Data Visualisation Using Python

New

The module explores Good Data Visualisation (GDV) and graph creation using Python.

In this module we demystify the principles of data visualisation, using Python software, to help researchers to better understand and reflect how the “5 Principles” of GDV can be achieved. We also examine how we can develop Python’s application in data visualisation beyond analysis. Students will have the opportunity to apply GDV knowledge and skills to data using Python in an online Zoom, self-paced, practical workshop. In addition there will be post-class exercises and a 1-hour asynchronous Q&A forum on Moodle Forum.

• Postgraduate students and staff
• Further details regarding eligibility criteria are available here

No previous knowledge or experience required although some programming experience will be an advantage.

Number of sessions: 2

To explore:

• Why data visualisation is important to trans-disciplinary research(ers); basic concepts/theories on data visualisation and primary challenges in data visualisation so important in today’s big data age

• What can contribute to Good Data Visualisation (GDV), what the “5 Principles” for GDV are and why they are crucial (illustrated with examples)

• How Python can be used for data visualisation to improve data analysis

• How to apply Python to create basic graphs (single line graphs, multiple curves, scattergraphs, etc.) in accordance with

By the end of this module the trainees will be able to:

• Critically appreciate the ‘5 principles’ of GDV, and be able apply these to specific research contexts

• Understand the features and (dis)advantages of mainstream data visualisation tools (e.g. Power BI) and how to seek out the most appropriate context(s) for their use, especially Python’s potential in data visualisation and graph creation

• Plot simple graphs in Python in accordance with the “5 Principles” of good data visualization

The module requires student to attend two 2-hour sessions that consist of a 2-hour presentation and self-paced preparation and post-class exercises and there will also be a 1 hour asynchronous Q&A session on Moodle Forum.

Session 1: consists of a presentation and discussion session via Zoom, with an introduction to key concepts and problems in data visualization, with examples from case studies. There will also be an opportunity for group discussion on the principles of data visualisation and aspects to consider to successfully communicate information using visual methods.

Session 2: consists of an online Zoom workshop where students have the opportunity to apply Python to visualise data and construct different types of graphs.

Students will be expected to have access to their own laptop or PC and ensure a copy of Python software is uploaded before the start of session 2.

Click the "Booking" panel on the left-hand sidebar (on a phone, this will be via a link called Booking/Availability near the top of the page).

Moodle is the 'Virtual Learning Environment' (VLE) that the SSRMP uses to deliver online courses.

SSRMP lecturers use Moodle to make teaching resources available before, during, and/or after classes, and to make announcements and answer questions.

For this reason, it is vital that all SSRMP students enrol onto and explore their course Moodle pages once booking their SSRMP modules via the UTBS, and that they do so before their module begins. Moodle pages for modules should go live around a week before the module commences, but some may be made visible to students, earlier.

For more information, and links to specific Moodle module pages, please visit our website