Author: Christian Peccei Author Email: [email protected] Python 3.x compatibility: Maciej Witkowiak, [email protected] Version: 1.1 Homepage: http://www.christianpeccei.com/projects/textmining

#Overview

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

#Installation

Extract the .zip file and run:

python setup.py install

#Installation directly from github

Run:

pip install git+https://github.com/ytmytm/python-textmining.git

#Documentation

Please see the docstrings in the functions themselves and the 'examples' subdirectory for actual applications of the various functions.