DSCI 531: Data Visualization I

Effective static data graphics using R and python for exploratory data analysis.

Course website: https://ubc-mds.github.io/DSCI_531_viz-1/

Course Learning Outcomes

By the end of the course, students are expected to:


You’ll be evaluated as follows:

Assessment Weight Due Date Location Covers
“Half Lab” Assignment 1 6% Saturday, Oct 13 at 18:00 Submit to Github Lec 1
Lab Assignment 2 12% Saturday, Oct 20 at 18:00 Submit to Github Lec 2-3
Quiz 1 20% Tuesday, Oct 23, 15:00-15:30 Your lab room; submit to canvas Lec 1-3, Lab 1-2
Lab Assignment 3 12% Saturday, Oct 27 at 18:00 Submit to Github Lec 4-5
Lab Assignment 4 12% Saturday, Nov 3 at 18:00 Submit to Github Lec 6-7
Quiz 2 20% Wed, November 7, 14:00 – 14:30 Your DSCI 512 (Wednesday) lab rooms Lec 4-8, Lab 3-4
Lec 8 Hackathon 6% Tuesday, Nov 6 at 18:00 Submit to GitHub NA
Peer Review of Hackathon 5% Friday Wednesday, Nov 7 at 18:00 Submit to GitHub NA
Participation 7% NA NA Seven lectures

Tip: Use the lecture learning objectives as beacons when studying for your quizzes!

Lecture Details

Lecture Topic Pre-readings/Resources
1 / complete worksheet Basic plot “types” with ggplot2 r4ds: data-vis, esp. 3.6
2 / complete worksheet EDA; aesthetic mappings in ggplot2 r4ds: data-vis, esp. 3.3
3 / complete worksheet Dependence. Finish looking at ggplot2 as a tool. stat545: colors; Jenny’s theme tutorial
4 / complete worksheet Special plot types: GGally, Interactivity and 3D plotting with plotly, ggmaps ggobi’s list of GGally extensions; r-bloggers on ggmap
5 Plotting for humans stat545: dos-and-donts, Geckoboard tips
6 Plotting in Python, Part I: matplotlib pyplot tut
7 Plotting in Python, Part II: seaborn elitedatascience seaborn tut
8 Hackathon  

Annotated Resources

Here are prominent course resources that we will be referring to.

  1. R for Data Science (r4ds)
    • Overall good book on using R for data science – including data vis, of course!
  2. ggplot2 book
    • Readable, comprehensive resource for learning about ggplot2, by the main author of the ggplot2 package, Hadley Wickham.
  3. STAT 545 “All the Graph Things” by Jenny Bryan.
    • Contains tutorials relevant to our subject matter.

Other resource that you might find useful:

  1. R Graphics Cookbook
    • Good as a reference if you want to learn how to make a specific type of plot in ggplot2.
  2. Jenny Bryan’s ggplot2 tutorial
    • Has a lot of examples and less dialogue.
  3. ggplot2 cheat sheet
    • Great for quick reference if you need something beyond tab-completion.
  4. “Visualization Analysis and Design” by Tamara Munzner, CRC Press, 2014.
    • The go-to book for data vis theory.


Please see the general MDS policies.


Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.