Interactive data visualization in Python transforms static charts into dynamic tools for exploration. Using Matplotlib with ipympl in JupyterLab allows zooming, panning, and real-time updates.

Data visualization in Python turns raw numbers into clear, compelling stories. With libraries like Matplotlib and Seaborn, you can create anything from basic charts to polished, presentation-ready ...

This repo contains Python code to generate the global dataset of factor returns, stock returns, and firm characteristics from “Is there a Replication Crisis in Finance?” by Jensen, Kelly, and Pedersen ...