A Python Tutorial for Data Scientists
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Contents:
1. Introduction
1.1. What is a Programming Language?
1.2. Why Python?
1.3. Installing Python and Jupyter
1.4. How to Use Python: Jupyter Notebooks
1.4.1. Jupyter Notebooks from the Command Line
1.4.2. How to Use Python: Other
1.5. Final Introductory Notes
2. Hello World!
2.1. Your First Program
2.1.1. The Print Function
2.2. Python as a Calculator
2.3. Exercise 2.1
3. Data in Python
3.1. Variables in Python
3.1.1. A Few Notes about Jupyter Notebooks
3.1.2. A Few Notes about Variable Names
3.1.3. Exercise 3.1
3.2. Python Data Types
3.2.1. Integers and Floats
3.2.2. Booleans
3.2.3. Strings
3.2.3.1. Operations with Strings
3.2.3.2. Special Characters
3.2.3.3. String Formatting
3.2.3.4. String Functions
3.2.4. Converting Data Types
3.2.5. Exercise 3.2
4. Lists and Arrays
4.1. Lists
4.1.1. Accessing List Elements
4.1.2. Exercise 4.1
4.1.3. Modifying Lists
4.1.3.1. Modifying Elements
4.1.3.2. Adding Elements
4.1.3.3. Removing Elements
4.1.3.4. Copying Lists
4.1.4. Other List Information
4.1.4.1. The
list()
Function
4.1.4.2. Lists have Length
4.1.4.3. The Range Function
4.1.4.4. Useful List Functions
4.1.5. Exercise 4.2
4.2. Numpy Arrays
4.2.1. Importing Packages in Python
4.2.2. Numpy Arrays
4.2.2.1. Array Size, Dimension, and Type
4.2.2.2. Accessing Array Elements
4.2.2.3. Useful Array Functions
4.2.3. Exercise 4.3
5. Loops
5.1. For Loops
5.1.1. Looping by Element
5.1.2. Looping by Index
5.1.2.1. The
enumerate()
Iterator
5.1.3. Nested Loops
5.2. Exercise 6.1
5.3. While Loops
5.3.1. Conditional Statements in Loops
5.4. Exercise 6.2
5.5. Optional: List Expressions
6. Conditional Statements
6.1. Logical Comparisons
6.1.1. Comparison Operators
6.1.2. Checking Types
6.2. Exercise 5.1
6.3. If-Else Statements
6.3.1. Basic Structure
6.3.2. Multiple Comparisons:
elif
6.4. Exercise 5.2
6.5. Masking Arrays
6.5.1. Boolean Arrays are Masks
6.5.2.
any()
and
all()
6.6. Exercise 5.3
7. Functions
7.1. What is a Function
7.2. Function Syntax
7.2.1. Positional Arguments
7.2.2. Keyword Arguments
7.3. Exercise 7.1
8. Plotting
8.1. Matplotlib
8.1.1. Line and Scatter Plots
8.1.2. Figures and Axes
8.1.3. Formatting Figures
8.2. Seaborn
9. Reading and Writing Data
10. Dictionaries
11. Random Numbers in Python
12. Classes
A Python Tutorial for Data Scientists
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8. Plotting
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8. Plotting
¶
PLOTTING IS SUPER IMPORTANT
8.1. Matplotlib
¶
8.1.1. Line and Scatter Plots
¶
8.1.2. Figures and Axes
¶
8.1.3. Formatting Figures
¶
8.2. Seaborn
¶
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