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COMP0015 Data Analysis

Here you will find a number of self-study activities. The first is an introduction to Data Visualisation. Its purpose is to give you some insight into one of the many ways that the skills you will learn on your undergraduate course can be used in 'real' life.

Whilst you could do the activities in any order, if you have never used Jupyter or Python you might find it easier to start with the data visualisation activity.

Getting started

These activities use a cloud service Jupyter notebook.

When you open one of the following links, the cloud service 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 you have the notebooks open using one of the following methods, you should follow the instructions in the notebook itself.

1. Using the notebook in the Binder cloud service (no account required)

If you do not want to create an account, then you can access the notebooks using a service called Binder. Please note that, using this option, once you exit from Binder any work will not be saved. If you wish to save your work you will need to save and download the notebook to your own computer before you exit Binder.

To access the notebooks use the following links, remember it may take a few minutes to start:

Data analysis with pandas

Data visualisation with pandas and plotly

2. Using a locally installed Python Jupyter notebook environment

If you already have a locally installed Python development environment and code editor, then you may be able to work out how to use the Jupyter notebook on your own machine. You will need to investigate options for doing this yourself depending on your own setup. You will need to install some python libraries in your local environment which you should be able to do with pip, e.g.:

pip install pandas
pip install plotly

Getting help

Ask for help by posting a message in the Discussion forum.

Feedback and corrections

Please report suggestions or errors here.

Data protection and privacy

You should not save any personal data in a notebook. Personal data is any data that could be used to identify you.

Information on privacy for the Binder service can be found here.

Information on privacy for the Microsoft Azure Notebooks service can be found here.


The introductory video in the data visualisation 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 The 'math_achievement_8th_grade.csv' file in this repository was downloaded from Gapminder.


basic data analysis in python



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