Intro to Python

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Welcome to the Introduction to Python course

1 General Information

This course will cover basic concepts and give you the confidence to work independently in the Python programming language. No prior coding or statistical knowledge is assumed, however you should be confident using basic computer software.

The course is split into chapters; each chapter will build upon the previous one. It will emphasis the application of skills, building confidence and resilience in programming.

It is essential that you have frequent opportunities to practice what you have learnt from the course.

2 Software Requirements

  • Python (Version 3.7 or higher)
  • Anaconda (it is a Python distribution that simplifies package management and deployment. It comes pre-installed with most of the necessary data analysis libraries and tools.)

3 Course Overview

Chapter 1 - Getting started with Python - Background of Python - Interacting with Jupyter - Accessing Help - Interacting with Python in other ways

Chapter 2 - Data Structure - Understand variable - Be familiar with different datatype in Python - Understand different type of data structure - Learn about Pandas package and use them - How to access help

Chapter 3 - Import and Export - Understand script structure and packages - Be able to load and install a package - Be able to check package versions and R version - Be able to import data from multiple formats - Be able to inspect loaded data and select elements within the data frame - Be able to export data - Be able to explore data

Chapter 4 - Dataframe - Be able to explore to datasets - Be able to sort data - Be able to subset data - Understand how to filter dataset on single and multiple conditions - Be able to derive new columns - Understand different merging techniques - Be able to merge datasets

Chapter 5 - Exploratory Data Analysis - Learn about copies and views - Understand how to update values - Be able to change column names - Understand different approach of handling missing data - Understand what tidy data is

Chapter 6 - Summary Statistics & Aggregation - Describe numeric and categorical data - Aggregate and data

Chapter 7 - Case Study

Chapter 8 - Control Flow & Loop

Chapter 9 - Comprehension List

Chapter 10 - Functions