Data handling with tidyr & dplyr and visualization with ggplot2

Welcome to the Day2 (2026-01-20)

📅 Schedule

Tuesday

Time Task or Topic
09.15-10.00 Lecture Data handling with tidyR
coffee break
10.15-11.00 Exercise/lab/practice Data handling with tidyR
coffee break
11.15-12.00 Lecture & exercise Data handling with tidyR
LUNCH break
13.00-14.00 Lecture & exercise Visualization with ggplot2 P1
coffee break
14.20-15.45 exercise & recap Visualization with ggplot2 P1

Wednesday

Time Task or Topic
09.15-10.00 Lecture Data handling with dplyR
coffee break
10.15-11.00 Exercise/lab/practice Data handling with dplyR
coffee break
11.15-12.00 Exercise/Recap Data handling with dplyR
LUNCH break
13.00-14.00 exercise ggplot2 P2 (advanced)
coffee break
14.20-15.30 exercise &  recap 
15.30-15.45 feedback

Content

3.1 Tidyr lecture & lab

Lecture:

Lab exercises: finish all the challenges

3.2 ggplot part 1

Lecture:

Lab exercises: finish all the challenges

Bonus practice:Basics) upto chapter: 1.17

3.3 dplyr lecture & lab

lecture: slides_dplyr.pdf Lab exercises: finish all the challenges

3.4 ggplot part 2

Lecture: same lecture

Lab exercises: remake the following graphs (website):

  1. Economist Scatterplot and/or
  2. WSJ Heatmap

Help!

i) Datasets used in these lectures and labs:

storms, cases, pollution, tb, gapminder_data.csv, gapminder_wide.csv, penguins

How to load data (e.g., ‘case’ data): 

# install.packages("readr")

library(readr)

cases_raw <- https://github.com/rstudio/EDAWR/blob/master/data-raw/cases.csv?raw=true

cases <- read_csv(cases_raw)

ii) Font problem!!! Solution (by Annrose):

# install.packages(devtools)
library(devtools)
library(extrafont)
font_import()
loadfonts(device = "win")
loadfonts()
fonts()

It has enabled you to register several fonts to my Windows and is now working

iii) End codes!

gapminder %>% filter(year == 2007) %>%
   mutate(gdpPercap = gdpPercap / 1000) %>%
   ggplot(aes(x = gdpPercap, y = lifeExp, color = continent)) +
   geom_point(size = 3) + scale_x_log10() + # Log scale for better visualization
   labs(title = "Life Expectancy vs. GDP per Capita (2007)", x = "GDP per Capita (in thousands)", y = "Life Expectancy", color = "Continent") +
   theme_minimal()

iv) References:

  • Tidyverse

📚 Course materieals

1. Download this repository:

Repository

  • Click on <>Code green box

  • Click on Dowlload ZIP, will be downloaded

  • Extract and enter into the repository folder📁

Tip

📬 For questions or feedback, contact at abu.siddique@slu.se

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

Feedback

Please give me feedback on these two days: https://forms.gle/yKsFezP4pi4DSajv8