- Level Foundation
- المدة 11 ساعات hours
- الطبع بواسطة Johns Hopkins University
-
Offered by
عن
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.الوحدات
Extensions of Scatterplots
1
Assignment
- Scatterplot Variations Quiz
1
Videos
- Variations on Scatterplots
5
Readings
- Note on Previewing Figures in R Studio
- Adding Best Fit Lines
- Drawing Scatterplot Matrices
- Correlation Plots
- Dot Plots
More figures for temporal data
1
Assignment
- Additional Temporal Figures Quiz
1
Videos
- Variations on Line Plots
3
Readings
- Shading in a line plot
- Making a stacked area graph
- Making dumbbell charts
Flows and Circles
1
Assignment
- Flows and Circles Quiz
1
Peer Review
- Advanced ggplot Figures
1
Videos
- Flows and Circles
4
Readings
- Making Alluvial Diagrams
- Packed Circles Figures
- Pie Charts
- A Note About Peer Review Assignments
Choropleths and Bubble Maps
3
Videos
- Introduction to Maps
- Choropleths
- Bubble Maps
2
Readings
- Wickham Chapter 7
- R Graph Gallery for Maps
Maps using Simple Features
1
Assignment
- Spatial Figures Quiz
1
Peer Review
- Spatial Figures Peer Review
1
Videos
- Simple Features Maps
3
Readings
- Note on sf library
- A Note on Data for Simple Features Maps and albersusa
- Simple Features for R Documentation
Animations with gganimate
1
Assignment
- gganimate Quiz
3
Videos
- gganimate Part 1
- gganimate Part 2
- gganimate Part 3
2
Readings
- Note: Known issue with gganimate
- gganimate
Plotly
1
Assignment
- ggplotly Quiz
1
Peer Review
- Animations and Interactivity Peer Review
2
Videos
- ggplotly Part 1
- ggplotly Part 2
2
Readings
- Making ggplot figures interactive with ggplotly()
- Animating ggplot figures with ggplotly
Auto Summary
"Advanced Data Visualization with R" is an essential course for professionals across various fields who regularly handle quantitative data and seek to enhance their data presentation skills. This course, part of the "Data Visualization and Dashboarding in R" Specialization, is firmly rooted in the Data Science & AI domain and is delivered by Coursera. Learners will dive deep into the powerful R statistical programming language, specifically focusing on its data visualization capabilities. Building on the foundational knowledge of R and the ggplot2 package, participants will explore a broader range of visualization techniques using additional R packages. The curriculum also covers spatial data visualizations and progresses to creating interactive and animated figures. This 660-minute course is designed for individuals who, despite having limited or no experience with R, possess basic computing skills and are eager to learn. By course completion, participants will be proficient in importing and manipulating data with the tidyverse package and generating reports using R Markdown. Available under the Starter subscription, this course offers a structured, comprehensive introduction to R, making it an attractive option for anyone looking to master advanced data visualization techniques.

Collin Paschall