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Data Visualization

This LibGuide collects resources and tutorials related to data visualization.

An Introduction to Data Visualization

Data visualization offers ways to transform data into visual representations, allowing us to spot patterns and trends more easily. Data visualization is usually one of three types:

  • Scientific visualization: these tend to be scientific data that is tied to real-world objects with spatial properties. For example, these visualizations include modeling air flow over an airplane. Scientific fields often have specific ways for doing these types of visualizations.
  • Information visualization: these tend to be charts and graphs but also include other visual and spatial representations.
  • Infographic: a specific sort of visualization that combines information visualization with narrative.

Why Visualize?

Workshops

Spring 2020 Schedule

Additional workshops on High Performance Computing are offered by the Holland Computing Center.  See their calendar for more information.

BootcampR: Orientation and Setup (February 11)

Never used R before? Don't have RStudio installed? Need to know how to install libraries in R? Stop by this orientation session to learn the very basics of the software, tools, and methods in R that we'll be using this semester.

BootcampR: R Basics / Intro to the Tidyverse (February 18)

Come learn the basics of base R and methods of the Tidyverse library. This workshop introduces general concepts of the R language how to do basic operations in R, as well as a quick introduction to the tidyverse library that will be used for the remainder of the workshop series.

BootcampR: Spark Joy with Data (February 25)

Do you work with data that often needs cleaning up? Do you have a need to summarize or aggregate data within one source, or among multiple sources? This workshop introduces the dplyr and tidyr methods from the Tidyverse library.

BootcampR: Making Graphs (March 3)

The visualization of data allows us to communicate effectively, spot patterns in large datasets, or simply look for issues with the underlying data. This workshop introduces best practices and principles for data visualization, and works hands-on with the ggplot library from the tidyverse.

BootcampR: Visualizing Networks (March 10)

This workshop introduces methods for building network graphs and conducting social network analysis in R. Attendees will work hands-on with the ggraph, network, and ggplot libraries for creating, analyzing, and visualizing networks.

BootcampR: Making Maps (March 17)

This workshop introduces methods for making maps in R. Leave ArcGIS behind and learn how you can use the sp, ggplot, ggmaps, and related libraries for doing spatial analysis and visualization with R.

BootcampR: Clustering and Classifying (March 31)

Do you need ways of summarizing or aggregating data, or have an interest in machine learning methods for the classification of data? This workshop introduces statistical methods for classifying and clustering data in R.

 

Digital Engagement Librarian

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Dr. Jason Heppler
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