Metadata-Version: 2.1
Name: evekeys
Version: 0.0.2
Summary: A set of functions that uses sklearn to conduct a TF-IDF analysis to generate keywords from event-based / grouped textual corpus.
Home-page: https://github.com/lingeringcode/evekeys/
Author: Chris A. Lindgren
Author-email: chris.a.lindgren@gmail.com
License: UNKNOWN
Download-URL: https://github.com/lingeringcode/evekeys/
Keywords: tf-idf,keyword extraction,event-based corpus
Platform: UNKNOWN
Description-Content-Type: text/markdown
Requires-Dist: pandas
Requires-Dist: sklearn
Requires-Dist: tqdm

# 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/](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

<pre>
# 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/*
</pre>

