Data Visualization with R

Data Visualization with R

This course is part of multiple programs.

Instructors: Yiwen Li

Access provided by Trybe

31,535 already enrolled

4 modules

Gain insight into a topic and learn the fundamentals.

269 reviews

Beginner level

No prior experience required

Flexible schedule

1 week at 10 hours a week

Learn at your own pace

96%

Most learners liked this course

4 modules

Gain insight into a topic and learn the fundamentals.

269 reviews

Beginner level

No prior experience required

Flexible schedule

1 week at 10 hours a week

Learn at your own pace

96%

Most learners liked this course

What you'll learn

Create bar charts, histograms, pie charts, scatter plots, line graphs, box plots, and maps using R and related packages.
Design customized charts and plots using annotations, axis titles, text labels, themes, and faceting.
Create maps using the Leaflet package for R.
Create interactive dashboards using the Shiny package for R.

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

13 assignments¹

AI Graded see disclaimer

Taught in English

See how employees at top companies are mastering in-demand skills

Learn more about Coursera for Business

logos of Petrobras, TATA, Danone, Capgemini, P&G and L'Oreal

Build your subject-matter expertise

This course is available as part of

When you enroll in this course, you'll also be asked to select a specific program.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 4 modules in this course

In this course, you will learn the Grammar of Graphics, a system for describing and building graphs, and how the ggplot2 data visualization package for R applies this concept to basic bar charts, histograms, pie charts, scatter plots, line plots, and box plots. You will also learn how to further customize your charts and plots using themes and other techniques. You will then learn how to use another data visualization package for R called Leaflet to create map plots, a unique way to plot data based on geolocation data. Finally, you will be introduced to creating interactive dashboards using the R Shiny package. You will learn how to create and customize Shiny apps, alter the appearance of the apps by adding HTML and image components, and deploy your interactive data apps on the web.

You will practice what you learn and build hands-on experience by completing labs in each module and a final project at the end of the course. Watch the videos, work through the labs, and watch your data science skill grow. Good luck! NOTE: This course requires knowledge of working with R and data. If you do not have these skills, it is highly recommended that you first take the Introduction to R Programming for Data Science as well as the Data Analysis with R courses from IBM prior to starting this course. Note: The pre-requisite for this course is basic R programming skills.

Data without a way to convey the story behind it to yourself or others is just numbers on a page. You can observe and tell the story of your data in a more impactful way through visualization. In this module, you will learn the basics of data visualization using R, including the fundamental components that are shared by all charts and plots, and how to bring those components to life using the ggplot2 package for R. You will also learn how to create three common chart types, including bar, histogram, and pie charts, from the qualitative and quantitative data.

What's included

5 videos3 readings4 assignments1 app item1 plugin

5 videos Total 21 minutes

Introduction to Data Visualization 4 minutes
Using ggplot2 5 minutes
Bar Charts 4 minutes
Histograms 4 minutes
Pie Charts 5 minutes

3 readings Total 9 minutes

Course Introduction 3 minutes
Summary & Highlights 3 minutes
Summary & Highlights 3 minutes

4 assignments Total 24 minutes

Graded Quiz 6 minutes
Graded Quiz 6 minutes
Practice Quiz 6 minutes
Practice Quiz 6 minutes

1 app item Total 20 minutes

Hands-on Lab: Apply Basic Chart Learning 20 minutes

1 plugin Total 15 minutes

Cheat Sheet: Basic Plots 15 minutes

In this module, you will take your data visualization skills to the next level! You will learn how to create three plot types, including scatter plots, line, plots, and box plots, using the ggplot2 library and then customize the visualizations using annotations and customized axis titles and text labels. You will also learn about faceting, a way to visualize each level of a discrete or categorical variable, and different ways to work with themes. Finally, you will learn about a unique chart type called a map that you can create using geolocation data and the Leaflet library.

What's included

6 videos2 readings4 assignments2 app items3 plugins

6 videos Total 32 minutes

Scatter Plots 4 minutes
Line Plots 6 minutes
Box Plots 5 minutes
Customize Plots 6 minutes
Themes and Faceting 6 minutes
v2.2.3 - Maps with Leaflet 4 minutes

2 readings Total 10 minutes

Summary & Highlights 5 minutes
Summary & Highlights 5 minutes

4 assignments Total 28 minutes

Graded Quiz 6 minutes
Graded Quiz 8 minutes
Practice Quiz 6 minutes
Practice Quiz 8 minutes

2 app items Total 75 minutes

Hands-on Lab: Apply Basic Plot Learning 30 minutes
Hands-on Lab: Apply Maps Learning 45 minutes

3 plugins Total 45 minutes

Cheat Sheet - Basic Plots 15 minutes
Cheat Sheet - Customization and Maps 15 minutes
Cheat Sheet - Customization and Maps using Leaflet 15 minutes

Your data tells a story. You have built the charts and plots that show important relationships between variables, identify outliers and anomalies, and see the trends that can help you predict what the future might bring. Now you want to put these insightful data visualizations at the fingertips of your stakeholders and make it easy to interact with and explore the data. You need a dashboard! In this module, you will learn why dashboards are important and then build interactive dashboards using the Shiny package for R. You will learn how Shiny dashboards are structured into user interface and server components and then build out these components and develop the logic to make them work together. You will also learn how to deploy your dashboards and provide a way to generate informative reports with R Markdown.

What's included

6 videos2 readings4 assignments2 ungraded labs5 plugins

6 videos Total 32 minutes

Introduction to Dashboards & Shiny 5 minutes
Shiny Basics 6 minutes
Create a Simple Shiny App 6 minutes
Explore Shiny Components 5 minutes
Deploy the Shiny App 5 minutes
Reports in rmd 6 minutes

2 readings Total 15 minutes

Summary & Highlights 10 minutes
Summary & Highlights 5 minutes

4 assignments Total 28 minutes

Graded Quiz 8 minutes
Graded Quiz 6 minutes
Practice Quiz 8 minutes
Practice Quiz 6 minutes

2 ungraded labs Total 120 minutes

Hands-on Lab: Create a Shiny App (using Coursera Labs) 60 minutes
Hands on Lab: Shiny Components (using Coursera Labs) 60 minutes

5 plugins Total 75 minutes

(Optional) Lab: Getting started with Posit Cloud 15 minutes
(Optional) Lab: Create Shiny App on Posit Cloud 15 minutes
Cheat Sheet - DashBoard 15 minutes
(Optional) Hands on Lab: Shiny Components on Posit Cloud 15 minutes
Cheat Sheet - Dashboard Application 15 minutes

What's included

3 readings1 assignment1 peer review1 app item1 ungraded lab2 plugins

3 readings Total 9 minutes

Final Project Overview – Dashboard with Shiny using Census Data 5 minutes
Congratulations and Next Steps 2 minutes
Credits and Acknowledgments 2 minutes

1 assignment Total 50 minutes

Final Exam 50 minutes

1 peer review Total 30 minutes

Option 2 - Peer Graded: Final Project - Submission and Evaluation 30 minutes

1 app item Total 20 minutes

Option 1 - AI Graded: Final Project - Submission and Evaluation 20 minutes

1 ungraded lab Total 60 minutes

Final Lab: Dashboard with Shiny using Census Data (on Coursera Labs) 60 minutes

2 plugins Total 20 minutes

Reading: Final Project Submission Guidelines and Deliverables 5 minutes
(Optional) Final Lab: Dashboard with Shiny using Census Data (on Posit Cloud) 15 minutes

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

Instructors

Instructor ratings

(65 ratings)

Yiwen Li

IBM

2 Courses 51,004 learners

Offered by

IBM

Why people choose Coursera for their career

Felipe M.

Learner since 2018

"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."

Jennifer J.

Learner since 2020

"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."

Larry W.

Learner since 2021

"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."

Chaitanya A.

"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."

Learner reviews

5 stars
76.95%
4 stars
15.98%
3 stars
3.34%
2 stars
1.48%
1 star
2.23%

Showing 3 of 269

Reviewed on Nov 7, 2024

The material is presented in "pieces" that are too large. There is a basic understanding of R that needs to be built prior to using the visualization tools.

Reviewed on Jul 9, 2022

The course was good and the videos explained the topic very well and the content was indeed very nice..thanks for providing such a good course

Reviewed on May 24, 2023

Great content. However, i think the labs should be more detailed

View more reviews