easyLDA 0.2.7

easily bult LDA Topic Models with just a list of docs (e.g. a list of twitter posts in CSV/TXT

easyLDA
-------

|PyPI version|

easyLDA is a library that easily build LDA Topic Models with just a list of docs (e.g. a list of twitter posts in CSV/TXT)
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

github: https://github.com/shichaoji/easyLDA
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

- If you have a collection of documents, and what to explore the
relationship & topics of the docs, easyLDA is a very handy library to
use. Simply run the commend and you'll get a trained LDA model with
results visualized

The library pipeline text preprocessing, such as tf-idf, n-grams from Gensim library
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

Credit to:

https://radimrehurek.com/gensim/

http://pyldavis.readthedocs.io/en/latest/readme.html

.. |PyPI version| image:: https://badge.fury.io/py/easyLDA.svg
:target: https://badge.fury.io/py/easyLDA

installation
~~~~~~~~~~~~

``$ pip install easyLDA``

usage example
~~~~~~~~~~~~~

simple need a text file (.csv) with each row represents a document (a post, comment, short article etc.), with only one column which is the text
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

text file (csv) sample view
^^^^^^^^^^^^^^^^^^^^^^^^^^^

easy to use, just in a shell window, type: easyLDA, then specify the location of the text document
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

1. then choose how many topics you want the model to fit
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

2. choose the topic contains only single word (1) or can be phases (2/3) as well
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

the program will be starting to train
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

- in shell $ easyLDA

model result
~~~~~~~~~~~~

models folder created by program contains the trained model
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

xx.html file is the interactive visulization of the model result
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

visualization live example
~~~~~~~~~~~~~~~~~~~~~~~~~~

.. code:: ipython2

from IPython.core.display import HTML
HTML(text)




.. raw:: html


<link rel="stylesheet" type="text/css" href="https://cdn.rawgit.com/bmabey/pyLDAvis/files/ldavis.v1.0.0.css">


<div id="ldavis_el12433140442019257808846793769"></div>
<script type="text/javascript">

var ldavis_el12433140442019257808846793769_data = {"plot.opts": {"xlab": "PC1", "ylab": "PC2"}, "topic.order": [9, 4, 12, 2, 7, 1, 10, 13, 8, 6, 3, 5, 15, 11, 14], "token.table": {"Topic": [15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 13, 14, 7, 11, 7, 10, 14, 6, 11, 6, 7, 10, 11, 14, 15, 15, 12, 6, 12, 1, 3, 4, 5, 8, 13, 1, 3, 10, 13, 3, 14, 9, 5, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 1, 2, 4, 5, 6, 9, 10, 12, 13, 14, 15, 6, 7, 11, 12, 9, 15, 4, 14, 3, 6, 7, 8, 10, 11, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 5, 4, 6, 7, 8, 11, 12, 14, 9, 13, 14, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 8, 11, 15, 13, 4, 5, 6, 7, 9, 8, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 14, 2, 14, 1, 3, 4, 12, 2, 13, 1, 5, 9, 11, 11, 1, 2, 3, 5, 7, 9, 10, 12, 14, 3, 3, 5, 3, 9, 11, 2, 5, 3, 9, 10, 2, 5, 8, 12, 10, 1, 2, 3, 4, 5, 9, 10, 6, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 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