Module 12: Manipulating, Plotting and Reporting Data in R

Type of Course - Dates - Venue - Description - Target audience - Exam - IMPORTANT: Incorporation in DTP and reimbursement by DS
Course prerequisites - Teacher - Course material - Fees - Enrol

Type of course

This is an online course.

Dates

Session 1: Monday May 31, 2021, from 1 pm to 4.30 pm

Session 2: Monday June 7, 2021, from 1 pm to 4.30 pm

Session 3: Monday June 14, 2021, from 1 pm to 4.30 pm

Please note: the deadline for UGent PhD students who want a refund to open a dossier on the DS website (Application for Registration) is April 30, 2021.

Venue

This is an online course.

Description

Data provides insight, but only if it is presented it in a clear and structured way. The open source software R is focused on data analysis thus perfectly equipped for that task. No matter if it is research data stored in a set of excel-files, yearly sales and purchases stored in an sql-database or just your time-tracking that is stored online in your favorite app, R can turn it into a insightful and professional looking report.

Within R, Tidyverse (dplyr, tidyr,…) offers comprehensive framework for clear and intuitive data manipulation. It combines readability with great flexibility and offers handles to increase your insight in the way data is structured. This will be subject of the first session.

The second session explores ggplot2, one of the best packages for making plots available anywhere. It’s clear philosophy and well-structured design leads to wide range of possibilities. Other packages have built on its core to produce specialized graphs or to allow interactive graphs and animations.

Finally, these plots, together with tables and text, can be presented in reports in pdf, html or word-format. The third session focusses on pdf-output with Rmarkdown and word-output with Officedown, but also covers the basics for html-output. It covers a general approach, changing layout and automating the procedures.

In each session, the concepts and code are presented step-by-step. Extended example-code is discussed and shared, and can serve as template for your own reports.

Target audience

Anyone who wants to turn data into clear and professional looking reports. The course offers a broad introduction with lots of example code, but also more complex and challenging examples and links online sources to present the full capabilities of reporting in R.

Exam

There is no exam connected to this module.

Incorporation in DTP and reimbursement from DS for UGent PhD students

As a UGent PhD student, to be able to incorporate this module as a 'transferable skills seminar' in your Doctoral Training Program (DTP) and get a refund of the registration fee from your Doctoral School (DS) you need to take part in all three sessions and follow strict rules: please take the necessary action in time. The deadline to open a dossier on the DS website (Application for Registration) for this course is April 30, 2021. Please note that opening a dossier does not mean that you are enrolled. You still need to enrol via the registration form on this site.

Course prerequisites

• Session 1: basic knowledge of R
• Session 2: basic knowledge of data structures in R
• Session 3: basic knowledge of data structures in R

Teacher

Dries Reynders studied Physics and Statistical Data Analysis at Ghent University.

He is an experienced teacher and is, in that role, well trained in explaining the link between mathematics and the reality it describes. Currently, he works as statistical consultant for the Stat-Gent consortium.

Course material

Extended example-code is shared, and can serve as template for your own reports.

Fees

A different price applies, depending on your main type of employment.

¹ If three or more employees from the same company enrol simultaneously for this course a reduction of 10% on the module price is taken into account.

² AUGent-staff and AUGent doctoral students who pay through use of an SAP internal order/invoice can participate at these special rates.

Enrol for this course