GESIS Training Courses

Scientific Coordination

Verena Kunz

Administrative Coordination

Janina Götsche

Applied Data Visualization with R

Online via Zoom
General Topics:
Course Level:
Software used:
Students: 330 €
Academics: 495 €
Commercial: 990 €
Additional links
Lecturer(s): Paul Bauer

About the lecturer - Paul Bauer

Course description

The workshop “Applied Data Visualization with R” introduces students to the theory and methods underlying data visualization. Data analysts face an ever-increasing amount of data (→ “big data”). Rather revolutionary technological developments allow researchers to visually engage with data in unprecedented ways. Hence, data visualization is one of the most exciting fields in data science right now. In this workshop, students acquire the skills to visualize data in R both for exploratory purposes as well as for the purpose of explanation and presentation. We'll rely on R, the most popular statistical programming environment when it comes to data visualization, and we'll make use of popular R packages such as ggplot2 and plotly. Besides creating static graphs we'll also explore interactive graphs and discuss how interactive visualization may revolutionize how we present data & findings. The workshop is based on the course script Applied Data Visualization.

Target group

Regular R users who are interested in visualizing data to communicate their findings.

Learning objectives

By the end of the course, participants will…
  • ...know the key concepts underlying the grammar of graphics.
  • able to read complex graphs.
  • able to critically assess graphs on different dimensions of quality.
  • able to use various plots for exploratory and presentational/explanatory purposes.
  • ...learn how to map data dimensions to visual dimensions.
  • ...learn how to use the popular R package to visualize graphs (ggplot2).
  • ...understand the potential of interactive graphs.
  • ...learn how to generate interactive graphs using ggplot2 and plotly.

  • Prerequisites

    Basic knowledge of R (and R packages such as dplyr), either because of previous work in R or through self-study, e.g. on DataCamp (access to Datacamp is organized for the course duration). We'll rely on R and Rstudio in the seminar.
  • Specifically, we will use data management functions from the tidyverse. If you lack this knowledge you should do the following courses on Datacamp:
  • Introduction to the Tidyverse (Dplyr): Chapter 1 (Data wrangling) & 3 (Grouping and summarizing)
  • Some introductory statistics courses covering regression analysis, frequentist statistics, frequentist hypothesis testing, etc.
    Software requirements
    The workshop will be based on the open-source programming language R. We follow the principles of 'Open Data,' 'Open Code,' and the integration of narrative text and code (no commercial software is needed). Please install R and RStudio before the workshop.  Participants will receive an email with further installation instructions (e.g., regarding required R packages).