M7 - Leverage your R Skills: Data Wrangling & Plotting with Tidyverse

Target audience

This course targets anyone who wants to use R for data processing and needs to produce professional looking graphs and/or summary statistics.

Description

Tidyverse is a collection of R-packages used for data wrangling and visualization that share a common design philosophy. The goal of this course is to get you up to speed with the most up-to-date and essential tidyverse tools for data exploration. After attending this course, you’ll have the tools to tackle a wide variety of data wrangling and visualization challenges, using the best parts of R tidyverse.

This course covers the most essential tools from 3 main R tidyverse packages that are frequently used in general data analysis procedure.
Lectures with R code demonstrations are blended with hands-on exercises which allows you to try out the tools you’ve seen in the class under guides.

What you will learn:

  • Data transforming and summarizing with dplyr: narrowing in on observations of interest, creating new variables that are functions of existing variables, and calculating a set of summary statistics (like counts or means)
  • Data visualization with ggplot2: creating more informative graphs (e.g., scatter plot, bar plot, histogram, smoother/regression line, …) in an elegant and efficient way. Arranging multiple plots on a grid
  • Data ingest and tidying with tidyr: storing it in a consistent form that matches the semantics of the dataset with the way it is stored.
  • Extra tools for programming: Merging and comparing two datasets based on various matching or filtering criterion. Other useful tools for R programming.

Not included in this course:

  • A systematic training guide in basics of R. If you never used R or RStudio before, we highly recommend you to take Module 1 of this year's program which will guide you to be familiar with the R environment for the implementation of data management and exploration tasks.
  • Big data. This course focuses on small, in-memory datasets as you can’t tackle big data easily unless you have experience with small data.
  • Statistics. Although you will see many basic statistics in this course, the main focus is on R and the tidyverse tools instead of explaining the statistical concepts.

Course prerequisites

The course is open to all interested persons. Basic R skills as provided in Module 1 of this year's program are strongly advised.

Exam / Certificate

There is no exam connected to this module. Participants who attend all three classes receive a certificate of attendance via e-mail at the end of the course.

Microcredential

This module is part of the microcredential 'Data Analysis in R: Basics and Beyond' that consists of three modules:

  • Module 1 - Getting Started with R Software for Data Analysis
  • Module 7 - Leverage your R Skills: Data Wrangling & Plotting with Tidyverse
  • Module 8 - Dynamic Report Generation with R Markdown

If you are planning on registering for all three modules, consider enrolling for the microcredential instead. Read more...

Type of course

This is an on campus course. We offer blended learning options if, exceptionally, you can't attend a session on campus.

Schedule

Three afternoons in February 2023: February 6, 7 & 9, 2023, from 1.30 pm to 4.30 pm.

Venue

Faculty of Science, Campus Sterre, Krijgslaan 281, building S5, 9000 Gent

Teacher

Foto Limin LiuDr. Limin Liu is a postdoc researcher at the Center for Statistics at Ghent University. She studied social work and sociology in Beijing and Berlin where she has accumulated several years of research experience in the field of sociology of eduction, social mobility and stratification. Upon her empirical research experience, she achieved a Master in Statistical Data Analysis at Ghent University. Since 2019, she has joined the team of statisticians and focused on both qualitative and quantitative research methods. She is experienced in guiding beginners from both academic and industry environment.

Course material

All course materials e.g., lecture slides, data, R scripts, exercises and solutions, will be made available at least one day before the start of the course as an RStudio project.

Fees

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

Employment Course fee (€)
Industry, private sector, profession* 420
Nonprofit, government, higher education staff 315
(Doctoral) student, unemployed 140

*If two or more employees from the same company enrol simultaneously for this course a reduction of 20% on the module price is taken into account starting from the second enrolment.

Register

Register for this course

UGent PhD students

As UGent PhD student you can incorporate this 'transferable skills seminar' in your Doctoral Training Program (DTP). To get a refund of the registration fee from your Doctoral School (DS) please follow these strict rules and take the necessary action in time. The deadline to open a dossier on the DS website (Application for Registration) for this course is January 6, 2023.

Opening a dossier with your DS does not mean that you are enrolled for the course with our academy. You still need to enrol via the registration form on this site.