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Exploring Data Visually with R

Martin Burger

Learn how to use data visualizations like scatterplots, barcharts, histograms, and boxplots for data exploration.

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Learn how to use data visualizations like scatterplots, barcharts, histograms, and boxplots for data exploration.

R is very versatile when it comes to data exploration. Any type of chart can be implemented in R. In this course, Exploring Data Visually with R, you will learn the standard visualization techniques that are used for data exploration. First, you will investigate how to use data visualizations. Then, you will explore common datasets with the 4 plot types including scatterplots, barcharts, histograms, and boxplots. Finally, you will be able to use and compare the 3 charting systems, which are R base, lattice, and ggplot2. When you are finished with this course, you will have the skills and knowledge to identify the most suitable chart type and to implement it in 3 different R charting tools.

This course is no longer available. Find something similar by browsing:
Data Visualization R Programming Scatterplots Barcharts Histograms Boxplots R Base

What's inside

Syllabus

Course Overview
Background on Data Visualization in R
Data Visualizations Based on Distributions
Data Visualizations Based on Clusters and Grouping Variables
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Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Introduces fundamentals and techniques of data visualization, a critical skill in data exploration
Suitable for learners looking to enhance their data exploration skills using R
Taught by Martin Burger, an industry expert in data analysis and visualization
Covers various visualization techniques using scatterplots, barcharts, histograms, and boxplots
Provides hands-on experience through practical examples and exercises

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Create your own learning path. Save this course to your list so you can find it easily later.
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Reviews summary

Foundational r data visualization with ggplot2

According to learners, this course provides a solid foundation in R data visualization, especially excelling in its coverage of ggplot2. Students frequently highlight the clear explanations and engaging hands-on activities as key strengths, making it a highly recommended starting point for beginners. However, some learners with prior R experience found the pace slow or content too basic, while a few newer R users noted it might assume some prior R knowledge. Overall, it's considered very useful for practical application, though not ideal for those seeking advanced techniques.
Recent reviews suggest improved quality, though some older critiques mentioned outdated content.
"Disappointing. The course felt outdated in some sections, and the examples weren't always clear."
"The structure from basic concepts to different charting systems (R base, lattice, ggplot2) was very effective."
"Recent parts feel quite current and relevant to modern R practices, which is great for learning current workflows."
Provides an excellent foundational introduction to data visualization concepts in R.
"This course was a fantastic introduction to data visualization in R... Highly recommend for beginners!"
"Perfect for learning the fundamentals. I particularly liked how the course covered different types of plots..."
"A solid foundation for anyone wanting to get into R visualizations. It's a good starting point."
The course excels with its clear teaching style and practical exercises.
"The instructor explained complex concepts very clearly, making it accessible even for someone new to R like me."
"The hands-on exercises really solidified my understanding."
"The instructor's teaching style is engaging. Very useful for my work as a data analyst."
"I appreciated the clear explanations and the structure. This helped me to effectively apply what I learned."
Offers comprehensive and practical lessons on using ggplot2 effectively.
"I particularly loved the practical examples using `ggplot2`. The instructor explained complex concepts very clearly..."
"Good course overall, especially for getting started with `ggplot2`."
"`ggplot2` coverage was a highlight. I think adding more real-world datasets or case studies would elevate it further."
"I found this course really helped me grasp the power of `ggplot2` for creating professional visualizations."
More experienced R users may find the course too slow or lacking in advanced topics.
"The content is okay, but I found some parts a bit too basic. As someone with prior R experience, I was hoping for more advanced techniques..."
"The pace was slow at times. Good for absolute beginners to R and data vis, but not for intermediates."
"While useful for review, I didn't gain many new insights as an intermediate R user seeking more complex topics."
Some learners found it challenging without prior R experience.
"I struggled with this course. While it covers the basics, I felt it assumed too much prior R knowledge..."
"Some explanations were rushed, and the exercises didn't always align with the lecture difficulty. I had to look up a lot of external resources."
"I would advise anyone taking this course to have a basic understanding of R syntax and data structures beforehand."

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 Exploring Data Visually with R with these activities:
Review R Basics
Ensures that students have the necessary programming skills for the course
Browse courses on R Programming
Show steps
  • Review basic R syntax
  • Practice writing simple R scripts
Complete Data Visualization Courses
Provides structured learning and exposure to best practices
Browse courses on Data Visualization
Show steps
  • Identify reputable online courses on data visualization
  • Enroll in a course and complete the modules
Form a Study Group
Offers opportunities to engage with peers and clarify concepts
Browse courses on Collaborative Learning
Show steps
  • Identify classmates who share interests
  • Set up regular meeting times
  • Discuss course material and work on problems together
Four other activities
Expand to see all activities and additional details
Show all seven activities
Walkthrough Practice Exercises Tutorial
Creates proficiency in the use of the R charting tools
Show steps
  • Review the documentation for the `ggplot` package
  • Practice using ggplot to create different types of charts
  • Review the documentation the `lattice` package
  • Practice using lattice to create different types of charts
Build a Data Visualization Dashboard
Provides hands-on experience in applying data visualization to real-world problems
Browse courses on Interactive Visualization
Show steps
  • Identify a business problem or question
  • Collect and clean the necessary data
  • Develop visualizations to answer the question or solve the problem
  • Create an interactive dashboard to present the results
Create Data Visualization Portfolio
Enhances data visualization skills and provides a record of progress
Browse courses on Data Visualization
Show steps
  • Gather a variety of data sets
  • Explore the data and identify insights
  • Create visualizations that effectively communicate the insights
  • Document the process and results in a portfolio
Mentor Junior Students
Reinforces knowledge through teaching and provides opportunities for leadership
Browse courses on Mentoring
Show steps
  • Identify students who would benefit from mentoring
  • Provide guidance and support on course-related topics

Career center

Learners who complete Exploring Data Visually with R will develop knowledge and skills that may be useful to these careers:
Data Analyst
Data Analysts collect, clean, and analyze data to identify trends and patterns. The course, Exploring Data Visually with R, provides valuable skills for Data Analysts, as it teaches how to use data visualization techniques to effectively present data insights. By learning how to create visually appealing and informative visualizations, Data Analysts can make data more accessible and easier to understand for stakeholders.
See salaries and explore the career path for Data Analyst
Business Intelligence Analyst
Business Intelligence Analysts use data to help businesses make better decisions. The course, Exploring Data Visually with R, provides valuable skills for Business Intelligence Analysts, as it teaches how to use data visualization techniques to effectively communicate data insights to stakeholders. By learning how to create visually appealing and informative visualizations, Business Intelligence Analysts can help businesses make better use of their data.
See salaries and explore the career path for Business Intelligence Analyst
Data Scientist
Data Scientists analyze data to extract meaningful insights and patterns, which are used to make informed decisions. The course, Exploring Data Visually with R, provides a solid foundation in data visualization techniques, which are essential for effectively communicating insights to stakeholders. By learning how to create clear and concise visualizations, Data Scientists can enhance the impact of their work and contribute to better decision-making.
See salaries and explore the career path for Data Scientist
Financial Analyst
Financial Analysts use data to make investment decisions. The course, Exploring Data Visually with R, provides valuable skills for Financial Analysts, as it teaches how to use data visualization techniques to effectively analyze financial data. By learning how to create clear and concise visualizations, Financial Analysts can make better investment decisions and communicate their findings more effectively to clients.
See salaries and explore the career path for Financial Analyst
Operations Research Analyst
Operations Research Analysts use data to improve business operations. The course, Exploring Data Visually with R, provides valuable skills for Operations Research Analysts, as it teaches how to use data visualization techniques to effectively analyze operations data. By learning how to create clear and concise visualizations, Operations Research Analysts can make better decisions and communicate their findings more effectively to stakeholders.
See salaries and explore the career path for Operations Research Analyst
Risk Analyst
Risk Analysts use data to identify and assess risks. The course, Exploring Data Visually with R, provides valuable skills for Risk Analysts, as it teaches how to use data visualization techniques to effectively analyze risk data. By learning how to create clear and concise visualizations, Risk Analysts can make better decisions and communicate their findings more effectively to stakeholders.
See salaries and explore the career path for Risk Analyst
Statistician
Statisticians use statistical methods to analyze data and draw conclusions. The course, Exploring Data Visually with R, provides a strong foundation in data visualization techniques, which are essential for effectively communicating statistical findings. By learning how to create clear and concise visualizations, Statisticians can enhance the impact of their work and make their findings more accessible to a wider audience.
See salaries and explore the career path for Statistician
Market Researcher
Market Researchers conduct surveys and analyze data to understand consumer behavior. The course, Exploring Data Visually with R, provides valuable skills for Market Researchers, as it teaches how to use data visualization techniques to effectively present research findings. By learning how to create clear and concise visualizations, Market Researchers can make their findings more accessible and easier to understand for stakeholders.
See salaries and explore the career path for Market Researcher
Data Engineer
Data Engineers build and maintain data infrastructure. The course, Exploring Data Visually with R, may be useful for Data Engineers, as it teaches how to use data visualization techniques to explore and analyze data. By learning how to create clear and concise visualizations, Data Engineers can better understand the data they are working with and make better decisions about how to manage and store it.
See salaries and explore the career path for Data Engineer
Data Architect
Data Architects design and build data systems. The course, Exploring Data Visually with R, may be useful for Data Architects, as it teaches how to use data visualization techniques to explore and analyze data. By learning how to create clear and concise visualizations, Data Architects can better understand the data they are working with and make better decisions about how to design and build data systems.
See salaries and explore the career path for Data Architect
Software Engineer
Software Engineers design, develop, and maintain software applications. The course, Exploring Data Visually with R, may be useful for Software Engineers who work with data, as it teaches how to use data visualization techniques to explore and analyze data. By learning how to create clear and concise visualizations, Software Engineers can better understand the data they are working with and make better decisions about how to design and build software applications.
See salaries and explore the career path for Software Engineer
Web Developer
Web Developers design and develop websites. The course, Exploring Data Visually with R, may be useful for Web Developers who work with data, as it teaches how to use data visualization techniques to explore and analyze data. By learning how to create clear and concise visualizations, Web Developers can better understand the data they are working with and make better decisions about how to design and develop websites.
See salaries and explore the career path for Web Developer
Database Administrator
Database Administrators manage and maintain databases. The course, Exploring Data Visually with R, may be useful for Database Administrators who work with data, as it teaches how to use data visualization techniques to explore and analyze data. By learning how to create clear and concise visualizations, Database Administrators can better understand the data they are working with and make better decisions about how to manage and maintain databases.
See salaries and explore the career path for Database Administrator
Business Analyst
Business Analysts use data to help businesses make better decisions. The course, Exploring Data Visually with R, may be useful for Business Analysts, as it teaches how to use data visualization techniques to explore and analyze data. By learning how to create clear and concise visualizations, Business Analysts can better understand the data they are working with and make better decisions about how to help businesses make better decisions.
See salaries and explore the career path for Business Analyst
Project Manager
Project Managers plan and execute projects. The course, Exploring Data Visually with R, may be useful for Project Managers who work with data, as it teaches how to use data visualization techniques to explore and analyze data. By learning how to create clear and concise visualizations, Project Managers can better understand the data they are working with and make better decisions about how to plan and execute projects.
See salaries and explore the career path for Project Manager

Reading list

We've selected 11 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 Exploring Data Visually with R.
Cover image
FlowingData.com Data Visualization Set
Save
Complements the course by covering the fundamentals of data visualization design. It provides a broad perspective on visual encoding techniques and considerations for effective communication through visualizations.
FlowingData.com Data Visualization Set by Nathan...
Paperback
$$$$
Cover image
Data Visualisation
Save
Serves as a practical guide to data visualization in R. It aligns well with the course's focus on using R for data exploration and visualization, providing detailed explanations and examples.
Data Visualisation: A Handbook for Data Driven...
Paperback
$$
Data Visualisation: A Handbook for Data Driven...
Paperback
$$$
Data Visualisation: A Handbook for Data Driven...
Kindle Edition
$$$
Cover image
R for Data Science
Save
Offers a comprehensive treatment of ggplot2, one of the most popular R packages for data visualization. It provides a deep understanding of ggplot2's grammar of graphics, allowing learners to create advanced and customized visualizations.
R for Data Science: Import, Tidy, Transform,...
Paperback
$$
(Deutsch) R für Data Science: Daten importieren, bereinigen,...
Kindle Edition
$$$
Cover image
Fundamentals of Data Visualization
Save
Delves into the theoretical foundations of data visualization. It provides insights into the cognitive and perceptual aspects of visual perception, helping learners understand how to design visualizations that are both informative and effective.
Fundamentals of Data Visualization: A Primer on...
Kindle Edition
$$$
Cover image
3D Graphics Rendering Cookbook
Save
Valuable reference for R users. It contains a collection of recipes for creating various types of visualizations, providing practical solutions for common visualization tasks encountered during data exploration.
3D Graphics Rendering Cookbook: A comprehensive...
Paperback
$$
3D Graphics Rendering Cookbook: A comprehensive...
Kindle Edition
$$
Cover image
Reflections on Slope Stability Engineering
Save
This classic work on data visualization emphasizes the principles of clear and effective communication through visual representations. It foundational text that provides valuable insights into the history and best practices of data visualization.
Reflections on Slope Stability Engineering
Paperback
$$$
Reflections on Slope Stability Engineering
Kindle Edition
$$$
Cover image
Data Visualisation with R
Save
Comprehensive guide to data visualization in R. It covers a wide range of topics, including data preparation, visualization techniques, and best practices. It useful resource for both beginners and experienced R users.
Data Visualisation with R: 100 Examples
Hardcover
$
Data Visualisation with R: 111 Examples
Hardcover
$$$
Data Visualisation with R: 111 Examples
Kindle Edition
$$
Data Visualisation with R: 100 Examples
Kindle Edition
$$$
Cover image
R for Data Science
Save
Provides a foundational understanding of R programming and data manipulation. It serves as a good preparatory resource for this course, as it covers basic concepts and techniques that are essential for data visualization.
R for Data Science: Import, Tidy, Transform,...
Paperback
$$
(Deutsch) R für Data Science: Daten importieren, bereinigen,...
Kindle Edition
$$$
Cover image
Interactive Data Visualization for the Web
Save
Delves into the world of interactive data visualization for the web. It covers techniques for creating interactive visualizations using HTML, CSS, and JavaScript. It useful resource for anyone interested in building dynamic and engaging data visualizations.
Interactive Data Visualization for the Web: An...
Paperback
$$
Interactive Data Visualization for the Web: An...
Paperback
$$
(中文) 数据可视化实战:使用D3设计交互式图表 (图灵程序设计丛书 23) (Chinese Edition)
Kindle Edition
$
Cover image
Data Visualization with Python and JavaScript
Save
Provides a comparative perspective on data visualization using Python and JavaScript. It covers both the theoretical and practical aspects of visualization, making it a valuable resource for those interested in exploring different technologies for data visualization.
Data Visualization with Python and JavaScript:...
Paperback
$$
Data Visualization with Python and JavaScript:...
Paperback
$$
Data Visualization with Python and JavaScript
Kindle Edition
$$
Cover image
Data Visualization with JavaScript
Save
Emphasizes the importance of choosing the right visualization for the data and the story it tells. It provides practical guidelines and examples to help learners create effective and meaningful visualizations that communicate insights clearly.
Data Visualization with JavaScript
Kindle Edition
$$

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Course image
Time
121 hours
Level
Introductory
Via
Pluralsight
Instructor
Martin Burger
Language
English
This course belongs to a collection called Exploratory Data Analysis with R. It's comprised of two courses:
  1. Exploring Data Visually with R (viewing)
  2. Exploring Your First Data Set with R
Traffic lights
Read about what's good
what should give you pause
and possible dealbreakers
Introduces fundamentals and techniques of data visualization, a critical skill in data exploration
Suitable for learners looking to enhance their data exploration skills using R
Taught by Martin Burger, an industry expert in data analysis and visualization
Covers various visualization techniques using scatterplots, barcharts, histograms, and boxplots
Provides hands-on experience through practical examples and exercises
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