Week 2 - Visualizing data
Data visualization and interpretation of graphical information 📊
Tasks
- Watch the videos
- Complete the readings
- Complete the assignments
- If you haven’t yet done so:
- Complete the Getting to Know you survey
Videos
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.
Assignments
Assignment |
Title |
Due |
|---|---|---|
| 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.
Readings
| 📖 | R4DS::Chp 3 - Data visualisation | Required |
| 📖 | IMS::Chp 2 - Summarizing and visualizing data | Required |
| 📄 | Make a plot | Optional |
| 📊 | Information is beautiful - COVID-19 data visualisations | Optional |
| 📊 | Wealth shown to scale | Optional |
| 📊 | Explore COVID-19 Symptoms Search Trends | Optional |
Code-along
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 - Beyoncé and Taylor Swift Lyrics.
| Recording | |
| 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 |
