- Instruction of preparation before the workshop
- Install R
- Install Rstudio
- Install required R packages for this workshop
- Helpful materials and references of R, for example, r cheatsheet, ggplot2 cheatsheet and best practices in visualization
Each session contains R markdown files (basically a coding notebook), but of two version, the one with solution, and the one that does not. To fully take advantage of this workshop, we recommand working on the R markdown files that do not have solutions first so as to evaluate yourself for your understanding of the materials.
- Instruction to the basic R
- Intro to data types and structure of R
- Intro to basic R data exploration/manipulation
- Intro to basic R visualization (advanced functions will be available in session 2)
- Logic control
- How to write your own R function
- Intro to data visualization with R
- Brief intro to ggplot2 (ggplot as an object you can add to, manipulate)
- Why factors are useful (convoluted plot vs. plot where you've grouped things into factors)
- Some cute plots to inspire us
- Intro to efficient data manipulation
- Group_by / summarize / mutate
- Melt
- Reordering levels of factors
- Practicum: Data Manipulation for Better Visualizations
- Find dataset that would lend itself to a heatmap, some kind of x, y plot like a scatter or boxplot, and which would benefit from faceting by a factor and/or a normalizing transformation
- Simple plot (scatter plot or boxplot) -- first without faceting, then with faceting (maybe introducing a factor using dplyr that we can facet by)
- Melting to make a heatmap
- Reordering factors (we could do this on a boxplot or scatterplot easily too-- if we have them build a factor with levels "Low", "Medium", "High" and have to reorder form the default High, Low, Medium order (alphabetical))