| Topic | Data visualization |
| Objectives | Learn data visualization with ggplot2 and basic data wrangling with tidyverse |
| Dataset | The John Hopkins CSSE Covid-19 dataset. |
| Language | R |
| Libraries [OPTIONAL] | tidyverse_1.3.0, lubridate_1.7.4, [ggthemes_4.2.0], [ggrepel_0.8.0.9000], [hrbrthemes_0.6.0] |
| Level | Beginner to Intermediate |
| Pre-requisites | Basic familiarity with R, RStudio, and RMarkdown |
We will do a live, interactive coding workshop to learn how to create the following plot:
Instructions are provided in workspace/data-vis.Rmd (Rmarkdown file)
and workspace/data-vis.html (pre-rendered HTML file - download the raw and open in a web browser to see)
Please click the following button if you like to use a web version of JupyterLab or RStudio with dependencies installed via Binder
- gganimate - Make animation with ggplot2
- Themes:
- ggrepel - Avoid text / label overlapping in ggplot2
- Interactive graph: ggiraph, plotly
- Combining ggplot: cowplot, patchwork
- Utilitis:
- extrafont - use custom font
- RColorBrewer - select color based on colorbrewer2 pallete
- Lower-level engine:
- grid graphic - low-level system for plotting in R
- gtable - layout engine for
ggplot2, built on top ofgridgraphic system
Special mention: ggplot2 extension gallery - A collection of popular ggplot2 extension
- A collection of data visualization books on Information is Beautiful
- Data visualization gallery:
- Flowing Data
- WTF Viz - How NOT to visualize
- Visualization of Biomedical Data - O'Donoghue SI et al. 2018
- Visualization Analysis and Design book by Tamara Munzer (view on Amazon)
- ggplot2: Elegant Graphics for Data Analysis by Hadley Wickham
- Fundamentals of Data Visualization by Claus O. Wilke
- Interactive web-based data visualization with R, plotly, and shiny by Carson Sievert
- Tableau
- JavaScript:
- Python-based: