Lesson 6

IS428 Visual Analytics for Business Intelligence

About

Weekly Session

Assignments

Visual Analytics Project

Course Resources

Programming Data Visualisation with R: Methods, Approaches and Best Practices

Content

• An overview of R
  • Introducing R and R Studio
  • Doing data science with tidyverse
• Data Visualisation with R
  • A layered grammar of graphics and ggplot2
  • ggplot2 extensions
  • interactive and dynamic graphics with plotly R
• Reproducible Analytics with R
  • Introducing R Markdown
• Democratizing Visually Driven Analytics on the web
  • Introducing Shiny framework

Core Readings

• What is Tidyverse?
• Tidy Data
• Introduction to dplyr
• Wickham, Hadley (March 2010). "A Layered Grammar of Graphics". Journal of Computational and Graphical Statistics. 19 (1): 3–28.
• What is R Markdown?
• Chapter 18 Pipes in R for Data Science.
• Chapter 10 Tibbles in R for Data Science.

Optional Readings

• Data Tidying
• Wickham, Hadley (2009). ggplot2: Elegant Graphics for Data Analysis. Springer.
• Healy, Kieran (2019) Data Visualization: A practical introduction (online version)
• Chapter 27 R Markdown of R for Data Science.

Self-learning Courses from DataCamp

• Data Visualization with ggplot2 (Part 1)
• Data Visualization with ggplot2 (Part 2)
• Data Visualization with ggplot2 (Part 3)