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Data Visualization with R

Yiwen Li, Tiffany Zhu, Saishruthi Swaminathan, and Gabriela de Queiroz

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.

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Syllabus

Module 1 - Introduction to Data Visualization

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.

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Develops data visualization skills using R, including ggplot2 and Leaflet

Builds a foundation for beginners in data visualization

Teaches the basics of data visualization, including components and plots

Provides hands-on practice through labs and a final project

Introduces interactive data visualization using Shiny

Requires prerequisite knowledge of R programming

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Reviews summary

R data visualization for practical applications

According to students, this course offers a largely positive and practical introduction to data visualization in R. Learners particularly praise the clear and comprehensive coverage of ggplot2 and the valuable module on creating interactive dashboards with Shiny. The course's hands-on labs and practical projects are frequently highlighted as effective learning tools. While many find it an excellent foundation, some note that the Leaflet module is a bit brief and emphasize that a solid understanding of R programming prerequisites is essential to avoid struggling with pacing, particularly in the Shiny section. Overall, it's considered highly beneficial for developing practical data visualization skills.

The Leaflet section was seen as brief or niche by some learners.

"The Leaflet module was interesting but felt a bit brief compared to ggplot2 and Shiny."

"I found the Leaflet section a bit niche for my needs, but it was still an interesting introduction."

"You learn about a unique chart type called a map that you can create using geolocation data and the Leaflet library."

Some found pacing effective, others desired more depth or found parts too fast.

"The Shiny part felt too fast-paced for me, and I needed to do additional research."

"While the course gives a good overview, for professional use, one might need to explore more advanced features independently."

"I was hoping for more depth in advanced visualization techniques and custom Shiny development."

"The structure of this course is excellent; it starts with the fundamentals and then moves to more complex topics smoothly."

Effectively teaches the Grammar of Graphics, a key underlying concept.

"The instructor explains the Grammar of Graphics really well, which is crucial for understanding ggplot2."

"I learned the Grammar of Graphics, a system for describing and building graphs, which was a great foundation."

"The Grammar of Graphics explanation is a highlight of the course, making complex ideas accessible."

Features effective labs and a final project for practical application.

"I loved the hands-on labs and the final project, which really cemented my understanding of the concepts."

"The hands-on nature of the course is perfect for learning a coding skill like data visualization in R."

"The emphasis on practical applications and the hands-on approach is what makes this course stand out."

"I found the practical examples and the step-by-step approach in the labs to be very effective."

Excellent coverage of ggplot2 and R Shiny for interactive dashboards.

"The coverage of ggplot2 was exceptionally clear, making complex visualizations understandable."

"I especially loved the Shiny module, which was a game-changer for building interactive dashboards."

"I particularly appreciated the modules on `ggplot2` and `Shiny`; it's a superb starting point."

"The way the course builds from basic plots to interactive Shiny apps is seamless and very effective."

Requires solid basic R knowledge; not suitable for absolute beginners in R.

"Make sure you're comfortable with R before starting; otherwise, you might struggle."

"I came in with basic R but struggled, feeling the prerequisites weren't strongly emphasized enough for my level."

"This course requires knowledge of working with R and data; it is highly recommended to take introductory R courses first."

"It's definitely for people who already have some R experience, as stated, and not for true R novices."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Data Visualization with R with these activities:

Read 'The Visual Display of Quantitative Information'

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Read 'The Visual Display of Quantitative Information' by Edward Tufte to gain a deeper understanding of the principles of data visualization.

View Beautiful Evidence on Amazon

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Purchase the book
Read the book
Take notes
Apply the principles to your own data visualization projects

Explore the RStudio IDE

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Become familiar with the RStudio IDE, which is essential for data science and data visualization.

Browse courses on RStudio

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Install RStudio
Create a new project
Explore the RStudio interface
Write and run your first R script
Debug your code

Join a Study Group

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Join a study group to connect with other students, discuss the course material, and work on projects together. This will help you learn from others and improve your understanding of the concepts.

Browse courses on Collaboration

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Find a study group
Attend study group meetings
Participate in discussions
Work on projects together
Help each other out

Four other activities

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Show all seven activities

Code Along with the Course Videos

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Practice your data visualization skills by coding along with the video tutorials in the course.

Browse courses on Ggplot2

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Watch the video tutorial
Open RStudio
Code along with the video
Run your code
Debug your code if necessary

Build a Data Visualization Portfolio

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Create a portfolio that demonstrates your data visualization skills. This will help you practice your skills and showcase your work to potential employers.

Browse courses on Data Visualization

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Gather your data
Choose the right charts and graphs
Design your visualizations
Create a narrative with your data
Present your portfolio

Create a Data Visualization Blog Post

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Write a blog post that shares your knowledge of data visualization. This will help you solidify your understanding of the concepts and improve your communication skills.

Browse courses on Data Visualization

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Choose a topic
Research your topic
Write your post
Edit and proofread your post
Publish your post

Contribute to the ggplot2 Package

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Contribute to the ggplot2 package to gain experience in open-source development and improve your understanding of the ggplot2 codebase.

Browse courses on Ggplot2

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Find an issue to work on
Fork the ggplot2 repository
Create a branch for your changes
Make your changes
Submit a pull request

Career center

Learners who complete Data Visualization with R will develop knowledge and skills that may be useful to these careers:

Data Visualization Engineer

Data Visualization Engineers design and develop data visualization tools and applications. This course, Data Visualization with R, would be a perfect fit for Data Visualization Engineers as it provides them with the skills they need to design and develop effective data visualizations. The course covers topics such as data cleaning, data transformation, and data visualization. By taking this course, Data Visualization Engineers can gain the skills they need to succeed in their field.

See salaries and explore the career path for Data Visualization Engineer

Data Scientist

Data Scientists are responsible for collecting, analyzing, and interpreting large datasets. This course, Data Visualization with R, can help Data Scientists build the foundation necessary for their work. The course equips learners with the skills to create custom visualizations that communicate complex data in a clear and concise way. With the ability to effectively visualize data, Data Scientists can gain insights from their data and communicate their findings to stakeholders.

See salaries and explore the career path for Data Scientist

Data Analyst

Data Analysts use data to help businesses make better decisions. This course, Data Visualization with R, is highly relevant to Data Analysts as it provides them with the tools they need to analyze and visualize data. The course covers topics such as data cleaning, data transformation, and data visualization. By taking this course, Data Analysts can gain the skills they need to extract insights from data and communicate their findings to stakeholders.

See salaries and explore the career path for Data Analyst

Interactive Data Visualization Developer

Interactive Data Visualization Developers create interactive data visualizations that allow users to explore and understand data. This course, Data Visualization with R, would be a strong fit for Interactive Data Visualization Developers as it provides them with the skills they need to create user-friendly and informative data visualizations. The course covers topics such as data cleaning, data transformation, and data visualization. By taking this course, Interactive Data Visualization Developers can gain the skills they need to succeed in their field.

See salaries and explore the career path for Interactive Data Visualization Developer

Business Analyst

Business Analysts use data to identify and solve business problems. This course, Data Visualization with R, can be useful for Business Analysts as it provides them with the skills they need to analyze and visualize data. The course covers topics such as data cleaning, data transformation, and data visualization. By taking this course, Business Analysts can gain the skills they need to identify inefficiencies, improve processes, and drive better decision-making.

See salaries and explore the career path for Business Analyst

Statistician

Statisticians collect, analyze, interpret, and present data. This course, Data Visualization with R, can help build a foundation for Statisticians, providing them with the skills they need to visualize data in a clear and concise way. The course covers topics such as data cleaning, data transformation, and data visualization. By taking this course, Statisticians can gain the skills they need to communicate their findings to stakeholders and make informed decisions.

See salaries and explore the career path for Statistician

Dashboard Developer

Dashboard Developers design and develop dashboards that provide insights to businesses. This course, Data Visualization with R, would be a great fit for Dashboard Developers as it provides them with the skills they need to create effective dashboards. The course covers topics such as data cleaning, data transformation, and data visualization. By taking this course, Dashboard Developers can gain the skills they need to succeed in their field.

See salaries and explore the career path for Dashboard Developer

Data Engineer

Data Engineers design, build, and maintain data systems. This course, Data Visualization with R, can help build a foundation for Data Engineers, providing them with the skills they need to visualize data in a clear and concise way. The course covers topics such as data cleaning, data transformation, and data visualization. By taking this course, Data Engineers can gain the skills they need to communicate their findings to stakeholders.

See salaries and explore the career path for Data Engineer

Software Engineer

Software Engineers design, develop, and maintain software systems. This course, Data Visualization with R, may be helpful for Software Engineers as it provides them with the skills to visualize data in a clear and concise way. The course covers topics such as data cleaning, data transformation, and data visualization. By taking this course, Software Engineers can gain the skills they need to communicate with stakeholders and develop software that meets their needs.

See salaries and explore the career path for Software Engineer

Product Manager

Product Managers manage the development and launch of new products. This course, Data Visualization with R, may be helpful for Product Managers as it provides them with the skills to analyze and visualize data. The course covers topics such as data cleaning, data transformation, and data visualization. By taking this course, Product Managers can gain the skills they need to make informed decisions about product development and launch.

See salaries and explore the career path for Product Manager

Marketing Analyst

Marketing Analysts use data to understand consumer behavior and develop marketing campaigns. This course, Data Visualization with R, may be helpful for Marketing Analysts as it provides them with the skills to analyze and visualize data. The course covers topics such as data cleaning, data transformation, and data visualization. By taking this course, Marketing Analysts can gain the skills they need to develop more effective marketing campaigns.

See salaries and explore the career path for Marketing Analyst

Financial Analyst

Financial Analysts use data to make investment decisions. This course, Data Visualization with R, may be helpful for Financial Analysts as it provides them with the skills to analyze and visualize data. The course covers topics such as data cleaning, data transformation, and data visualization. By taking this course, Financial Analysts can gain the skills they need to make informed investment decisions.

See salaries and explore the career path for Financial Analyst

Operations Research Analyst

Operations Research Analysts use data to improve the efficiency of organizations. This course, Data Visualization with R, may be helpful for Operations Research Analysts as it provides them with the skills to analyze and visualize data. The course covers topics such as data cleaning, data transformation, and data visualization. By taking this course, Operations Research Analysts can gain the skills they need to identify and solve problems in organizations.

See salaries and explore the career path for Operations Research Analyst

Project Manager

Project Managers plan, execute, and close projects. This course, Data Visualization with R, may be helpful for Project Managers as it provides them with the skills to analyze and visualize data. The course covers topics such as data cleaning, data transformation, and data visualization. By taking this course, Project Managers can gain the skills they need to track project progress and make informed decisions.

See salaries and explore the career path for Project Manager

Business Intelligence Analyst

Business Intelligence Analysts collect and analyze data to provide insights to businesses. This course, Data Visualization with R, may be useful for Business Intelligence Analysts as it provides them with the skills to analyze and visualize data. The course covers topics such as data cleaning, data transformation, and data visualization. By taking this course, Business Intelligence Analysts can gain the skills they need to develop dashboards and reports that provide insights to businesses.

See salaries and explore the career path for Business Intelligence Analyst

Reading list

We've selected 14 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Data Visualization with R.

Advanced R, Second Edition

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Comprehensive guide to the ggplot2 package for R. It covers topics such as data preparation, chart types, and statistical analysis.

Data Visualization with R

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What's inside

Syllabus

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Reviews summary

R data visualization for practical applications

Activities

Career center

Reading list

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