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.
- 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
Jake VanderPlas is a long-time user and developer of the Python scientific stack. He currently works as an interdisciplinary research director at the University of Washington, conducts his own astronomy research, and spends time advising and consulting with local scientists from a wide range of fields.
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