scientistmetrics 0.0.3

Python package for metrics and scoring : quantifying the quality of predictions

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