In this 3-day hands-on course, participants will learn how to create clear, elegant, and insightful data visualizations using R. The course takes a practical approach, beginning with data wrangling and cleaning, and progressing through basic and advanced plotting techniques to interactive dashboards and reproducible reporting.
Whether you're new to data visualization or looking to refine your R plotting skills, this course will guide you through powerful tools from the tidyverse, ggplot2, plotly, and shiny. Participants will leave with a set of reusable templates and scripts, plus the confidence to visualize complex datasets in meaningful ways.
No prior experience in R is strictly required, but a basic familiarity with R  is helpful.

This course is aimed at researchers and technical workers with a background in any data-related field. In general, no programming experience is needed. The course teaches all relevant steps to load, transform and visualize the data. However, basic knowledge of R is beneficial. If you like to learn R beforehand, We suggest you to attend our Introduction to R and the tidyverse course:  https://www.physalia-courses.org/courses-workshops/r-tidyverse/

By the end of the workshop, participants will be able to:
    

• Understand and apply core principles of effective data visualization, including appropriate use of colors, chart types, and   layout.
• Import, clean, and transform data in R using the tidyverse suite of packages.
• Grasp the layered grammar of graphics in ggplot2 and how to build plots step by step.
• Create a variety of data visualizations to explore and communicate insights using ggplot2.
• Produce high-quality, publication-ready figures that are clear, visually appealing, and easy to interpret.

All materials and code examples will be available on GitHub/GitLab.

Day 1 – Data Wrangling and Basic Plotting - 1-5 PM Berlin time

    Importing datasets from CSV, Excel, and online repositories
    Introduction to the tidyverse: dplyr, tidyr, readr, and tibble
    Cleaning and transforming data for visualization
    Creating basic plots using ggplot2: scatterplots, barplots, boxplots, and line plots
    Mapping variables to aesthetics: color, shape, size
    Saving and exporting plots

Day 2 – Advanced and Aesthetic Visualizations - 1-5 PM Berlin time

    Multi-panel and faceted plots (facet_wrap, facet_grid)
    Complex plots: heatmaps, PCA biplots, violin plots, Manhattan plots, oncoplots
    Fine-tuning plots: custom themes, color palettes, fonts, and labels
    Using extensions and custom geoms to enhance data storytelling
    Combining multiple plots (patchwork, cowplot)

Day 3 – Interactive Visualizations and Reporting- 1-5 PM Berlin time

    Intro to interactivity with plotly and ggplotly
    Interactive dashboards with shiny: linking inputs and outputs
    Embedding plots in R Markdown and HTML reports
    Dynamic visualizations for web sharing
    Best practices for reproducibility and version control

Cancellation Policy:

> 30  days before the start date = 30% cancellation fee

< 30 days before the start date= No Refund.

Physalia-courses cannot be held responsible for any travel fees, accommodation or other expenses incurred to you as a result of the cancellation.