Visualizing Data with R from edX

In this course, you will learn about 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 R data visualization package called Leaflet to create map plots, a unique way to plot data based on geolocation data. Finally, you will learn about 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. Enroll in the course, watch the videos, work through the labs, and then watch your data science skills grow!

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.

What's inside

Learning objectives

Create basic bar charts, histograms, pie charts, scatter plots, line plots, box plots, and maps using r and related packages, such as ggplot2.
Customize charts and plots using themes and faceting.

Create maps using the leaflet package for r.
Create interactive dashboards using the shiny package for r.

Create basic bar charts, histograms, pie charts, scatter plots, line plots, box plots, and maps using r and related packages, such as ggplot2.
Customize charts and plots using themes and faceting.
Create maps using the leaflet package for r.
Create interactive dashboards using the shiny package for r.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Explores a framework for data visualization that's an industry standard: Grammar of Graphics

Develops skills in data visualization that are foundational for data science

Teaches graphing techniques using the ggplot2 data visualization package for R, a tool popular for its ggplot2 package

Builds a strong foundation for learners in using the Leaflet package for R, a tool used to create maps

Demonstrates how to create interactive dashboards using the R Shiny package, a versatile tool for developing data apps

Provides hands-on practice through labs, reinforcing the concepts learned in each module

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 Visualizing Data with R with these activities:

Create basic visualizations using R

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Refresh your understanding of the basics of data visualizations in R to ensure you have a strong foundation for this course.

Browse courses on Visualizations

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Review basic ggplot2 syntax and chart types
Create a simple bar chart or histogram with R code

Compile a collection of data visualization resources

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Build a curated repository of useful resources, including articles, tutorials, datasets, and tools related to data visualization.

Browse courses on Data Visualization

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Search and identify relevant resources
Organize and categorize the resources

Review the book 'ggplot2: Elegant Graphics for Data Analysis' by Hadley Wickham

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Gain a deeper understanding of the principles and techniques of ggplot2 by reviewing this comprehensive book.

View Advanced R, Second Edition (Chapman & Hall/CRC... on Amazon

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Read and understand the concepts introduced in the book
Follow along with the code examples and exercises provided

15 other activities

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Show all 18 activities

Practice creating basic bar charts

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Will help you gain proficiency and familiarity with how to create bar charts using R.

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Open ggplot2 in R
Create sample dataset
Create a bar chart using the sample dataset

Practice creating histograms

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Will help you reinforce your understanding of creating histograms in R.

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Open ggplot2 in R
Create sample dataset
Create a histogram using the sample dataset

Practice creating pie charts

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Will get you comfortable in creating pie charts using R and ggplot2.

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Open ggplot2 in R
Create sample dataset
Create a pie chart using the sample dataset

Practice creating line plots

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Will aid you in practicing how to create line plots with R.

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Open ggplot2 in R
Create sample dataset
Create a line plot using the sample dataset

Explore the ggplot2 package

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Delve deeper into the features and capabilities of ggplot2 through guided tutorials to enhance your data visualization skills.

Browse courses on Ggplot2

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Follow an online tutorial on using ggplot2
Create a more complex visualization using ggplot2

Join or start a peer group to discuss ggplot2 and data visualization

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Connect with other learners and exchange knowledge by participating in peer-led discussions on ggplot2 and data visualization.

Browse courses on Data Visualization

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Join or create a peer group
Participate in discussions
Share your experiences and insights

Practice creating different chart types

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Reinforce your understanding by practicing the creation of various chart types using R code.

Browse courses on Data Visualization

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Create a scatter plot
Create a line plot
Create a box plot

Complete coding challenges on platforms like LeetCode or HackerRank

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Reinforce your understanding of ggplot2 and other data visualization techniques by solving coding challenges that require you to implement these concepts.

Browse courses on Data Visualization

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Choose a platform like LeetCode or HackerRank
Identify challenges related to data visualization
Solve the challenges using ggplot2 or other relevant packages
Review and analyze your solutions

Discuss visualization techniques with peers

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Engage with fellow learners to exchange ideas and insights on visualization techniques, best practices, and common challenges.

Browse courses on Data Visualization

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Join a study group or online forum
Participate in discussions on visualization topics

Follow online tutorials on advanced ggplot2 techniques

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Expand your knowledge of ggplot2 by exploring online tutorials that cover advanced topics such as faceting, themes, and interactive graphics.

Browse courses on Data Visualization

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Identify online tutorials on advanced ggplot2 techniques
Follow the tutorials and experiment with the code examples
Apply the learned techniques to your own data visualization projects

Volunteer as a mentor for aspiring data visualization learners

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Strengthen your understanding of ggplot2 and data visualization by sharing your knowledge and mentoring others.

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Join a mentoring program or find mentees directly
Provide guidance and support on ggplot2 and data visualization concepts

Develop a data visualization dashboard for a real-world dataset

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Apply the concepts of ggplot2 and dashboard creation to a practical problem by designing and implementing a dashboard that visualizes and analyzes a dataset of your choice.

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Gather and explore a real-world dataset
Design the dashboard layout and visualizations
Implement the dashboard using ggplot2 and Shiny
Test and refine the dashboard for usability
Deploy the dashboard and share it with others

Create a visualization dashboard using Shiny

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Will allow you to apply your skills in creating interactive dashboards using Shiny, which can help you present your data in a more engaging and user-friendly way.

Browse courses on Shiny

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Design the layout and functionality of your dashboard
Create the Shiny app using R code
Deploy your dashboard on a web server

Develop a visualization for a dataset

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Apply your skills to create a visualization that effectively communicates insights from a real-world dataset.

Browse courses on Data Visualization

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Choose a dataset of interest
Explore the data to identify key features
Design and create a visualization

Participate in data visualization competitions or hackathons

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Challenge yourself and showcase your skills by participating in data visualization competitions or hackathons.

Browse courses on Data Visualization

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Identify relevant competitions or hackathons
Form a team or work individually
Develop a data visualization solution
Submit and present your solution

Career center

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

Data Analyst

Data analysts use skills and knowledge gained from courses, such as \"Visualizing Data with R\", to collect, analyze, and interpret data to help organizations make informed decisions. This course helps data analysts build the skills to transform raw data into relevant and actionable insights.

See salaries and explore the career path for Data Analyst

Data Scientist

Data scientists use skills and knowledge gained from courses, such as \"Visualizing Data with R\", to build and deploy machine learning and AI models to identify patterns and trends in data. These insights provide data scientists with valuable information they can use to solve complex problems and make informed decisions.

See salaries and explore the career path for Data Scientist

Data Engineer

Data engineers use skills and knowledge gained from courses, such as \"Visualizing Data with R\", to design, build, and maintain data pipelines to ensure the data used by data scientists and other stakeholders is accurate, reliable, and accessible.

See salaries and explore the career path for Data Engineer

Statistician

Statisticians use skills and knowledge gained from courses, such as \"Visualizing Data with R\", to collect, analyze, and interpret data to draw conclusions and make predictions about the future. This course provides statisticians with the tools they need to communicate complex data in clear and concise ways.

See salaries and explore the career path for Statistician

Machine Learning Engineer

Machine learning engineers use skills and knowledge gained from courses, such as \"Visualizing Data with R\", to build and deploy machine learning models to solve real-world problems. This course helps machine learning engineers develop the skills they need to work with complex datasets and build models that are accurate and efficient.

See salaries and explore the career path for Machine Learning Engineer

Business Analyst

Business analysts use skills and knowledge gained from courses, such as \"Visualizing Data with R\", to analyze data and identify trends and recommend solutions to business problems. This course, by teaching business analysts how to communicate insights from data in clear and compelling ways, helps them succeed in their chosen career field.

See salaries and explore the career path for Business Analyst

Software Engineer

Software engineers use skills and knowledge gained from courses, such as \"Visualizing Data with R\", to design, build, and maintain software applications. This course, by providing software engineers with the skills to develop data visualization dashboards, ensures that the applications they build are both visually appealing and informative.

See salaries and explore the career path for Software Engineer

Data Journalist

Data journalists use skills and knowledge gained from courses, such as \"Visualizing Data with R\", to communicate data-driven stories to the public. This course helps data journalists to create visually appealing and easy-to-understand data visualizations that inform and engage their audience.

See salaries and explore the career path for Data Journalist

UX Designer

UX designers use skills and knowledge gained from courses, such as \"Visualizing Data with R\", to create user-friendly and visually appealing digital products. This course provides UX designers with the tools they need to understand how users interact with data and how to design interfaces that are both intuitive and efficient.

See salaries and explore the career path for UX Designer

Product Manager

Product managers use skills and knowledge gained from courses, such as \"Visualizing Data with R\", to manage the development and launch of new products. This course helps product managers to understand how to use data to make informed decisions about product features and marketing strategies.

See salaries and explore the career path for Product Manager

Marketing Analyst

Marketing analysts use skills and knowledge gained from courses, such as \"Visualizing Data with R\", to analyze marketing data and identify trends and recommend solutions to marketing problems. This course provides marketing analysts with the tools they need to communicate insights from data in clear and compelling ways.

See salaries and explore the career path for Marketing Analyst

Financial Analyst

Financial analysts use skills and knowledge gained from courses, such as \"Visualizing Data with R\", to analyze financial data and make recommendations about investments. This course provides financial analysts with the tools they need to identify trends and make informed decisions about investments.

See salaries and explore the career path for Financial Analyst

Actuary

Actuaries use skills and knowledge gained from courses, such as \"Visualizing Data with R\", to analyze risk and uncertainty to make informed decisions about insurance and other financial products. This course provides actuaries with the tools they need to develop models that can predict future events and make informed decisions about risk.

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Operations Research Analyst

Operations research analysts use skills and knowledge gained from courses, such as \"Visualizing Data with R\", to analyze data and develop solutions to improve the efficiency of operations. This course provides operations research analysts with the tools they need to identify bottlenecks and develop solutions that can improve productivity.

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Epidemiologist

Epidemiologists use skills and knowledge gained from courses, such as \"Visualizing Data with R\", to investigate the causes of disease and develop strategies to prevent and control outbreaks. This course provides epidemiologists with the tools they need to analyze data and identify trends that can help them to identify the causes of disease and develop effective prevention strategies.

See salaries and explore the career path for Epidemiologist