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Advanced Data Visualization with R

Approx. 11 hours to complete

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Course Summary

Learn advanced data visualization techniques with R in this course offered by Johns Hopkins University. Gain practical skills in creating and customizing a variety of visualizations for effective data communication.

Key Learning Points

Learn to create custom visualizations using ggplot2
Explore interactive visualization tools like Plotly and Shiny
Understand principles of good data visualization and effective communication

Learning Outcomes

Create and customize a variety of visualizations using R
Understand principles of effective data communication
Use interactive visualization tools to enhance data analysis

Prerequisites or good to have knowledge before taking this course

Basic knowledge of R programming
Familiarity with data analysis concepts and techniques

Course Difficulty Level

Advanced

Course Format

Online
Self-paced
Video Lectures

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Related Education Paths

Notable People in This Field

Nathan Yau
Alberto Cairo

Related Books

Description

Data visualization is a critical skill for anyone that routinely using quantitative data in his or her work - which is to say that data visualization is a tool that almost every worker needs today. One of the critical tools for data visualization today is the R statistical programming language. Especially in conjunction with the tidyverse software packages, R has become an extremely powerful and flexible platform for making figures, tables, and reproducible reports. However, R can be intimidating for first time users, and there are so many resources online that it can be difficult to sort through without guidance.

This course is the third in the Specialization "Data Visualization and Dashboarding in R." Learners come into this course with a foundation using R to make many basic kinds of visualization, primarily with the ggplot2 package. Accordingly, this course focuses on expanding the learners' inventory of data visualization options. Drawing on additional packages to supplement ggplot2, learners will made more variants of traditional figures, as well as venture into spatial data. The course ends make interactive and animated figures. To fill that need, this course is intended for learners who have little or no experience with R but who are looking for an introduction to this tool. By the end of this course, students will be able to import data into R, manipulate that data using tools from the popular tidyverse package, and make simple reports using R Markdown. The course is designed for students with good basic computing skills, but limited if any experience with programming.

Outline

Advanced Figures with ggplot2
Variations on Scatterplots
Variations on Line Plots
Flows and Circles
Note on Previewing Figures in R Studio
Adding Best Fit Lines
Drawing Scatterplot Matrices
Correlation Plots
Dot Plots
Shading in a line plot
Making a stacked area graph
Making dumbbell charts
Making Alluvial Diagrams
Packed Circles Figures
Pie Charts
A Note About Peer Review Assignments
Scatterplot Variations Quiz
Additional Temporal Figures Quiz
Flows and Circles Quiz

Spatial Data
Introduction to Maps
Choropleths
Bubble Maps
Simple Features Maps
Wickham Chapter 7
R Graph Gallery for Maps
Note on sf library
A Note on Data for Simple Features Maps and albersusa
Simple Features for R Documentation
Spatial Figures Quiz

Plotly and gganimate
gganimate Part 1
gganimate Part 2
gganimate Part 3
ggplotly Part 1
ggplotly Part 2
Note: Known issue with gganimate
gganimate
Making ggplot figures interactive with ggplotly()
Animating ggplot figures with ggplotly
gganimate Quiz
ggplotly Quiz

Summary of User Reviews

Discover the power of advanced data visualization with R with the JHU Advanced Data Visualization R course on Coursera. This course has received positive reviews from learners, with many citing its comprehensive coverage of data visualization techniques as a standout feature.

Key Aspect Users Liked About This Course

Comprehensive coverage of data visualization techniques

Pros from User Reviews

Great course for learning advanced data visualization techniques using R
Excellent instructor who explains concepts clearly and thoroughly
Hands-on exercises and assignments help learners gain practical experience
Provides useful tips and tricks for creating effective visualizations
Course materials are well-organized and easy to follow

Cons from User Reviews

Some learners may find the course challenging if they are new to R programming
Course content may not be suitable for those seeking a basic introduction to data visualization
Some learners may prefer more interactive learning experiences
Learners who are not comfortable with statistics may struggle with certain concepts
Course may require a significant time commitment to complete

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