A Whirlwind Tour of Python

Table of contents

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