Exploratory data analysis using visualization & Data organization in spreadsheets

CVEN 5999 - Summer 2025

Lars Schöbitz

Solving coding problems

Tipps for search engines

  • Use actionable verbs that describe what you want to do
  • Be specific
  • Add R to the search query
  • Add the name of the R package name to the search query
  • Scroll through the top 5 results (don’t just pick the first)

Example: “How to remove a legend from a plot in R ggplot2”

Stack Overflow

What is it?

  • The biggest support network for (coding) problems
  • Can be intimidating at first
  • Up-vote system

Workflow

  • First, briefly read the question that was posted
  • Then, read the answer marked as “correct”
  • Then, read one or two more answers with high votes
  • Then, check out the “Linked” posts
  • Always give credit for the solution

Tipps for AI tools

  • Use actionable verbs that describe what you want to do
  • Be specific
  • Add R to the search query
  • Add the name of the R package name to the search query

Example: “How to remove a legend from a plot in R ggplot2”

Other sources for help

Learning Objectives (for this week)

  1. Learners can describe the four main aesthetic mappings that can be used to visualise data using the ggplot2 R Package.
  2. Learners can control the colour scaling applied to a plot using colour as an aesthetic mapping.
  3. Learners can compare three different geoms and their use case.
  4. Learners can apply a theme to control font types and sizes within a plot.
  5. Learners can apply 12 principles for data organisation in spreadsheets in the layout of a collected dataset.

Exploratory Data Analysis with ggplot2

R Package ggplot2

  • ggplot2 is tidyverse’s data visualization package
  • gg in ggplot2 stands for Grammar of Graphics
  • Inspired by the book Grammar of Graphics by Leland Wilkinson
  • Documentation: https://ggplot2.tidyverse.org/
  • Book: https://ggplot2-book.org

Code structure

  • ggplot() is the main function in ggplot2
  • Plots are constructed in layers
  • Structure of the code for plots can be summarized as
ggplot(data = [dataset], 
       mapping = aes(x = [x-variable], 
                     y = [y-variable])) +
   geom_xxx() +
   other options

Code structure

ggplot()

Code structure

ggplot(data = gapminder_yr_2007)

Code structure

ggplot(data = gapminder_yr_2007,
       mapping = aes())

Code structure

ggplot(data = gapminder_yr_2007,
       mapping = aes(x = continent,
                     y = lifeExp))

Code structure

ggplot(data = gapminder_yr_2007,
       mapping = aes(x = continent,
                     y = lifeExp)) +
  geom_boxplot()

Code structure

ggplot(data = gapminder_yr_2007,
       mapping = aes(x = continent,
                     y = lifeExp)) +
  geom_boxplot() +
  theme_minimal()

Code structure

ggplot(data = gapminder_yr_2007,
       mapping = aes(x = continent,
                     y = lifeExp)) +
  geom_boxplot() +
  theme_minimal(base_size = 14)

Live Coding Exercise: Reproduce this plot

clone-repository-to-posit-cloud

Follow along on the screen

  1. Open the GitHub organisation for the course: https://github.com/cven5999-ss25
  2. You will find a repository titled: wk-03-USERNAME (with your GitHub Username)
  3. You will “clone” this repository to Posit Cloud

Break

10:00

Visualising numerical data

Types of variables

numerical

discrete variables

  • non-negative
  • whole numbers
  • e.g. number of students, roll of a dice

continuous variables

  • infinite number of values
  • also dates and times
  • e.g. length, weight, size

non-numerical

categorical variables

  • finite number of values
  • distinct groups (e.g. EU countries, continents)
  • ordinal if levels have natural ordering (e.g. week days, school grades)

Data Organisation in Spreadsheets

Data Organisation in Spreadsheets

Read the paper (it’s part of your homework), but you can also:

  • Go through the annotated slides: https://kbroman.org/Talk_DataOrg/dataorg_notes.pdf
  • Watch Karl Broman give the talk (02:36 to 45:00): https://youtu.be/t74E0a90gkA?t=156
  • Read the content on a website: https://kbroman.org/dataorg/

But, especially apply it to your data

via GIPHY

Why?

Because it will make your life easier!

License? CC0 (!)

Homework week 3

Identify a dataset for the capstone project

  • A dataset from your own research
  • A dataset from your work
  • A dataset that you find interesting and is available as open data

Homework due dates

  • All material on course website
  • Homework assignment & learning reflection due: 2025-06-20

Thanks! 🌻

Slides created via revealjs and Quarto: https://quarto.org/docs/presentations/revealjs/

Access slides as PDF on GitHub

All material is licensed under Creative Commons Attribution Share Alike 4.0 International.

cven5999-ss25.github.io/website/