Data Visualization

Guide for technologies, techniques, and best practices for data visualization.

Data Visualization Best Practices

1. Know your audience.
2. Know you message.
3. Adapt your visualization scale to the presentation medium.
4. Avoid chartjunk (Keep it simple).
5. Use color effectively.
6. Avoid the default settings.

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Peter Lawson
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Choosing an Appropriate Visual Encoding

Data visualization relies on communication through perception. A good data visualization can exploit the natural tendency of the human visual system to recognize structure and patterns.

The brain can process information faster and more efficiently when it is in a visual format.

Key to achieving this is the choice of visual encodings for your data that correspond to preattentive attributes. Preattentive attributes are visual attributes, including size, color, shape, and position that are processed at a high speed by the visual system.

Consider the images below, what stands out to you in each image? Was the red dot in the color hue figure immediately apparent? That is preattentive processing at work.

Visual Attributes

Image Source: https://help.tableau.com/current/blueprint/en-us/bp_why_visual_analytics.html

Precision of Quantitative Information Attribute Example Natural Interpretation
Highly Precise                          
Length                       
               
Longer = Greater
Position
Higher = Greater
Imprecise
Width
Wider = Greater
Size
Larger = Greater
Intensity
Darker = Greater
 
 

Images adapted from: https://help.tableau.com/current/blueprint/en-us/bp_why_visual_analytics.html
Table adapted from: Few, S. (2009). Now you see it: Simple visualization techniques for quantitative analysis (p. 41). Oakland, CA: Analytics Press.

Color in Data Visualizations

Choosing a Color Palette

Your selection of a color palette in your data visualization will depend on properties of your data. The three primary types of color palettes include:
Type of Color Palette
Description of Use
Example
Qualitative Palette
Categorical data that does not have an inherent ordering.
Sequential Palette
Data that is numeric, or has a natural ordering.
Diverging Palette
Numeric data that diverges from a center value.

Image Source: https://medium.com/nightingale/how-to-choose-the-colors-for-your-data-visualizations-50b2557fa335

Color in Data Visualization Resources

Data Visualization Design Resources