Metadata-Version: 2.1
Name: textmining3
Version: 1.1.0
Summary: Text Mining Utilities for Python 3
Home-page: https://github.com/djcomlab/textmining3
Author: David Johnson
Author-email: djcomlab@gmail.com
License: GNU General Public License v3
Keywords: textmining3
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Text Processing :: General
Classifier: Topic :: Text Processing :: Linguistic
Requires-Dist: Click (>=6.0)
Provides-Extra: pandas
Requires-Dist: pandas (>=0.23.4); extra == 'pandas'

===========
textmining3
===========


.. image:: https://img.shields.io/pypi/v/textmining.svg
        :target: https://pypi.python.org/pypi/textmining3

.. image:: https://img.shields.io/travis/djcomlab/textmining3.svg
        :target: https://travis-ci.org/djcomlab/textmining3

.. image:: https://readthedocs.org/projects/textmining3/badge/?version=latest
        :target: https://textmining3.readthedocs.io/en/latest/?badge=latest
        :alt: Documentation Status




Text Mining Utilities for Python 3


* Free software: GNU General Public License v3
* Documentation: https://textmining3.readthedocs.io.
* Requires Python >= 3.6


Features
--------

This package contains a variety of useful functions for text mining in Python 3.

It focuses on statistical text mining (i.e. the bag-of-words model) and makes it
very easy to create a term-document matrix from a collection of documents. This
matrix can then be read into a statistical package (R, MATLAB, etc.) for further
analysis. The package also provides some useful utilities for finding
collocations (i.e. significant two-word phrases), computing the edit distance
between words, and chunking long documents up into smaller pieces.

The package has a large amount of curated data (stopwords, common names, an
English dictionary with parts of speech and word frequencies) which allows the
user to extract fairly sophisticated features from a document.

This package does NOT have any natural language processing capabilities such as
part-of-speech tagging. Please see the Python NLTK for that sort of
functionality (plus much, much more).

The original code and documentation is available in PyPI under the package name
`textmining`. This package is a port to Python 3 and published in PyPI under the package
name textmining3, and is based on the original.


Credits
-------
The original `textmining` 1.0 package code was authored by Christian Peccei <cpeccei@hotmail.com>

.. _`textmining`: https://pypi.org/project/textmining/1.0/

This package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.

.. _Cookiecutter: https://github.com/audreyr/cookiecutter
.. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage


=======
History
=======

1.1.0 (2018-13-19)
------------------
* Add new feature to export DTM to pandas.DataFrame

1.0.2 (2018-12-19)
------------------
* First port of textmining to Python 3

1.0.0 (2010-01-11)
------------------

* Original release of textmining on PyPI (see https://pypi.org/project/textmining/1.0/)


