Getting Started with Data Visualization in R
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Course Summary
This course is an introduction to data visualization using R programming language. It covers basic principles of data visualization, such as identifying the right visualization method for different types of data, selecting appropriate colors and fonts, and designing effective charts and graphs.Key Learning Points
- Learn the basics of data visualization using R programming language
- Understand how to identify the right visualization method for different types of data
- Learn how to design effective charts and graphs
Related Topics for further study
Learning Outcomes
- Understand the principles of data visualization
- Learn how to use R programming language for data visualization
- Design effective charts and graphs
Prerequisites or good to have knowledge before taking this course
- Basic knowledge of R programming language
- Familiarity with data analysis and statistics
Course Difficulty Level
IntermediateCourse Format
- Online
- Self-paced
- Video lectures
Similar Courses
- Data Visualization with Python
- Graphical Data Analysis with R
- Data Visualization with Tableau
Related Education Paths
- Data Science Specialization
- Applied Data Science with Python Specialization
- Data Engineering, Big Data, and Machine Learning on GCP Specialization
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
- Getting Started with Data Management and Visualization with R
- Introduction to the Course
- Introduction to R and Software Installation
- Basic R, Part 1
- Basic R Part 2
- Functions in R
- Dataframes
- Basics of Importing Data into R
- Base R Visualizations
- How to Watch the Videos
- The RStudio Cheat Sheet
- Base R Cheat Sheet
- R for Data Science, Chapter 4
- A Note on File Paths
- CCES Data
- Cookbook for R: Basic Plots
- Install R and Setup Quiz
- Base R and Functions Quiz
- Dataframes and Importing Data in R
- Base R Visualization Quiz
- Using the Tidyverse packages
- Introduction to the tidyverse
- Data import and structure in the tidyverse
- Filtering, selecting, recoding, renaming, and piping
- Recoding, Renaming, and Calculating Columns
- Grouping and summarizing data
- R for Data Science, Introduction and Part II: Wrangle
- Data Import Cheat Sheet
- tibble, readr, and tidyr Documentation
- R for Data Science, Chapter 5
- Data Wrangling Cheat Sheet
- Getting Started with dplyr
- Learning to Read R Documentation
- Tidyverse Introduction Quiz
- Manipulating Variables and Creating Summaries Quiz
- Using R Markdown to Make Reports
- Creating reports with R Markdown
- R Markdown syntax and tables
- qplots and closing thoughts
- Note on Installing LaTex
- Note on Previewing Figures in R Markdown
- R for Data Science, Chapter 27
- R Markdown Cheat Sheet
- R Markdown Reference Guide
- R Markdown: The Definitive Guide
- qplot() Documentation
- A Note About Peer Review Assignments
- R Markdown Intro Quiz
- R Markdown Syntax Quiz
- Incorporating Tables and Figures Quiz
Summary of User Reviews
Discover the world of data visualization with R in this course offered by Johns Hopkins University. Students praise the course for its clear and concise explanations, as well as the practical examples that are provided throughout. Overall, the course is highly recommended for anyone interested in learning more about data visualization.Key Aspect Users Liked About This Course
Many users appreciate the practical examples provided throughout the course.Pros from User Reviews
- Clear and concise explanations
- Practical examples are provided throughout
- Great course for beginners
- Well-structured and easy to follow
- Instructors are knowledgeable and engaging
Cons from User Reviews
- Some users feel that the course moves too slowly
- The course is not challenging enough for more experienced users
- Some sections could benefit from more in-depth explanations
- Lack of interaction with other students
- No real-world projects or assignments
Collin Paschall
4.8 Raiting
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