Introduction to Data Science Using Python

The most widely used free Python book for people who want to work with data rather than build software. Teaches the language through practical tasks: reading files, scraping web data, calling APIs, and storing results in databases.

Charles R. Severance

Exploratory data analysis taught as a working process: import and clean the data, explore one variable, then pairs, then build models. Every technique is shown as Python code applied to a real national survey dataset.

Allen B. Downey

A complete tutorial on the scientific Python stack, written by the core developers of the libraries themselves. Covers NumPy, matplotlib, SciPy, pandas, scikit-learn, and image processing, moving from first steps to advanced numerical work.

Gael Varoquaux, Emmanuelle Gouillart, Olav Vahtras, Pierre de Buyl