Data processing with R tidyverse

Introduction

is a very 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
reproducible workflows using pipelines (magrittr %>%, or the new native operator |>)

Adopt Hadley Wickham, Chief Scientist at RStudio, philosophy: take each step of data science and replace many intricacies of 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.

This course provides a complete introduction to data science in 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 80% of the time spent in analysis — speeding this up is the mission of this course.

Tidyverse

The tidyverse is an official CRAN package and here is its manifesto. Hadley proposed the following workflow described in his must-read book R for data science

H. Wickham - R for data science, licence CC

In terms of R packages, the workflow is nicely depicted as in this picture, by David Robinson

Requirements

Prior knowledge

Participants must have basic experience in programming environments such as Matlab, Octave or other programming languages or complete a simple free online course.

There will be a special session on updates of the tidyverse for participants of previous iterations of the course.

Material

Each student must bring their own laptop with R and Rstudio installed as detailed in the install tutorial prior to the course.

Location

The course will be held online using Webex. The lectures (only) will be recorded. It will not be available during the course time.

Please join the for questions and communication around the workshop.

Registration

The course is limited to 50 participants. Registration is open HERE.

ECTS

PhD students that enrolled through the doctoral school of the University of Luxembourg will receive 1 ECTS in category 1, which requires handing in practicals.

Please note that ECTS can only be received for the course once. If you already have received ECTS for the last version of the course, no ECTS can be awarded for this year’s edition. If you are not at student at the University of Luxembourg, contact your doctoral school or other relevant authority to your course of study first.

Elixir

This event is supported by ELIXIR-Luxembourg