The material is structured within thirteen small modules. Each module covers various related topics through appropriate case studies, presentations and readings. The conceptual ideas come to life when practice becomes reality which is why the material is designed as a hands on taught workshop, through the application of R. The workshop provides the opportunity for participants to test their knowledge, both conceptual and practical by adopting an interactive student/teacher approach. Students are expected to use their own time to practise and hone the data handling expertise acquired during the workshop.
We recommend you complete tasks marked as Your Turn the end of each section.
RStudio IDE; R language; Introduction to Visualization Principles; Data Wrangling and Visualising Data; R Markdown
What you will learn:
Basic use of R/RStudio console
Good habits for workflow
Inputting and importing different data types
R environment: record keeping
Data classification
Descriptive summary statistics
dplyr’s key data manipulation verbs: select, mutate, filter, arrange and summarise/summarize
to aggregate data by groups
to chain data manipulation operations using the pipe operator
basic principles of effective data visualisation
to specify ggplot2 building blocks and combine them to create graphical display
about the philosophy that guides ggplot2: grammatical elements (layers) and aesthetic mapping
visualising data with maps
authoring R Markdown reports; embedding R code; LaTex to incorporate mathematical expressions