8-11 January 2024

R is one of the most versatile and popular open source languages for processing, analyzing, and visualizing data. The diversity of packages and learning resources available for using R across different disciplines can be disparate and overwhelming, so a solid grasp of R is essential for those involved in scientific research.  This course will teach all the elements needed for interacting with data programatically, through a dynamic and interactive focus to highlight the relationship between code and output. The most common data manipulation and processing tasks will be addressed, taught using the ‘tidyverse’ package universe and dialect. Document preparation will be taught using Quarto, a novel technical and scientific publishing system.   The topics and tools have been carefully chosen to empower participants with the necessary skills for modern scientific research. 

This course is targeted to novice users with or without prior programming experience. 

After the course, participants will be able to use R for:

- importing files,

- wrangling and transforming data,

- producing figures, tables, and documents oriented to their particular fields. 

Daily on-line meetings,  14:00-1900 CET; offline communication through Slack

 Day 1. Introduction  

A general introduction to code-based data analysis, history of the R language, and getting familiar with the R ecosystem.

- Advantages of working with Integrated Development Environments (e.g. RStudio)

- Project-oriented workflows

            - The R workspace

            - Paths, files, and naming conventions

- The importance of source code

- Packages that extend the capabilities of R

Day 2. Data preparation

Mastering the data structures and concepts needed to easily import, manipulate, and prepare data prior to analysis or visualization

- Importing files

- Data structures and working with ‘tidy data’

- Transforming and manipulating rows and columns

- Data wrangling with dplyr

- Exporting data objects to common file formats

Day 3. Data visualization

Crafting high quality, fully customized figures with ggplot2

- Fundamentals of data visualization and the grammar of graphics

- Using colors, fills, shapes and geometries to convey data insights

- Customizing plot elements for creative design

- Export high resolution figures for reports, presentations or publications

Day 4. Efficient and reproducible programming and reporting

Unlock the power of R with nifty tools to program efficiently and share code+results in various formats

- Streamlining repetitive tasks (iteration and the purrr package)  

- Writing and applying new functions 

- Tools and good practices for sharing code

- Seamless integration of code, text, figures, and tables to produce elegant documents with Quarto