Python Code for ESG–Financial Performance Analysis Using Deep Learning and Network Methods

This repository contains the Python code used to generate all tables and figures presented in the associated research article on ESG–financial performance relationships. The scripts implement data preprocessing, nonlinear dimensionality reduction, and network-based analysis to examine sustainability–performance patterns at the firm level. The code includes routines for data normalization, clustering, similarity-based network construction, and visualization. All tables and figures were generated by the authors using Python-based analyses, ensuring full reproducibility of the empirical results. The repository is intended to support transparency, replicability, and further methodological development in sustainability and sustainable finance research.