kendall-w

Author: Ugo Loobuyck

Overview

Computes Kendall's coefficient of concordance for inter-annotator agreement in the case of item ranking between more than two annotators.

Installation

To install use pip:

$ pip install kendall-w

Or clone the repo:

$ git clone https://github.com/ugolbck/kendall-w.git
$ python setup.py install

Usage

import kendall_w.kendall_w as kw

annotations = [
        [1, 1, 1, 2],
        [2, 2, 2, 3],
        [3, 3, 3, 1],
    ]

W = kw.compute_w(annotations) # returns 0.4375 (fair overall agreement)

Contributions

All contributions are welcome.

How to help?

1. Fork this repository to your GitHub account
2. Clone the forked repositery to local
3. Code something and push to your branch
4. Create a pull request from your repository

TODO:

• Handle pandas.DataFrame as an input with the instructions in the main file
• Use numpy for faster computation?