Learn Python: Visualisation using Matplotlib and Seaborn

Standard Course
£400 +VAT
per delegate
Course duration: 1 day

This course covers all you need to know to explore data visually and create report-ready visualisations using the matplotlib and seaborn libraries.

By attending this course, you will:

  • Learn how to create highly customised plots using both pyplot and object-oriented interfaces in matplotlib, as well as seaborn’s additional plotting facilities.
  • Gain a range of techniques to uncover business insight from your data using different visualisation strategies.
  • Understand the interactions between matplotlib and seaborn to write efficient code for stunning visualisations.

Who is it for?

This course is designed for people with prior knowledge of Python who wish to learn how to use the matplotlib and seaborn libraries to create visualisations for data exploration and business reports.


Basic knowledge of Python, as covered by Learn Python: Introduction and Learn Python: pandas for Data Analysis. Including: data types and structures (float, int, str, bool, list, tuple, dict); conditional logic, control flow, and list comprehensions; how to use the Python standard library; basic understanding of NumPy and pandas’ data structures.

What you will learn

  • Introduction to matplotlib and the pyplot module
  • Matplotlib terminology
  • Logic behind graph making
  • Implicit (pyplot) vs explicit (object-oriented) approach
  • Using and understanding matplotlib documentation

  • An introduction to continuous data
  • Coding using implicit and explicit approaches in greater detail
  • How to create different plots, including:
    • Scatter plot
    • Line chart
    • Histogram
    • Boxplot
  • Plotting multiple graphs, sub plots, customising charts, multiple axis objects

  • An introduction to categorical data
  • Bar Charts
  • Customising graphical output
  • A visualization case study – matplotlib in practice

  • What is seaborn?
  • How to install the library
  • The differences in syntax between seaborn and matplotlib
  • Why is it important to understand matplotlib when working with seaborn
  • Structure of the seaborn library
  • Figure-level functions and Axes-level functions
  • Using and understanding seaborn documentation

  • Visualising distributions of data using displot()
  • Exploring relationships between continuous data using relplot() functions
  • Plotting categorical data using catplot()
  • Additional customisations and plotting options

Learn Python: Visualisation using Matplotlib and Seaborn

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