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Data visualisation with Python


Python has a wide range of libraries for plotting and visualising data. Many of these are excellent, but it can be hard for a newcomer to know where to start.

We will introduce the range of options available, then do hands-on visualisation exercises with some popular libraries: Matplotlib, Seaborn, and Altair. Seaborn builds on Matplotlib to easily create beautiful statistical visualisations. Altair is intended for interactive visualisation and makes it easy to create complex responsive visualisations.

Learning Objectives

At the end of this workshop you should be able to:

  • be aware of the landscape of visualisation libraries
  • create visualisations of data in Matplotlib, Seaborn and Altair
  • know how to search the documentation for further visualisation functions


This workshop is designed for participants with a basic knowledge of Python. The "Data tidying with Python and Pandas" workshop is recommended as a prerequisite.

Attendees are required to bring their own laptop computers.

You should install the Anaconda Python distribution before attending:

  • Go to:
  • Select your operating system
  • Select the Python 3.7 (not 2.7) option to download and install. This is a large download (over 600MB). If you aren't able to install it prior to the workshop, we can work around this, but please contact us beforehand.

Notebooks and Data

This workshop is implemented as a set of Jupyter Notebooks, and we will use (and introduce) Jupyter during the workshop.

You can find all notebooks and data in this github repository. For this workshop, we will use the Seaborn_Matplotlib.ipynb and Altair.ipynb notebooks.