Customizing Visualizations
We're still working on our article for Customizing Visualizations. Please check back soon for more information.
9bcx8n|
Find a path to becoming a Customizing Visualizations. Learn more at:
OpenCourser.com/topic/9bcx8n/customizing
Reading list
We've selected 16 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
Customizing Visualizations.
This classic book must-read for anyone interested in data visualization. It provides a deep dive into the principles of visual perception and how they can be applied to create effective visualizations. While it does not specifically cover customizing visualizations, it provides a strong foundation for understanding the underlying theory.
Provides a comprehensive overview of information visualization. It covers topics such as the perception of visualization, the design of visualizations, and the evaluation of visualizations.
Classic work on data visualization. It provides a comprehensive overview of the grammar of graphics, which set of principles for creating effective visualizations.
Provides a collection of essays on visual complexity. It covers topics such as the different types of visual complexity, how to measure visual complexity, and how to use visual complexity to communicate your findings.
Provides a comprehensive overview of data visualization with Tableau. It covers topics such as data preparation, creating visualizations, and customizing visualizations.
Provides a comprehensive overview of data visualization with Python and JavaScript. It covers topics such as data preparation, creating visualizations, and customizing visualizations.
Provides a comprehensive overview of dashboards. It covers topics such as the different types of dashboards, how to design effective dashboards, and how to use dashboards to communicate your findings.
Provides a comprehensive overview of the theory and practice of interactive data visualization for the web. It covers topics such as data visualization principles, web technologies for data visualization, and best practices for creating effective interactive visualizations.
Provides a comprehensive overview of data visualization with D3.js. It covers topics such as data preparation, creating visualizations, and customizing visualizations.
Practical guide to using ggplot2, a popular R package for data visualization. It provides comprehensive coverage of customizing visualizations using ggplot2, making it an excellent resource for those who want to master this tool.
Provides a solid foundation in data visualization principles and techniques. It covers a wide range of topics, including customizing visualizations, and is suitable for both beginners and experienced practitioners.
Provides a practical guide to creating data-driven stories using R. It covers a range of techniques for visualizing and communicating data, including customizing visualizations to make them more engaging and impactful.
Provides a practical guide to choosing the right visualization for your data. It covers topics such as the different types of visualizations, when to use each type of visualization, and how to create effective visualizations.
Provides a practical guide to data visualization. It covers topics such as choosing the right visualization for your data, creating effective visualizations, and using data visualization to communicate your findings.
Provides a collection of recipes for creating visualizations in R. It covers topics such as creating basic visualizations, customizing visualizations, and creating interactive visualizations.
Provides a practical guide to creating visualizations using R. It covers a range of topics, including customizing visualizations, and is suitable for those who want to use this tool to create data-driven dashboards and reports.
For more information about how these books relate to this course, visit:
OpenCourser.com/topic/9bcx8n/customizing
Save
