A Whirlwind Tour of Python

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Table of Contents
Chapter 1. A Whirlwind Tour of Python
	Introduction
	Using Code Examples
		Installation and Practical Considerations
		The Zen of Python
	How to Run Python Code
	A Quick Tour of Python Language Syntax
		Comments Are Marked by #
		End-of-Line Terminates a Statement
		Semicolon Can Optionally Terminate a Statement
		Indentation: Whitespace Matters!
		Whitespace Within Lines Does Not Matter
		Parentheses Are for Grouping or Calling
		Finishing Up and Learning More
	Basic Python Semantics: Variables and Objects
		Python Variables Are Pointers
		Everything Is an Object
	Basic Python Semantics: Operators
		Arithmetic Operations
		Bitwise Operations
		Assignment Operations
		Comparison Operations
		Boolean Operations
		Identity and Membership Operators
	Built-In Types: Simple Values
		Integers
		Floating-Point Numbers
		Complex Numbers
		String Type
		None Type
		Boolean Type
	Built-In Data Structures
		Lists
		Tuples
		Dictionaries
		Sets
		More Specialized Data Structures
	Control Flow
		Conditional Statements: if, elif, and else
		for loops
		while loops
		break and continue: Fine-Tuning Your Loops
		Loops with an else Block
	Defining and Using Functions
		Using Functions
		Defining Functions
		Default Argument Values
		*args and **kwargs: Flexible Arguments
		Anonymous (lambda) Functions
	Errors and Exceptions
		Runtime Errors
		Catching Exceptions: try and except
		Raising Exceptions: raise
		Diving Deeper into Exceptions
		try…except…else…finally
	Iterators
		Iterating over lists
		range(): A List Is Not Always a List
		Useful Iterators
		Specialized Iterators: itertools
	List Comprehensions
		Basic List Comprehensions
		Multiple Iteration
		Conditionals on the Iterator
		Conditionals on the Value
	Generators
		Generator Expressions
		Generator Functions: Using yield
		Example: Prime Number Generator
	Modules and Packages
		Loading Modules: the import Statement
		Importing from Python’s Standard Library
		Importing from Third-Party Modules
	String Manipulation and Regular Expressions
		Simple String Manipulation in Python
		Format Strings
		Flexible Pattern Matching with Regular Expressions
	A Preview of Data Science Tools
		NumPy: Numerical Python
		Pandas: Labeled Column-Oriented Data
		Matplotlib: MATLAB-style scientific visualization
		SciPy: Scientific Python
		Other Data Science Packages
	Resources for Further Learning
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