgH>`__
- `Notebook and visualization used in the demo <http://nbviewer.ipython.org/github/bmabey/hacker_news_topic_modelling/blob/master/HN%20Topic%20Model%20Talk.ipynb>`__
- `Slide deck <https://speakerdeck.com/bmabey/visualizing-topic-models>`__
`Carson Sievert <https://cpsievert.me/>`__ created a video demoing the R package. The visualization is the same and so it applies equally to pyLDAvis:
- `Visualizing & Exploring the Twenty Newsgroup Data <https://www.youtube.com/watch?v=IksL96ls4o0>`__
More documentation
To read about the methodology behind pyLDAvis, see the original paper <http://nlp.stanford.edu/events/illvi2014/papers/sievert-illvi2014.pdf>
,
which was presented at the 2014 ACL Workshop on Interactive Language Learning, Visualization, and Interfaces <http://nlp.stanford.edu/events/illvi2014/>
in Baltimore
on June 27, 2014.
.. |version status| image:: https://img.shields.io/pypi/v/pyLDAvis.svg :target: https://pypi.python.org/pypi/pyLDAvis .. |build status| image:: https://travis-ci.org/bmabey/pyLDAvis.png?branch=master :target: https://travis-ci.org/bmabey/pyLDAvis .. |docs| image:: https://readthedocs.org/projects/pyldavis/badge/?version=latest :target: https://pyLDAvis.readthedocs.org