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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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