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Data Visualization

A guide to data visualization principles and techniques.

Data Visualization

Data visualization should be a constant consideration throughout the course of a research project. Exploring your data through visuals can help you spot patterns that might not be obvious by looking at statistics alone. Take a look at this example – even if the summary stats seem similar, the actual data can be very different!

Also, remember that data visualization isn't just about understanding your data; it's often the end result of your research. So, it's a good idea to put some time and thought into your charts, graphs, and figures right from the start. Take a look at the best practices tab to consider the goal of your data visualization before you get started.

Different fields might use different software and data types, but the basic principles of good data visualization are the same. This guide can give you some tips and tools to help you create effective data visuals.

An image of the data visualization process: get to know your data, determine your goal, is visualization needed, cleaning the data, visualizing data

This image depicts a flow diagram of the data visualization process. Created using Canva.

Library Resources

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This LibGuide was adapted from the Data Visualization LibGuide at UCSD.

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