COMP0034: Code for activities in week 1
Using Jupyter notebooks
You should have a preferred Jupyter notebook environment set up from COMP0035, if not then use the Binder cloud service below. This creates a virtual coding environment in the cloud for you to use so you don't need to install anything on your machine. It will take a few minutes for this environment to be created, once it is ready you will see a page that looks a little like this one with a list of files.
If you are using PyCharm Professional then refer to the documentation which explains how to use jupyter notebooks.
Once you have the notebook open, you should follow the instructions in the notebook itself.
You can access the notebooks using Binder at https://mybinder.org/v2/gh/nicholsons/comp0034_week1.git/master?. You will be able to make changes to the code during your Binder sessions and see the effect of your changes, however when you exit Binder any changes that you have made will not be saved. If you wish to save changes that you make to access at another time then the menu bar within the Binder session provides an option to download the notebook to your computer.
Activity 1.3 Introduction to data visualisation Jupyter notebook
The jupyter notebook provides an introduction to visualising data.
The introductory video in the notebook is a TED talk given by Hans Rosling called 'The best stats you have ever seen'.
The code examples in the notebook make use of the Plotly Express library. This library provides direct access to the Gapminder data set. There are also examples for the use of the Gapminder data in their help and documentation.
The Gapminder data can also be accessed freely at Gapminder.org. The 'math_achievement_8th_grade.csv' file in this repository was downloaded from Gapminder.
Activity 1.7 Introduction to pie and line charts using matplotlib
This notebook introduces you to using matplotlib and pandas to create charts.
It also introduces bar and pie charts as a means of representing data.
Feedback and corrections to files in this repository
Please report suggestions or errors at https://github.com/nicholsons/comp0034_week1/issues.