9-13 November 2020
Due to the COVID-19 outbreak, this course will be held online
Data visualization is an important skill in all data-related fields such as scientific research and journalism. An elegant way to produce such visualizations in a reproducible way is the `ggplot2` package providing a structured graphics framework in R. In this course, you learn how to use R to load, transform, explore and visualize data. The course also covers the basic concepts in data visualization and a suite of different chart types and tricks to make appealing and informative-rich plots using `ggplot2`.
This workshop is aimed at researchers and technical workers with a background in any data-related field. In general, no programming experience is needed. The course teaches all relevant steps to load, transform and visualize the data. However, basic knowledge of R is beneficial. If you like to learn R beforehand, I suggest chapter 1 to 4 of “R Programming for Data Science” by Roger D. Peng: https://bookdown.org/rdpeng/rprogdatascience/
After completing the workshop, students should be in a position to:
1. know and apply the principles of good data visualization such as the right choice of colors and chart types
2. load and transform data in R using `tidyverse`
3. understand the layered structure of `ggplot2`
4. visualize the data in multiple ways using `ggplot2`
5. create publication quality and easy understandable figures
6. perform reproducible by using version control and project organization
The workshop is delivered over 5 days (see the detailed curriculum below). The lectures are interactive with active exercises and discussion where asking questions is strongly
All course materials (including copies of presentations, practical exercises, data files, and example scripts) will be provided electronically to participants.
Monday - 10 am - 6 pm Berlin time
• Introduction to data wrangling in R
– Part I: Getting started with R and RStudio
– Part II: Data transformation and exploration with `tidyverse`
This includes course material
> 30 days before the start date = 30% cancellation fee
< 30 days before the start date= No Refund.
Physalia-courses cannot be held responsible for any travel fees, accommodation or other expenses incurred to you as a result of the cancellation.