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Data Presentation

This guide provides information about various data visualizations types, design principles, as well as data presentation tools.

Design Considerations

Color may be used to enhance the beauty as well as convey and/or clarify meaning in your visualization. However, color may also confuse and mislead. Consider your audience. How will they access your visualization (online, in print, on a projector screen)? Are colors in your pallet difficult to distinguish for those with visual impairments? Are there potential cultural connotations to take into account?

It is important to consider all of these aspects when choosing a color pallet for your visualization. 

Color Selection Advice:

Color Selection Tools:

Potential pitfalls of improper/misleading color usage:

The baseline and scale of your charts are important factors to consider in order to accurately represent your data. With the possible exception in analysis of economic and finance data, most charts should have a natural baseline of zero. However, using a baseline that is logical, meaningful, and that does not misrepresent the data.

Here are a few examples of how non-zero baselines have been used to alter the perception of data:


This first chart is from a Fox News broadcast.

The first chart was provided from a 2012 Forbes article.

This second chart uses the same data, with a baseline of zero. Notice that the difference in tax rates appears much less drastic. 

The second, corrected chart is from


This is another example from a 2017 Vox story

It is not enough to choose an appropriate visualization type, color scheme, and scale. It is also important to consider how you will organize your data within a visualization.

Do you have wide ranges? Perhaps using multiple charts will better illustrate the variations in different scales.

Do you have a large quantity of data? If so, you may try changing chart types, splitting up data points, or simplifying colors so that your chart doesn't become too overwhelming.

Are you comparing multiple sets of variables? It may be helpful to try several chart types to make sure your data is easy to read while conveying the information you desire. Don't be afraid to break visualization conventions for chart types if your data is better visualized using a non-standard method.