Learn Enough Python to Be Dangerous: Software Development, Flask Web Apps, and Beginning Data Science with Python

Cover
Half Title
Title Page
Copyright Page
Contents
Preface
Acknowledgments
About the Author
Chapter 1 Hello, World!
	1.1 Introduction to Python
		1.1.1 System Setup and Installation
	1.2 Python in a REPL
		1.2.1 Exercises
	1.3 Python in a File
		1.3.1 Exercise
	1.4 Python in a Shell Script
		1.4.1 Exercise
	1.5 Python in a Web Browser
		1.5.1 Deployment
	1.5.2 Exercises
Chapter 2 Strings
	2.1 String Basics
		2.1.1 Exercises
	2.2 Concatenation and Interpolation
		2.2.1 Formatted Strings
		2.2.2 Raw Strings
		2.2.3 Exercises
	2.3 Printing
		2.3.1 Exercises
	2.4 Length, Booleans, and Control Flow
		2.4.1 Combining and Inverting Booleans
		2.4.2 Boolean Context
		2.4.3 Exercises
	2.5 Methods
		2.5.1 Exercises
	2.6 String Iteration
		2.6.1 Exercises
Chapter 3 Lists
	3.1 Splitting
		3.1.1 Exercises
	3.2 List Access
		3.2.1 Exercises
	3.3 List Slicing
		3.3.1 Exercises
	3.4 More List Techniques
		3.4.1 Element Inclusion
		3.4.2 Sorting and Reversing
		3.4.3 Appending and Popping
		3.4.4 Undoing a Split
		3.4.5 Exercises
	3.5 List Iteration
		3.5.1 Exercises
	3.6 Tuples and Sets
		3.6.1 Exercises
Chapter 4 Other Native Objects
	4.1 Math
		4.1.1 More Advanced Operations
		4.1.2 Math to String
		4.1.3 Exercises
	4.2 Times and Datetimes
		4.2.1 Exercises
	4.3 Regular Expressions
		4.3.1 Splitting on Regexes
		4.3.2 Exercises
	4.4 Dictionaries
		4.4.1 Dictionary Iteration
		4.4.2 Merging Dictionaries
		4.4.3 Exercises
	4.5 Application: Unique Words
		4.5.1 Exercises
Chapter 5 Functions and Iterators
	5.1 Function Definitions
		5.1.1 First-Class Functions
		5.1.2 Variable and Keyword Arguments
		5.1.3 Exercises
	5.2 Functions in a File
		5.2.1 Exercise
	5.3 Iterators
		5.3.1 Generators
		5.3.2 Exercises
Chapter 6 Functional Programming
	6.1 List Comprehensions
		6.1.1 Exercise
	6.2 List Comprehensions with Conditions
		6.2.1 Exercise
	6.3 Dictionary Comprehensions
		6.3.1 Exercise
	6.4 Generator and Set Comprehensions
		6.4.1 Generator Comprehensions
		6.4.2 Set Comprehensions
		6.4.3 Exercise
	6.5 Other Functional Techniques
		6.5.1 Functional Programming and TDD
		6.5.2 Exercise
Chapter 7 Objects and Classes
	7.1 Defining Classes
		7.1.1 Exercises
	7.2 CustomIterators
		7.2.1 Exercise
	7.3 Inheritance
		7.3.1 Exercise
	7.4 Derived Classes
		7.4.1 Exercises
Chapter 8 Testing and Test-Driven Development
	8.1 Package Setup
		8.1.1 Exercise
	8.2 Initial Test Coverage
		8.2.1 A Useful Passing Test
		8.2.2 Pending Tests
		8.2.3 Exercises
	8.3 Red
		8.3.1 Exercise
	8.4 Green
		8.4.1 Exercise
	8.5 Refactor
		8.5.1 Publishing the Python Package
		8.5.2 Exercises
Chapter 9 Shell Scripts
	9.1 Reading from Files
		9.1.1 Exercises
	9.2 Reading from URLs
		9.2.1 Exercises
	9.3 DOM Manipulation at the Comm and Line
		9.3.1 Exercises
Chapter 10 A Live Web Application
	10.1 Setup
		10.1.1 Exercise
	10.2 Site Pages
		10.2.1 Exercises
	10.3 Layouts
		10.3.1 Exercises
	10.4 Template Engine
		10.4.1 Variable Titles
		10.4.2 Site Navigation
		10.4.3 Exercises
	10.5 Palindrome Detector
		10.5.1 Form Tests
		10.5.2 Exercises
	10.6 Conclusion
Chapter 11 Data Science
	11.1 Data Science Setup
	11.2 Numerical Computations with NumPy
		11.2.1 Arrays
		11.2.2 Multidimensional Arrays
		11.2.3 Constants, Functions, and Linear Spacing
		11.2.4 Exercises
	11.3 Data Visualization with Matplotlib
		11.3.1 Plotting
		11.3.2 Scatter Plots
		11.3.3 Histograms
		11.3.4 Exercises
	11.4 Introduction to Data Analysis with pandas
		11.4.1 Handcrafted Examples
		11.4.2 Exercise
	11.5 pandas Example: Nobel Laureates
		11.5.1 Exercises
	11.6 pandasExample:Titanic
		11.6.1 Exercises
	11.7 MachineLearningwithscikit-learn
		11.7.1 LinearRegression
		11.7.2 Machine-LearningModels
		11.7.3 k-MeansClustering
		11.7.4 Exercises
	11.8 FurtherResourcesandConclusion
Index
	A
	B
	C
	D
	E
	F
	G
	H
	I
	J
	K
	L
	M
	N
	O
	P
	R
	S
	T
	U
	V
	W
	X
	Y
	Z