Data Visualization in R

Research Computing Center

John Crerar Library - Kathleen A. Zar Room

Data Science as an interdisciplinary field has become more popular. As an important component of the data pipeline, data visualization helps data scientists understand data and results better both in the exploratory and analytical phases. The R programming language is rich in visualization. A few comprehensive visualization systems, such as baseR, ggplot2, and lattice, are built on top of R, making the language stand out in the world of data visualization. The tidyverse ecosystem of R packages, for example, is specifically tailored for Data Science, and it has made the R programming language popular. ggplot2, which is one of the core packages in tidyverse, offers users a comprehensive way to visualize data. In addition, the package has rich statistical graphics theory being embedded. Without understanding such theory, the visualization know-how can be challenging.&nbsp; In this workshop, we will first introduce the basics of data visualization with a focus on the grammar of graphics, then some hands-on exercises will be offered to consolidate the understanding of visualizing data using a few built-in datasets. The workshop will cover most of the commonly used visualizations such as line plots, scatterplots, heatmaps, and maps, etc. Also, we will provide solutions to spruce up visualizations for publication purposes. After the workshop, users will know how to use R to visualize data in their research and work.&nbsp; Objectives: <ul><li>Attendees will learn the basic visualization theory</li><li>Attendees will get exposed to the richness of visualization in R</li><li>Attendees will learn data visualization basics in R</li><li>Attendees will learn how to use R to carry out and tidy up visualizations</li><li>Attendees will learn how to make maps</li><li>Attendees will have opportunity to visualize data using a few real-world datasets</li></ul> Prerequisites: Basic R programming skills and a laptop with RStudio and tidyverse installed.Length: 2 HoursLevel: Intermediate

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Data Visualization in R

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Data Visualization in R

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