https://github.com/djcomlab/textmining3

Text Mining Utilities for Python 3
https://github.com/djcomlab/textmining3

data-science python python3 text-analysis text-mining text-processing

Last synced: about 1 year ago
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Text Mining Utilities for Python 3

• Host: GitHub
• URL: https://github.com/djcomlab/textmining3
• Owner: djcomlab
• License: other
• Created: 2018-10-05T14:46:18.000Z (almost 8 years ago)
• Default Branch: master
• Last Pushed: 2022-12-26T20:46:29.000Z (over 3 years ago)
• Last Synced: 2025-03-10T01:10:21.512Z (over 1 year ago)
• Topics: data-science, python, python3, text-analysis, text-mining, text-processing
• Language: Python
• Homepage:
• Size: 1.77 MB
• Stars: 1
• Watchers: 0
• Forks: 0
• Open Issues: 3
• Metadata Files:
  • Readme: README.rst
  • Changelog: HISTORY.rst
  • Contributing: CONTRIBUTING.rst
  • License: LICENSE

Awesome Lists containing this project

README

          
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textmining3

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.. 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 

.. _`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