COM6018 Data Science with Python

Week 5: Using Matplotlib

Jon Barker

Copyright © 2023–2025 Jon Barker, University of Sheffield. All rights reserved.

In this lab

• Reading datasets from CSV files
• Making complex figures with subplots
• Exploring distributions with scatter plots
• Generating pie charts and stackplots
• Plotting geographic data
• Plotting a contour map of a mathematical function

The Task

• You are provided with some complex datasets.

• For each dataset you are shown a plot or plots that you need to reproduce.

• You need to write Matplotlib code to produce something as similar as possible.

The Data

We will be using data from three separate datasets

• data/renewable_energy.csv - Renewable energy production in the UK

  https://ourworldindata.org/renewable-energy

• data/iris.csv - Measurements of iris flowers

  https://archive.ics.uci.edu/ml/datasets/iris

• data/wind_farms_uk.csv - Locations of wind farms in the UK

https://en.wikipedia.org/wiki/List_of_offshore_wind_farms_in_the_United_Kingdom

Plot 1

Global renewable energy production over time.

Plot 1b

Renewable energy production broken down by region.

Plot 2

The share of renewable energy sources changing over time.

Plot 3

Using the Iris data. Distribution of petal and sepal, lengths and widths.

Plot 4

Using the wind farm data. Location and size of wind farms in the UK.

Plot 5

Visualising the function .

Obtaining the Jupyter Notebook

If you have cloned and pulled the module's GitHub repository then you should see,

materials/labs/
├── 050_using_matplotlib.ipynb
|-- ... etc
├── data
│   ├── renewable_energy.csv
│   ├── iris.csv
│   ├── wind_farms_uk.csv
│   ├── ... etc

The lab is 050_using_matplotlib.ipynb, and it will need the data files data/renewable_energy.csv, data/iris.csv and data/wind_farms_uk.csv,

Or you can download the notebook and data via links on Blackboard.

Getting Help

• If you are stuck just raise a hand to ask for help.

• Feel free to discuss the lab with your neighbours.

• Re-read the Matplotlib tutorial notes

  • In the Git repo at tutorials/050_Introducing_Matplotlib.ipynb
  • or online at https://uos-com-6018.github.io/COM6018

• Use the Matplotlib https://matplotlib.org/ documentation for reference.