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UCLA QCBio Collaboratory workshop W28: Advanced Data Visualization with ggplot2

Author: Wenbin Guo
Last Update: 2024 Fall

Description

This advanced workshop provides a comprehensive introduction to data visualization in R, with a focus on mastering ggplot2 (https://ggplot2.tidyverse.org/) to create effective, insightful graphics. Tailored for participants with a foundational knowledge of R, the workshop covers topics like data wrangling, visualization principles, and advanced techniques to customize and expand visualizations. Participants will gain hands-on experience and explore the art and science of visualization, learning to manipulate data and create plots that are clear, accurate, and visually engaging. For registration information, please refer to this link

Schedule

The workshop is taught every quarter (3-day workshop, 3 hours per day).

Day 1: Introduction to data wrangling and visualization

  • R/RStudio environment setup
  • Overview of data visualization: key concepts and workflow
  • Data manipulation and transformation with dplyr
  • Introduction to ggplot2 and the grammar of graphics
  • Hands-on exercises with dplyr and ggplot2

Day 2: In-depth exploration of ggplot2

  • Aesthetics, visual elements, and geometric objects
  • Layer components and varous types of plots
  • Scales (size, shape, colour, position) control
  • Coordinate systems and facets
  • Creating basic plots with ggplot2: histogram, bar chart, boxplot, scatter plot, etc.

Day 3: Customization and advanced topics in ggplot2

  • Customizing titles, axes, legends, and themes
  • Principles of data visualization and best practices
  • Exploring ggplot2 extension packages
  • Building and customizing complex visualizations with ggplot2

Requirements

Technical:

R/RStudio

Prerequisite:

Participants should have basic knowledge and experience with R programming. Familiarity with R data structures, such as factors, vectors, and data frames will be beneficial.

Folder Description

  • slides: slides for each day of the workshop
  • dayN: example code and exercises for each day’s topics

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