pyLDAvis 3.4.1
Interactive topic model visualization. Port of the R package.
License: BSD-3-Clause
Requires Python: >=3.9
Keywords: data science,visualization

pyLDAvis
========

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>`_.

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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 <http://stat-graphics.org/movies/ldavis.html>`__

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.




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   :target: https://pypi.python.org/pypi/pyLDAvis
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   :target: https://travis-ci.org/bmabey/pyLDAvis
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   :target: https://pyLDAvis.readthedocs.org