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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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What's inside

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.

Module 2 - Basic Plots, Maps, and Customization

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.

Module 3 - Dashboards

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.

Module 4 - Final Assignment

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

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

Relevant and engaging data visualization course for all skill levels

Learners say that this course titled "Data Visualization with R" is well-received and well-suited for learners of all skill levels. Students are largely positive about the engaging assignments, relevant content, and well-structured labs. Learners also report that the instructors are knowledgeable and that the course material is high quality. One common critique is that a cheat sheet for course codes and syntax would be helpful.

Students report that the instructors are knowledgeable.

"Great Course material. Awesome **Instructors**!"

"Dear Professors.Thank you for sharing your knowledge. I learned a lot in this course, especially regarding ggplot and shiny."

"Thank you!"

Learners appreciate the engaging assignments.

"learnt a lot of things ..it a very good course."

"great i learned alot and practice many things in a different way,thanks coursera"

"This was an amazing course. There were a lot of concepts to digest."

Learners report that the course material is high quality.

"very useful course"

"very knowledgeble"

"good course skills training and application introduction, applied sciences."

Learners highly value the relevant course content.

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

"I cannot over emphasize how IBM courses are very **relevant** and yet engaging even for my busy schedule."

"The course was good and the videos explained the topic very well and the content was indeed very nice."

Learners request a cheat sheet for course codes and syntax.

"One suggestion for improvement I have is that a cheat-sheet or catalogue of sorts be provided within the course, which collates all the coding and syntax from the course onto one single space."

"This is especially helpful while taking up the course as part of the specialization series. It isn't easy to remember precise code syntax after just one or two uses of a function."

"As I progressed through the courses in the specialization, I found myself having to return to previous courses and comb through the hands-on labs to retrieve specific codes, functions and syntaxes."

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 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 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 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

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

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

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

What's inside

Syllabus

Good to know

Save this course

Reviews summary

Relevant and engaging data visualization course for all skill levels

Activities

Career center

Reading list

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