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
Related Topics for further study
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
AdvancedCourse Format
- Online
- Self-paced
- Video Lectures
Similar Courses
- Data Visualization with Python
- Data Visualization with Tableau
- Data Visualization and Communication with Tableau
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.
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 techniquesPros 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
Collin Paschall
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