Data processing with R tidyverse

The four day course provides a complete introduction to data science in R with the tidyverse. The course will not go deep into statistics but rather getting data ready, some exploratory analysis, visualization and handling models.

Preparing data takes up to 90% of the time spent in analysis — speeding this up is the mission of this course.

Keywords: R-programming

Resource type: course materials

Target audience: Researchers

Difficulty level: Intermediate

Authors: Aurélien Ginolhac, Roland Krause, Eric Koncina

Data processing with R tidyverse R is a powerful language for data science in many disciplines of research with a steep learning curve. The tidyverse group of packages provide a dialect that greatly simplifies: * data importing * cleaning * processing * visualization as well as providing reproducible workflows using pipelines (`%>%`) Adopt Hadley Wickham, Chief Scientist at RStudio, philosophy: take each step of data science and replace many intricacies of R with clear, consistent and easy to learn syntax. RStudio will be the software to use since it eases package management, scripting, plotting and data handling. R-programming Researchers