Lesson 6
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IS428 Visual Analytics for Business Intelligence
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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)
