Python Training Course

Day One

Setting Up

• Python 2 and Python 3
• Running Snippets of Python Code
• Hello World!

Variables and Simple Data Types

• What Really Happens When You Run hello_world.py
• Variables
  • Naming and Using Variables
  • Avoiding Name Errors When Using Variables
• Strings
  • Changing Case in a String with Methods
  • Combining or Concatenating Strings
  • Adding Whitespace to Strings with Tabs or Newlines
  • Stripping Whitespace
  • Avoiding Syntax Errors with Strings
  • Printing in Python 2
• Numbers
  • Integers
  • Floats
  • Avoiding Type Errors with the str() Function
  • Integers in Python 2
• Comments
  • How Do You Write Comments?
  • What Kind of Comments Should You Write?
• The Zen of Python

3 Introducing Lists

• What Is a List?
  • Accessing Elements in a List
  • Index Positions Start at 0, Not 1
  • Using Individual Values from a List
• Changing, Adding, and Removing Elements
  • Modifying Elements in a List
  • Adding Elements to a List
  • Removing Elements from a List
• Organizing a List
  • Sorting a List Permanently with the sort() Method
  • Sorting a List Temporarily with the sorted() Function
  • Printing a List in Reverse Order
  • Finding the Length of a List
• Avoiding Index Errors When Working with Lists

Day Two4. 5. 6.

4. Working with Lists

• Looping Through an Entire List
  • A Closer Look at Looping
  • Doing More Work Within a for Loop
  • Doing Something After a for Loop
• Avoiding Indentation Errors
  • Forgetting to Indent
  • Forgetting to Indent Additional Lines
  • Indenting Unnecessarily
  • Indenting Unnecessarily After the Loop
  • Forgetting the Colon
• Making Numerical Lists
  • Using the range() Function
  • Using range() to Make a List of Numbers
  • Simple Statistics with a List of Numbers
  • List Comprehensions
• Working with Part of a List
• Slicing a List
• Looping Through a Slice
• Copying a List
• Tuples
• Defining a Tuple
• Looping Through All Values in a Tuple
• Writing over a Tuple
• Styling Your Code
• The Style Guide
• Indentation
• Line Length
• Blank Lines
• Other Style Guidelines

5. if Statements

• A Simple Example
  • Conditional Tests
  • Checking for Equality
  • Ignoring Case When Checking for Equality
  • Checking for Inequality
  • Numerical Comparisons
  • Checking Multiple Conditions
  • Checking Whether a Value Is in a List
  • Checking Whether a Value Is Not in a List
  • Boolean Expressions
• if Statements
  • Simple if Statements
  • if-else Statements
  • The if -elif -else Chain
  • Using Multiple elif Blocks
  • Omitting the else Block
  • Testing Multiple Conditions
• Using if Statements with Lists
  • Checking for Special Items
  • Checking That a List Is Not Empty
  • Using Multiple Lists
• Styling Your if Statements

6. Dictionaries

• A Simple Dictionary
• Working with Dictionaries
  • Accessing Values in a Dictionary
  • Adding New Key-Value Pairs
  • Starting with an Empty Dictionary
  • Modifying Values in a Dictionary
  • Removing Key-Value Pairs
  • A Dictionary of Similar Objects
• Looping Through a Dictionary
  • Looping Through All Key-Value Pairs
  • Looping Through All the Keys in a Dictionary
  • Looping Through a Dictionary’s Keys in Order
  • Looping Through All Values in a Dictionary
• Nesting
  • A List of Dictionaries
  • A List in a Dictionary
  • A Dictionary in a Dictionary

Day Three7.8.9.

7. User Input and while Loops

• How the input() Function Works
  • Writing Clear Prompts
  • Using int() to Accept Numerical Input
  • The Modulo Operator
  • Accepting Input in Python 2.7
• Introducing while Loops
  • The while Loop in Action
  • Letting the User Choose When to Quit
  • Using a Flag
  • Using break to Exit a Loop
  • Using continue in a Loop
  • Avoiding Infinite Loops
• Using a while Loop with Lists and Dictionaries
  • Moving Items from One List to Another
  • Removing All Instances of Specific Values from a List
  • Filling a Dictionary with User Input

  8. Functions

  • Defining a Function
    • Passing Information to a Function
    • Arguments and Parameters
  • Passing Arguments
    • Positional Arguments
    • Keyword Arguments
    • Default Values
    • Equivalent Function Calls
    • Avoiding Argument Errors
  • Return Values
    • Returning a Simple Value
    • Making an Argument Optional
    • Returning a Dictionary
    • Using a Function with a while Loop
  • Passing a List
    • Modifying a List in a Function
    • Preventing a Function from Modifying a List
    • Passing an Arbitrary Number of Arguments
      • Mixing Positional and Arbitrary Arguments
      • Using Arbitrary Keyword Arguments
    • Storing Your Functions in Modules
      • Importing an Entire Module
      • Importing Specific Functions
      • Using as to Give a Function an Alias
      • Using as to Give a Module an Alias
      • Importing All Functions in a Module
    • Styling Functions

    9. Classes

    • Creating and Using a Class
      • Creating the Dog Class
      • Making an Instance from a Class
    • Working with Classes and Instances
      • The Car Class
      • Setting a Default Value for an Attribute
      • Modifying Attribute Values
    • Inheritance
      • The __init__() Method for a Child Class
      • Inheritance in Python 2.7
      • Defining Attributes and Methods for the Child Class
      • Overriding Methods from the Parent Class
      • Instances as Attributes
      • Modeling Real-World Objects
    • Importing Classes
      • Importing a Single Class
      • Storing Multiple Classes in a Modul
      • Importing Multiple Classes from a Module
      • Importing an Entire Module
      • Importing All Classes from a Module
      • Importing a Module into a Module
      • Finding Your Own Workflow
    • The Python Standard Library
    • Styling Classes

Day Four10.11

10. Files and Exceptions

• Reading from a File
• Reading an Entire File
• File Paths
• Reading Line by Line
• Making a List of Lines from a File
• Working with a Files Contents
• Large Files: One Million Digits
• Is Your Birthday Contained in Pi?

11. Testing Your Code

• Testing a Function
  • Unit Tests and Test Cases
  • A Passing Test
  • A Failing Test
  • Responding to a Failed Test
  • Adding New Tests
• Testing a Class
  • A Variety of Assert Methods
  • A Class to Test
  • Testing the AnonymousSurvey Class
  • The setUp() Method

Day FiveVisualisation Project

• Installing matplotlib
  • On Linux
  • On OS X
  • On Windows
  • Testing matplotlib
  • The matplotlib Gallery
• Plotting a Simple Line Graph
  • Changing the Label Type and Graph Thickness
  • Correcting the Plot
  • Plotting and Styling Individual Points with scatter()
  • Plotting a Series of Points with scatter()
  • Calculating Data Automatically
  • Removing Outlines from Data Points
  • Defining Custom Colors
  • Using a Colormap
  • Saving Your Plots Automatically
• Random Walks
• Creating the RandomWalk() Class
• Choosing Directions
• Plotting the Random Walk
• Generating Multiple Random Walks
• Styling the Walk
• Coloring the Points
• Plotting the Starting and Ending Points
• Cleaning Up the Axes
• Adding Plot Points
• Altering the Size to Fill the Screen
• Rolling Dice with Pygal
  • Installing Pygal
  • The Pygal Gallery
  • Creating the Die Class
  • Rolling the Die
  • Analyzing the Results
  • Making a Histogram
  • Rolling Two Dice
  • Rolling Dice of Different Sizes

2.Downloading Data

• The CSV File Format
  • Parsing the CSV File Headers
  • Printing the Headers and Their Positions
  • Extracting and Reading Data
  • Plotting Data in a Temperature Chart
  • The datetime Module
  • Plotting Dates
  • Plotting a Longer Timeframe
  • Plotting a Second Data Series
  • Shading an Area in the Chart
  • Error-Checking
• Mapping Global Data Sets: JSON Format
  • Downloading World Population Data
  • Extracting Relevant Data
  • Converting Strings into Numerical Values
  • Obtaining Two-Digit Country Codes
  • Building a World Map
  • Plotting Numerical Data on a World Map
  • Plotting a Complete Population Map
  • Grouping Countries by Population
  • Styling World Maps in Pygal
  • Lightening the Color Theme

3.Working with APIs

• Using a Web API
  • Git and GitHub
  • Requesting Data Using an API Call
  • Installing Requests
  • Processing an API Response
  • Working with the Response Dictionary
  • Summarizing the Top Repositories
  • Monitoring API Rate Limits
• Visualizing Repositories Using Pygal
  • Refining Pygal Charts
  • Adding Custom Tooltips
  • Plotting the Data
  • Adding Clickable Links to Our Graph
• The Hacker News API