Metadata-Version: 2.1
Name: scientistmetrics
Version: 0.0.1
Summary: Python package for calculating correlation amongst categorical variables
Home-page: https://github.com/enfantbenidedieu/scientistmetrics
Author: Duverier DJIFACK ZEBAZE
Author-email: duverierdjifack@gmail.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE

# scientistmetrics

## About scientistmetrics

**scientistmetrics** is a `Python` package for calculating correlation amongst categorical variables.

## Why scientistmetrics?

The function provides the option for computing one of six measures of association between two nominal variables from the data given in a 2d contingency table: 
* Pearson's chi-squared test : https://en.wikipedia.org/wiki/Pearson%27s_chi-squared_test
* Phi coefficient : https://en.wikipedia.org/wiki/Phi_coefficient
* G-test: https://en.wikipedia.org/wiki/G-test
* Cramer's V : https://en.wikipedia.org/wiki/Cramer's_V
* Tschuprow's T : https://en.wikipedia.org/wiki/Tschuprow's_T
* Pearson contingency coefficient : https://www.statisticshowto.com/contingency-coefficient/

Notebook is availabled.

## Installation

### Dependencies

scientistmetrics requires :

```
Python >=3.10
Numpy >=1.23.5
Pandas >=1.5.3
Plotnine >=0.10.1
Scipy >=1.10.1
```

## User installation

You can install scientistmetrics using `pip` :

```
pip install scientistmetrics
```

## Author

Duvérier DJIFACK ZEBAZE

