A Whirlwind Tour of Python

Description

Cover Additional Resources Copyright 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 About the Author