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Index
Python Crash Course
Introduction
Who is meant to read this book?
What will you learn from this book?
Chapter 1: Python Programming
What is Python Programming?
How to use Python Programming
Who can use Python Programming?
What can you do with Python Programming?
Importance of Python Programming in the Economics
Importance of Python Programming at the Workplace
How can you earn using Python Programming?
Chapter 2: Python Programming Concepts
Basic Concepts in Python Programming
The Terms used in Python Programming
How to start Python Programming for Data Analysis
How to Install Python
Chapter 3: Python Programming Lessons
How to Learn about Python Programming
Where can you learn about Python Programming?
What is the Cost of Getting a Python Certification?
The Best Python Course
What Job can you get with Python?
Chapter 4: Operating Systems
Python on Linux
Python on OS X
Python on Windows
Python Troubleshooting
Chapter 5: List
What is a List?
How to Change Elements
How to Remove Element
How to Add Elements
How to Organize a List
Chapter 6: Variable and Simple Data Types
Dictionaries
Functions
Classes
Testing your Code
File and Exceptions
User Input and while Loops
Chapter 7: Data Visualization
How to Generate Data
How to Download Data
How to Work with APIs
Chapter 8: Web Applications
How to Work with Django
User Accounts
How to Style and Deploy an App
Conclusion
Python for Data Analysis
Introduction
Chapter 1: What is a Data Analysis
What is Data Analytics?
Understanding How Data Analytics Works
The Different Types of Data Analytics
Chapter 2: Reasons to Work with a Data Analysis
Chapter 3: How Does Python Fit Into This?
Chapter 4: Some of the Basic Codes in Python
The Keywords
Python Comments
Python as an OOP Language
How to Write a Class
Python Functions
Python Variables
Lists vs. Dictionaries
Creating a Simple Loop
The If Else Statement in Decision Control
Can I Create an Inheritance?
Chapter 5: What is the NumPy Library
Understanding More About NumPy
Chapter 6: Taking It Further with Pandas
How to Install Pandas
The Data Structures in Pandas
Chapter 7: The Importance of Cleaning and Organizing the Data
Collecting the Data
Organizing the Data
Dealing with the Outliers
Filling in Missing Data
How to Deal with Duplicates
Chapter 8: Training, Testing, and Repeating
Picking Out the Algorithms to Use
Training Our Data
Testing the Data
Repeat the Process
Chapter 9: Machine Learning and How It Fits Into Our Data Analysis
What is Machine Learning?
How Does Machine Learning Work with Data Analysis?
Supervised Machine Learning
Unsupervised Machine Learning
Reinforcement Machine Learning
Chapter 10: Presenting the Results
Conclusion
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