Training Course Details

Data Visualisation with Python

Data Visualisation with Python

Course Level: Intermediate

Python has a number of packages for the effective creation of graphics to communicate your data insights. This course will examine two popular libraries for creating static 2D plots: Matplotlib and Seaborn. During the training session, we’ll cover plotting basics and customisation of figures with Matplotlib, before moving onto complex statistical visualisations with Seaborn.

Data Visualisation with Python

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Course Details

  • Course Outline
  • Learning Outcomes
  • Materials
  • Prior Knowledge

Course Outline

  • Matplotlib: Introduction to the most widely used visualisation library for Python, covering basic plotting and formatting.
  • Plot building: Using Matplotlib’s object-oriented interface to build more complex plots made up of multiple plot panels.
  • Customisation: Creating visually-appealing figures by customising fonts, axes and colours, and defining custom style sheets.
  • Seaborn: Introduction to Seaborn, a very useful graphics package built on top of Matplotlib to aid in easy creation of beautiful statistical graphs.
  • Statistical visualisation: Exploring your data using Seaborn’s statistical functions, including regression models, kernel density estimation, bivariate distributions and pairwise plots.

Learning Outcomes

By the end of the course, participants will be able to…

  • use a range of techniques for communicating their data insights
  • create beautiful graphics with concise code
  • compose complex visualisations as well as standard displays such as scatter plots, histograms, boxplots and more


Prior Knowledge

This course assumes you have some basic familiarity with Python programming and data structures including Pandas data objects. Completion of the Introduction to Python course or similar experience would be sufficient.

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