π» Week 09 Lab
Data Exploration and Visualisation Workshop
By the end of this lab, you should be able to: i) Recognise when to use bar plots, box plots, and error bars appropriately, ii) Explain why pie charts often fail for comparisons, iii) Apply visualisation principles from research to your βοΈ Mini-Project 2 work, iv) Critique visualisation choices using evidence-based guidelines.
This lab builds on the π₯οΈ Week 09 Lecture discussion of exploratory data analysis principles. Your class teacher will facilitate a conversation about DOs and DONβTs of visualisation to help you make better choices for your βοΈ Mini-Project 2.
π Preparation
- Attend the π₯οΈ Week 09 Lecture
- Make as much progress as feasibly possible on your βοΈ Mini-Project 2
π£οΈ Lab Roadmap
| Part | Activity Type | Focus | Outcome |
|---|---|---|---|
| Part I | π€ TEACHING MOMENT | Chart types: whatβs good vs bad | Understand when to use different visualisation types |
| Part II | π― ACTION POINTS | Hall of Fame/Shame | Share examples and critique visualisations |
π NOTE: Whenever you see a π€ TEACHING MOMENT, this means your class teacher deserves your full attention!
Part I: Chart Types Discussion (60 min)
Your class teacher will discuss examples of what types of data work well with different chart types and what they are bad for. They will use Friends Donβt Let Friends Make Bad Graphs and may reference other visualisation resources.
Your class teacher will cover these four points:
Use bar plots for counting stuff, not for averages
To communicate uncertainty, use box plots or error bars (but understand what they represent: Q1/Q3, median, etc.)
Pie charts are confusing and often not a good idea
Donβt plot too many line plots (spaghetti plots). At best, highlight one versus the rest.
Part II: Hall of Fame/Shame (30 min)
π― ACTION POINTS
Go to the
#socialchannel on Slack and locate the threads titled βHall of Fameβ and βHall of ShameβShare a screenshot or link to your favourite and least favourite visualisations
Be ready to explain your choices using the principles discussed in Part I
Appendix | Resources, links, etc.
Visualisation Resources
- Data Viz Catalogue - Comprehensive guide to chart types
- Seaborn Gallery - Examples of seaborn plots
- Matplotlib Gallery - Examples of matplotlib visualisations
- Data to Viz - Decision tree for choosing chart types
- Friends Donβt Let Friends Make Bad Graphs - Research-based visualisation guidelines
Useful Links
- π₯οΈ Week 09 Lecture
- βοΈ Mini-Project 2 (due W10)
- π Syllabus
Support this week
- Slack: Post questions to
#help - Office Hours: Book via StudentHub
