Python package for calculating correlation amongst categorical variables
Project description
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
