Python Libraries
Ignacio Cervera, Natalia Cassinello · 2026
This chapter introduces the main Python libraries used throughout the book, highlighting how they simplify programming by providing reliable, pre-built tools for common tasks. It presents a structured overview of key libraries across different domains, including data manipulation (Pandas, NumPy), scientific computing and econometrics (SciPy, Statsmodels), optimization (PuLP), financial analysis (Yfinance, Empyrical), web interaction (Requests, OS), and visualization (Matplotlib, Seaborn). Each library is briefly described in terms of its core functionality and typical applications, emphasizing how combining general-purpose and specialized packages enable efficient, practical problem-solving in finance and data analysis.