GESIS Training Courses
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Scientific Coordination

Julia Leesch
Tel: +49 221 47694-169

Administrative Coordination

Claudia O'Donovan-Bellante
Tel: +49 621 1246-221

Data Wrangling & Exploration with the Tidyverse in R

Lecturer(s):
Dr. Johannes Breuer, Thomas Ebel

Location: Mannheim B2,8 / Kurssprache: Englisch

About the lecturer - Dr. Johannes Breuer

About the lecturer - Thomas Ebel

Course description

Before researchers can start to analyze their data, they first have to wrangle (i.e., clean and transform) and explore them. While this can be done with base R, the syntax for this is typically verbose and not intuitive and, hence, difficult to learn, remember, and read. The tidyverse addresses this problem by providing a consistent syntax that is also easy to read, learn, and remember. The tidyverse website describes it as “an opinionated collection of R packages designed for data science” and points out that “all packages share an underlying design philosophy, grammar, and data structures” (see https://www.tidyverse.org/). These attributes make the tidyverse especially attractive for novice R users. In this workshop, we will introduce participants to the tidyverse and its packages and relevant concepts like tidy data and the pipe operator. In the practical parts of the workshop, we will focus on wrangling (importing, tidying, transforming) and exploring (with a focus on visualization) the data. For the exercises, we will use RStudio. The course is meant for R beginners who are looking for an accessible, hands-on introduction to the first steps of working with data in R as well as more advanced R users who want to switch from base R to the tidyverse for their data wrangling and exploration tasks.


Target group

Beginners or advanced users of R who want to learn (more) about data wrangling and exploration and/or switch from base R to the tidyverse.   


Learning objectives

Participants will learn how to wrangle and explore data in R using packages from the tidyverse. At the end of the course, they will be familiar with the concepts of tidy data and the pipe operator, able to import, transform, and explore their data with the tidyverse, and comfortable rewriting base R syntax in tidyverse syntax.


Prerequisites

Participants should at least have some basic knowledge of (base) R. This knowledge can be acquired through the GESIS course “Einführung in R” by Jan-Philipp Kolb that takes place directly before this course. Other means of gaining some basic familiarity with R are, for example, the swirl (Learn R, in R) course R Programming (see https://swirlstats.com/) or the DataCamp online course “Introduction to R” (https://www.datacamp.com/courses/free-introduction-to-r), both of which are available for free.


Schedule

Recommended readings

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