Data Visualisation for Our Future Climate

This 3 hour interactive workshop introduces best practices for creating data visualisations, with exercises in R and Python to equip attendees with the practical skills to implement them.

Slides

Data Visualisation for Our Future Climate

Data visualisation can be a very effective method of communicating research findings to broad audiences. However, good data visualisation requires appreciation and careful consideration of your audience, a chart’s purpose, and its technical design elements. It also involves a creative element, where we make choices about the story we want to tell. Our design decisions are then driven by the need to convey that story most effectively to our audience.

By the end of this session, you’ll:

• Understand why data visualisation is an important aspect of research communication,
• Be able to choose an appropriate chart type for a specific audience, and
• Know how to design effective charts that still look good,
• and be able to create effective data visualisations using R and/or Python.

Session plan

• Careers in data visualisation (15 mins): Slides, questions
• Introduction to data visualisation (30 mins): Slides, interactive discussion
• Overview of software for charts (15 mins): Slides, interactive discussion
• BREAK: 10 mins
• Choosing a chart type (50 mins): Live code demonstration in Python, exercise, and discussion
• BREAK: 60 mins
• Styling charts (50 mins): Live code demonstration in R, exercise, and discussion
• Wrapping up and questions (10 mins)

Software prerequisites

For the interactive coding parts of this session, we will be creating some visualisations either using ggplot2 in R or plotnine in Python.

Please make sure you have installed the following packages:

R

• tidyverse

Optional:

• gghighlight
• ggtext
• ggview

Python

• pandas
• matplotlib.pyplot
• plotnine