semvec/pypi-packages huggingface dataset:
exponema 0.0.1
This package finds the exponent of a value with respect to a given degree
Requires Python: >=3.7

<h2>BRIEF:</h2>
<p>This package finds the exponent of a value with respect to a given degree</p>

<h1>HOW TO USE </h1>:
<p>------> call the funtion : ex(value,degree)</p>
<p>------> NB: value and degree arguments are expeced to be integers</p>

<h2>EXAMPLE:</h2>
<p>from exponema import expon</p>
<p>expon.ex(2,3)</p>
<p>### result 8 </p>
databoy 1.0.0
This is a python package for easily storing, reading and manipulating data.
Requires Python: >=3.7

## DataBoy ##
This is a python module that is tested and has been confirmed to work with python 3.10 and above
===========================================================
Credits: 
Cosmic Dev
===========================================================
This is version 1.0 of this module. More features and thing WILL be added in the future.
That being said. Enjoy!
eurlex2lexparency 1.3
Transforming documents from Eur-Lex to Lexparency

# eurlex2lexparency
Transforming documents from Eur-Lex to Lexparency

## Installation

`pip install eurlex2lexparency`

## Usage

Using this package requires a settings-module on first level,
featuring the definition of the following variables.

| Name                 | Description                                               |
|----------------------|-----------------------------------------------------------|
| LEXPATH              | Filesystem path to store the transformed documents.       |
| CELEX_CONNECT_STRING | To be used by `sqlalchemy.create_engine`                  |
| LANG_2_ADDRESS       | Dictionary, language code to corresponding Lexparency URL |
irrcac 0.4.0
Degree of agreement among raters.
Requires Python: >=3.8,<3.11
Keywords: Chance-corrected agreement coefficients,Inter-rater reliability,Inter-annotator agreement

Chance-corrected Agreement Coefficients
=======================================

.. image:: https://readthedocs.org/projects/irrcac/badge/?version=latest
  :target: https://irrcac.readthedocs.io/en/latest/?badge=latest
  :alt: Documentation Status

.. image:: https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white
  :target: https://github.com/pre-commit/pre-commit
  :alt: pre-commit

.. image:: https://img.shields.io/badge/code%20style-black-000000.svg
  :target: https://github.com/psf/black

The **irrCAC** is a Python package that provides several functions for
calculating various chance-corrected agreement coefficients. This package
closely follows the general framework of inter-rater reliability assessment
presented by Gwet (2014).

The functionality covers calculations for various chance-corrected agreement
coefficients (CAC) among 2 or more raters. Among the CAC coefficients covered
are Cohen's kappa, Conger's kappa, Fleiss' kappa, Brennan-Prediger coefficient,
Gwet's AC1/AC2 coefficients, and Krippendorff's alpha. Multiple sets of weights
are proposed for computing weighted analyses.

The functions included in this package can handle 2 types of input data. Those
types with the corresponding coefficients are in the following list:

1. Contingency Table

  1. Brennar-Prediger
  2. Cohen's kappa
  3. Gwet AC1/AC2
  4. Krippendorff's Alpha
  5. Percent Agreement
  6. Schott's Pi

2. Raw Data

  1. Fleiss' kappa
  2. Gwet AC1/AC2
  3. Krippendorff's Alpha
  4. Conger's kappa
  5. Brennar-Prediger

.. note::
   All of these statistical procedures are described in details in
   Gwet, K.L. (2014,ISBN:978-0970806284):
   "Handbook of Inter-Rater Reliability," 4th edition, Advanced Analytics, LLC.

   This package is a port *(with permission)* to Python of the
   `irrCAC <https://github.com/kgwet/irrCAC>`_ library for R by Gwet, K.L.

.. important::
   This is a **work in progress** and *does not* have (yet) the full
   functionality found in the R library.

Installation
------------
To install the package, run:

.. code:: bash

    pip install irrCAC

Developers
----------
To run the tests, install `poetry <https://python-poetry.org/>`_ and run:

.. code:: bash

    poetry install

Next run:

.. code:: bash

    poetry run pytest

There is also a config file for `tox <https://tox.readthedocs.io/en/latest/>`_
so you can automatically run the tests for various python versions like this:

.. code:: bash

    tox

Documentation
-------------
The documentation of the project is available at the following page:
http://irrcac.readthedocs.io/