Instructor-led training

Advanced Python 3 (4 Day Course)

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What you'll learn

In this Python training course, students already familiar with Python programming will learn advanced Python techniques such as IPython Notebook, the Collections module, mapping and filtering, lamba functions, advanced sorting, writing object-oriented code, testing and debugging, NumPy, pandas, matplotlib, regular expressions, Unicode, text encoding and working with databases, CSV files, JSON and XML. This advanced Python course is taught using Python 3, however, differences between Python 2 and Python 3 are noted.

Prerequisites

Basic Python programming experience. In particular, you should be very comfortable with: working with strings; working with lists, tuples and dictionaries; loops and conditionals; and writing your own functions. Experience in the following areas would be beneficial: some exposure to HTML, XML, JSON, and SQL.

Course Outline

IPython Notebook

Getting Started with IPython Notebook

Creating Your First IPython Notebook

IPython Notebook Modes

Useful Shortcut Keys

Markdown

Magic Commands

Getting Help

Advanced Python Concepts

Advanced List Comprehensions

Collections Module

Mapping and Filtering

Lambda Functions

Advanced Sorting

Unpacking Sequences in Function Calls

Modules and Packages

Working with Data

Databases

CSV

Getting Data from the Web

HTML

XML

JSON

Classes and Objects

Creating Classes

Attributes, Methods and Properties

Extending Classes

Documenting Classes

Static, Class, Abstract Methods

Decorator

Testing and Debugging

Creating Simulations

Testing for Performance

The unittest Module

NumPy

One-dimensional Arrays

Multi-dimensional Arrays

Getting Basic Information about an Array

NumPy Arrays Compared to Python Lists

Universal Functions

Modifying Parts of an Array

Adding a Row Vector to All Rows

Random Sampling

pandas

Series and DataFrames

Accessing Elements from a Series

Series Alignment

Comparing One Series with Another

Element-wise Operations

Creating a DataFrame from NumPy Array

Creating a DataFrame from Series

Creating a DataFrame from a CSVl

Getting Columns and Rows

Cleaning Data

Advanced Python

Combining Row and Column Selection

Scalar Data: at[] and iat[]

Boolean Selection

Plotting with matplotlib

Regular Expressions

Regular Expression Syntax

Python's Handling of Regular Expressions

Unicode and Encoding

Encoding and Decoding Files in Python

Converting a File from cp1252 to UTF-8

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