Week 2 - Visualizing data

Data visualization and interpretation of graphical information πŸ“Š



You have two options for watching the course videos, on YouTube or on MediaHopper. You can also find a playlists for all course videos on YouTube here and on MediaHopper here.

01 Keeping up with IDS: Week 2 10:25
02 Data and visualisation 23:52
03 Visualising data with ggplot2 21:40
04 Visualising numerical data 23:57
05 Visualising categorical data 6:28
06 AE: StarWars + Dataviz 5:18


Due this week
Lab 00 Hello IDS! Tue, 29 Sep, 16:00 UK
HW 00 Pet names Thur, 1 Oct, 16:00 UK
EC Extra credit Multiple (see assignment)
OQ 01 Data visuallization Sun, 4 Oct, 23:59 UK
Due next week
Lab 01 Plastic waste Tue, 6 Oct, 16:00 UK

If you’re having difficulty accessing your HW or Lab repo, see troubleshooting advice here.


πŸ“– R4DS::Chp 3 - Data visualisation Required
πŸ“– IMS::Chp 2 - Summarizing and visualizing data Required
πŸ“„ Make a plot Optional
πŸ“Š Information is beautiful - COVID-19 data visualisations Optional
πŸ“Š Wealth shown to scale Optional
πŸ“Š Explore COVID-19 Symptoms Search Trends Optional


The data come from TidyTuesday. TidyTuesday is a weekly social data project for the R community. Read more about TidyTuesday here and see people’s contributions on Twitter under the #tidytuesday hashtag.

You can find starter code for this session on RStudio Cloud, in the project titled Code Along 02 - BeyoncΓ© and Taylor Swift Lyrics.

Session artifacts .Rmd     .md

Interactive R tutorials

The following are interactive R tutorials, designed to give you more practice with R. These are optional, but the “Airbnb listings in Edinburgh” dataset show up in your next homework assignment as well, so you might want to go through that one so that you can gain familiarity with it. If you’re struggling with any of the topics covered this week, we strongly recommend you work through the second tutorial as well.

Airbnb listings in Edinburgh Related to HW 01
Data Visualization Basics Extra practice