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A set of functions that uses sklearn to conduct a TF-IDF analysis to generate keywords from event-based / grouped textual corpus.

Project description

evekeys: Isolate keywords from an event-based and custom-grouped textual corpus

By Chris Lindgren chris.a.lindgren@gmail.com

Distributed under the BSD 3-clause license. See LICENSE.txt or http://opensource.org/licenses/BSD-3-Clause for details.

Documentation: https://evekeys.readthedocs.io/en/latest/

Overview

A set of functions that uses scikit-learn to conduct a TF-IDF analysis to isolate keywords from event-based documents. It answers the following questions:

  1. What keywords represent a particular period of content?
  2. What keywords represent a particular group of content from a particular period?

It assumes you have:

  • imported your corpus as a pandas DataFrame,
  • included metadata information, such as a list of dates and list of groups to reorganize your corpus, and
  • pre-processed your documents.

It functions only with Python 3.x and is not backwards-compatible.

Warning: evekeys performs little to no custom error-handling, so make sure your inputs are formatted properly. If you have questions, please let me know via email.

System requirements

  • pandas
  • sklearn
  • tqdm

Installation

pip install evekeys

Known Issues or Limitations

  • Please contact me if you discover any issues.

Example notebooks

  • Coming soon.

Distribution update terminal commands

# Create new distribution of code for archiving
sudo python setup.py sdist bdist_wheel

# Distribute to Python Package Index
python -m twine upload --repository-url https://upload.pypi.org/legacy/ dist/*

Project details


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