Python Real-World Data Science 无水印pdf

Python

Real-World

Data

Science

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Python: Real-World Data Science

Table of Contents
Python: Real-World Data Science
Meet Your Course Guide
What's so cool about Data Science?
Course Structure
Course Journey
The Course Roadmap and Timeline
1. Course Module 1: Python Fundamentals
1. Introduction and First Steps – Take a Deep Breath
A proper introduction
Enter the Python
About Python
Portability
Coherence
Developer productivity
An extensive library
Software quality
Software integration
Satisfaction and enjoyment
What are the drawbacks?
Who is using Python today?
Setting up the environment
Python 2 versus Python 3 – the great debate
What you need for this course
Installing Python
Installing IPython
Installing additional packages
How you can run a Python program
Running Python scripts
Running the Python interactive shell
Running Python as a service
Running Python as a GUI application
How is Python code organized
How do we use modules and packages
Python's execution model

Names and namespaces
Scopes
Guidelines on how to write good code
The Python culture
A note on the IDEs
2. Object-oriented Design
Introducing object-oriented
Objects and classes
Specifying attributes and behaviors
Data describes objects
Behaviors are actions
Hiding details and creating the public interface
Composition
Inheritance
Inheritance provides abstraction
Multiple inheritance
Case study
3. Objects in Python
Creating Python classes
Adding attributes
Making it do something
Talking to yourself
More arguments
Initializing the object
Explaining yourself
Modules and packages
Organizing the modules
Absolute imports
Relative imports
Organizing module contents
Who can access my data?
Third-party libraries
Case study
4. When Objects Are Alike
Basic inheritance
Extending built-ins
Overriding and super
Multiple inheritance

The diamond problem
Different sets of arguments
Polymorphism
Abstract base classes
Using an abstract base class
Creating an abstract base class
Demystifying the magic
Case study
5. Expecting the Unexpected
Raising exceptions
Raising an exception
The effects of an exception
Handling exceptions
The exception hierarchy
Defining our own exceptions
Case study
6. When to Use Object-oriented Programming
Treat objects as objects
Adding behavior to class data with properties
Properties in detail
Decorators – another way to create properties
Deciding when to use properties
Manager objects
Removing duplicate code
In practice
Case study
7. Python Data Structures
Empty objects
Tuples and named tuples
Named tuples
Dictionaries
Dictionary use cases
Using defaultdict
Counter
Lists
Sorting lists
Sets
Extending built-ins