Explore

Getting Started with Data Visualization in R

Approx. 12 hours to complete

Save Course

Go to Course

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

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

Intermediate

Course Format

Online
Self-paced
Video lectures

Similar Courses

Data Visualization with Python
Graphical Data Analysis with R
Data Visualization with Tableau

Related Education Paths

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.

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

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

Recommended for you

Complete Data Science Training with Python for Data Analysis

Beginners python data analytics : Data science introduction : Learn data science : Python data analysis methods tutorial THIS IS A COMPLETE DATA SCIENCE TRAINING WITH PYTHON FOR DATA ANALYSIS: ...

Save Course

R Programming for Data Science and Machine Learning

Learn R programming to implement Machine Learning & DS algorithms R is one of the most popular and widely used tools for statistical programming....

Save Course

Tableau for Beginners: Get CA Certified, Grow Your Career

Jump into data visualization with hands-on exercises and pass the Certified Associate exam.   Are you looking to find a way to increase your salary and enjoy your work more?...

Save Course

Research Report: Delivering Insights

You have completed all the hard work of conducting your internal, secondary, and primary research. Getting Started & Synthesizing Findings and Deriving Insights...

Save Course