It is often mentioned that 80% of a data analysis pipeline is involved with the tedious process of cleaning and preparing data in a correct way so they can be consumed for analysis and visualization (Dasu & Johnson, 2003). Tidy data facilitates easier data transformation and visualization. Tidy data works hand in hand with the tools provided by the tidyverse collection of R packages, in a way that promotes reproducibility and efficiency. ggplot2 (Wickham, 2009) is one of the core members of the tidyverse. It is one of the best and most used R packages for data visualization. In this workshop, participants will learn the principle of tidy data, how to transform and combine datasets using the tools from the tidyverse and how to generate advanced visualization with the ggplot2 package.
Dasu, T., & Johnson, T. (2003). Exploratory Data Mining and Data Cleaning. https://doi.org/10.1002/0471448354
Wickham, H. (2009). ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York. Retrieved from http://ggplot2.org
Then this workshop will equip you with the skills to tackle the above use-cases and many more!
Participants should be familiar with the concepts taught in the course “Introduction to Data Science with R and R Studio” (https://www.pe-rc.nl/data-science-r) and be comfortable in working with:
The course is spread across four days in four consecutive weeks and takes place on a dedicated Microsoft Teams group that will be created for the course. Each day of the course will be broken into three sections by a lunch break (1 hour) and two shorter breaks (20 minutes). Each of the first two sections of a course day will be chaired by one of the instructors who will share his computer screen via with the rest of participants. During these sections, theoretical concepts will be taught via a presentation, mixed with live coding practice (i.e. the instructor writes the code to solve a problem), interaction with participants as well as short exercises (2 – 3 minutes each) performed by participants on their own. The other instructor will be answering questions on the chat of the Teams group.
A week before the start of the course, a short meeting is planned to set up the computers with the required software.
Target Group | The course is aimed at PhD candidates, postdocs, and academic staff |
Group Size | 24 participants |
Course duration | 4 days (two days a week from 9:00 to 17:00). Participants are expected to be present full time, only in urgent exceptions a few hours leave form the course is possible |
Language of instruction | English |
Frequency of recurrence | To be determined |
Number of credits | 1.2 ECTS |
Lecturers | Ioannis Baltzakis, Alejandro Morales Sierra |
Prior knowledge | Participants should be familiar with all the concepts taught in the course “Introduction to R” offered by PE&RC |
Estimated self-study/practice time | 2 hours (see above at Course setup) |
Location | Online (Microsoft Teams) |
EARLY-BIRD FEE 2 | REGULAR FEE 2 | |
PE&RC / WIMEK / EPS / WASS / VLAG / WIAS PhD candidates with an approved TSP | € 155,- | € 205,- |
PE&RC postdocs and staff | € 310,- | € 360,- |
All other academic participants | € 350,- | € 390,- |
All others | € 505,- | € 555,- |
1 The course fee includes coffee/tea, and lunches. It does not include accommodation (NB: options for accommodation are given above)
2 The Early-Bird Fee applies to anyone who REGISTERS A MINIMUM OF TWO MONTHS BEFORE START OF THE COURSE
Note:
Note: If you would like to cancel your registration, ALWAYS inform us (and do note that you will be kept to the cancellation conditions)
Dr. Lennart Suselbeek (PE&RC)
Phone: +31 (0) 317 485426
Email: lennart.suselbeek@wur.nl
At this moment, this course is not scheduled yet. However, if you register your interest in this activity below, we will inform you as soon as the course is scheduled and registration of participation is opened.