Welcome to ESTYP Documentation’s documentation!

Hello, my name is Esteban Rucán and I glad to share this project with you. I’m a data scientist from Chile and I’m interested in the development of tools for the analysis of data. Always I’m looking for new ways to improve my skills and I think that the best way to do it is sharing my knowledge with others. I hope that this project will be useful for you.

ESTYP (Extended Statistical Toolkit Yet Practical) is a Python library that serves as a multifaceted toolkit for statistical analysis:

  • The testing module encompasses a wide range of statistical tests, including t-tests, chi-squared tests, and correlation tests, providing robust methods for data comparison and validation. These functions are inspired by their analogs in R software, ensuring user-friendliness.

  • In the linear_model module, users can find functionalities related to logistic regression, including variable selection techniques and additional methods for calculating confidence intervals and p-values. This module enhances the capabilities of traditional logistic regression analysis in scikit-learn and ensuring convergence in cases that statmodels can’t afford.

  • The cluster module is designed to assist in clustering analysis, offering tools to identify the optimal number of clusters using methods like the elbow or silhouette techniques.

Together, these modules form a comprehensive and practical statistical toolkit that caters to various analytical needs.

This documentation is also powered by Jupyter. You can start using the ESTYP library by installing it.

Indices and tables