Plotting
Once the data and results are ready to be displayed, there’s just as much of an art as there is a science as to how to do so effectively. In this section we’ll go over common types of plots that we think you might want to be familiar with, and discuss how common types of plotting “goals” can be achieved.
- Basics of PlottingA one-page summary of the goals of plotting data and what to keep in mind while doing it
- Introduction to ggplot2Here we go over the use of the useful and common package for plotting
- Iterative PlottingThe process of building up a plot through iterative testing
- Facetting & GridsMaking multiple “panels’ in a plot by some grouping factors
- Plotting Multiple DataFramesMaking plots that work by pulling in different sources of data for different components of the plot
- DistributionsPlotting the shapes of various distributions
- Part to Whole ComparisonsUsing plots to highlight the differences between particular sections of the data at hand
- Relationships Between VariablesPlotting the different relationships between variables in our results
- MappingPlotting geographical maps from multiple spatial and non-spatial data
- AnnotationsAdding components like extra text and shapes to a plot
- Values Between GroupsPlotting to highlight how specific key variables are different across key groups
- Phylogenetic TreesVisualizing the phylogenetic relationships between organisms in both classical and circular trees
About R Manual
Learn more about this project
The R Manual is a resource jointed authored by Cole Brookson, Dr. Shelby Riskin, and Dr. Jacqueline Sztepanacz. This resource is not officially affiliated with the R Programming language, but aims to help students with the steep learning curve associated with learning R for the first time.
Funding
This project is made possible through the University of Toronto Learning & Education Advancement Fund (LEAF) program
Additional Resources
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U of T Coders
Student-led UofT support system for learning programing
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The Carpentries
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