Data Visualization
by Aihua Li · Ball State University
Ball State University course on visualizing large datasets in R across five modules. Covers exploratory analysis with ggplot2, histograms, scatter plots and box plots, colour choices, interactive and spatial maps, and R Markdown reports, ending with a build-your-own visualization project.
More resources on Data Visualization
PolicyViz
Jon Schwabish interviews researchers, designers, and analysts about presenting data clearly, covering chart choice, color, annotation, and slide design. Episodes mix craft-level technique with the working habits organizations need to turn analysis into communication people actually read.
flowingdata.com
FlowingData is a data visualization blog that teaches how to tell stories with data, featuring tutorials, design tips, case studies, and a gallery of real-world charts, dashboards, and infographics.
data-to-viz.com
Data-to-Viz is a practical reference and gallery of data visualization techniques, offering clear explanations of many chart types, best-use scenarios, and visual examples to illustrate effective data storytelling.
Flourish
Browser-based tool for building animated and interactive charts, maps and scrollytelling stories from spreadsheet data using preset templates, with no coding needed. Publishing and embedding are free on public projects.
Datawrapper
Web tool used widely in newsrooms to turn spreadsheet data into publication-quality charts, maps and tables. You paste data, pick a chart type, refine labels and colors, then embed the responsive result.
Observable
A reactive JavaScript notebook platform for exploratory data work, where cells re-run automatically as inputs change. Useful for prototyping D3 and Plot visualizations, sharing runnable code, and studying published notebooks from the visualization community.