Data processing with R tidyverse
Introduction
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.
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 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 should have basic experience in programming environments such as Matlab, Octave or other programming languages or complete a simple free online course.
There is a special session on updates of the tidyverse on 11 May 2020 for participants of previous iterations of the course. No registration is required to attend.
Material
Each student must bring their own laptop with R and Rstudio installed with recent versions. Please look at install tutorial to set it up prior to the course.
Schedule
This course will take place either offline or online depending on the requirements.
Dates and time
7 & 8 and 11 & 12 May 2020.
Each day, the workshop will be a mixture of lectures and practicals from:
- 9:00 - 9:30 welcome coffee
- 9:30 - 12:30 course work with a coffee break
- 12:30 - 13:30 lunch breaks from
13:30 - 17:30 course work with a coffee break
Coffee will be served outside the course room in the lounge area.
Program
| Date | Time | Session | Teacher | Notes |
|---|---|---|---|---|
| 2020-05-07 | 09:30 | Introduction | AG | |
| 11:00 | Tidy data | RK | ||
| 13:30 | String manipulation | RK | stringr |
|
| 14:30 | RMarkdown | AG | knitr |
|
| 16:00 | Import | AG | readr |
|
| 18:00 | Dinner with participants | RK | ||
| 2020-05-08 | 09:30 | Data transformation | RK | dplyr, tidyr |
| 13:30 | Visualization | AG | ggplot |
|
| 2020-05-11 | 09:30 | Functional programming | AG | purrr |
| 13:30 | Tidy models | AG | broom |
|
| 15:30 | Advanced Programming | AG | tidyeval |
|
| 2020-05-12 | 09:30 | New developments in 2020 | AG | |
| 10:15 | Coffee break | |||
| 10:45 | Practical | All |
Location
The course will be held online or (if the Covid-19 situation is cleared by then) at:
Maison du Nombre (MNO) Room 1.1010 University of Luxembourg Belval Campus 6, avenue de la Fonte L-4364 Esch-sur-Alzette Luxembourg
MNO room 1.1010, 1st floor
Registration
The course is limited to 30 participants. Register through this form
ECTS
PhD students that enrolled through the doctoral school will receive 2 ECTS in category 1, which requires handing in a short project and practicals as Rmd files that students miss. For example if you are absent the first day, you must do and send back:
- practical introduction with
datasauRus - practical string manipulation
- practical import data
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 will be awarded for this year’s edition.
Elixir
This event is supported by ELIXIR-Luxembourg