- Why Visualize?
Through data visualizations such as graphs, maps, etc. We can identify important patterns which allows us to better understand our data to perform further analysis. At the same time, a good data visualization will also allow us to easily communicate information about our data.
- Understanding Visualization
Sometimes you may encounter a visualization that you do not understand. You might just not be familiar with that type of visualization, often because different disciplines have their "go-to" types of visualizations that work well with their data.
Or perhaps you haven't dealt with charts and graphs a lot before. You may need to work on developing your data visualization literacy here or here.
Check out these links to help you make sense of what you find:
Understanding Visualizations by IBM
- Quick general overview of common visualizations
The Data Visualization Catalogue
- Explains many visualizations with breakdowns that clearly show you how to read them
- Explains how to understand and use some less familiar visualization types
- Tips for finding the key information to look for in a visualization. Check out this whole section on data visualization literacy for more tips on understanding visualizations
- Explains how to create a good data visualization and examines the effective of different types of data visualization
- Explains how to understand network graphs
- Bar charts/graphs come up often, learning about some alternative formats, not as commonly mentioned, might be a useful addition to your data visualization toolkit
- Dual axes graphs can be problematic. Read this article to make sense of the problems and alternatives to a dual axes graph
- Best Practices of Visualization
- Don’t manipulate your visualization to better fit your argument.
- Choose a data visualization that fits the data and your purpose
- Don’t overcrowd a data visualization
- Choose a data visualization that doesn’t hinder understanding
- Galleries and Examples