To tap into the power of Python's open data science stack—including NumPy, Pandas, Matplotlib, Scikit-learn, and other tools—you first need to understand the syntax, semantics, and patterns of the Python language. This report provides a brief yet comprehensive introduction to Python for engineers, researchers, and data scientists who are already familiar with another programming language.

Author Jake VanderPlas, an interdisciplinary research director at the University of Washington, explains Python’s essential syntax and semantics, built-in data types and structures, function definitions, control flow statements, and more, using Python 3 syntax.

You’ll explore:

Python syntax basics and running Python code
Basic semantics of Python variables, objects, and operators
Built-in simple types and data structures
Control flow statements for executing code blocks conditionally
Methods for creating and using reusable functions
Iterators, list comprehensions, and generators
String manipulation and regular expressions
Python’s standard library and third-party modules
Python’s core data science tools
Recommended resources to help you learn more.