Learn R Interactively — Directly in the R Console with swirl and DSBswirl
swirl is an R package that provides interactive learning courses directly in the R console. Students can practice R commands at their own pace and receive immediate feedback – without leaving the R environment.
The DSBswirl package contains swirl courses specifically developed for the Data Science in Biology course series. The courses are aligned with the lecture content and are ideal for preparation and review.
Available DSBswirl Courses
German Courses
| Course | Topic | Accompanies | No. of Lessons |
|---|---|---|---|
| DSB-01 | R Basics | DS 1 | 16 |
| DSB-02 | Data Exploration with R | DS 1 | 8 |
| DSB-03 | Data Wrangling and Tidyverse | DS 1 | 7 |
| DSB-04 | Data Visualization with ggplot2 | DS 1 | 16 |
| DSB-05 | Handling Special Data Types | DS 1 | 7 |
| DSB-06 | Advanced R Programming | DS 3 | 6 |
English Course
| Course | Topic | No. of Lessons |
|---|---|---|
| Data analysis with R | Fundamentals, Tidyverse, Visualization, Linear Regression | 16 |
Installation on Your Own Computer
Both packages are already pre-installed on our Posit Workbench!
1. Install the Packages
# Install swirl (if not already installed)
install.packages("swirl")
# Install DSBswirl (from GitHub)
if (!require("remotes")) install.packages("remotes")
remotes::install_github("uham-bio/DSBswirl")2. Install DSBswirl Courses
library(DSBswirl)
# Install all courses
DSBswirl::install_dsb_courses()On success, you will see | Course successfully installed! for each of the 6 courses.
Starting Courses
# Start swirl
library(swirl)
swirl()You will be asked for a freely chosen name — this allows you to resume unfinished lessons later.
Controls During Lessons
| Input | Description |
|---|---|
swirl() |
Start swirl and select a course |
... + ENTER |
Display next text section |
skip() |
Skip the current question |
play() |
Experiment freely in R |
nxt() |
Return to the lesson after play() |
main() |
Return to the main menu |
bye() |
Save progress and exit |
info() |
Display these options |
| Esc | Leave swirl at any time |
A lesson typically takes 10–20 minutes. You can interrupt at any time — the next time you start, you will continue where you left off.
After starting swirl(), select the desired course from the list. You can interrupt anytime with bye() and continue later from where you left off.
Further Resources
- DSBswirl on GitHub – Source code and documentation
- swirl Project Website – Official swirl website
RLab Courses
As part of the Teaching Lab RLab (Universitätskolleg 2.0, funded by the BMBF 2017–2019), additional swirl courses were developed for Biology, Geography, and Meteorology. All courses can be used independently and for self-study.
Biology
| Course | Language | Download |
|---|---|---|
| Data Analysis with R — accompanying the course Data analysis with R (IMF, UHH) | EN | 📦 .swc |
| Statistik & Programmierung mit R — former BSc course BMARSYS-6 (Marine Ecosystem and Fisheries Sciences) | DE | 📦 .swc |
| Datenaufbereitung mit tidyr — Marine Ecosystem and Fisheries Sciences | DE | 📦 .swc |
| Daten visualisieren mit ggplot2 — Department of Biology | DE | 📦 .swc |
Geography & Meteorology
| Course | Subject | Download |
|---|---|---|
| R Grundlagen | Geography | 📦 .swc |
| Daten einlesen und kennenlernen | Geography | 📦 .swc |
| Deskriptive Statistik mit bodenkundlichen Daten | Physical Geography | 📦 .swc |
| Deskriptive Statistik Geländeklimatologie | Physical Geography | 📦 .swc |
| Datenhandling und Visualisieren von Klimadaten | Meteorology | 📦 .swc |
| Deskriptive Statistik und Vergleiche meteorologischer Zeitreihen | Meteorology | 📦 .swc |
The RLab courses are installed locally via an .swc file using the install_course() function. The .swc file extension is also used by Adobe in connection with the multimedia platform flash. The .swc RLab files (swirl course) are unrelated; opening them with Adobe software (if installed on your computer) will not work.
To download the course files, right-click and select ‘Save target as…’.
Then enter the following command in the R console and press Enter:
install_course(swc_path = "/file-path/filename.swc")You should now see | Course successfully installed! in the console.
The RLab project was funded from 2017–2019 as a Teaching Lab of the Universitätskolleg 2.0 at the University of Hamburg (BMBF 01PL17033). Project lead: Prof. Jürgen Böhner; conceptual development: Niels Schwab. Contributors included teachers from Geography, Meteorology, Biology, and Marine Ecosystem Sciences as well as student research assistants.