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Data Visualization

1. Do use the full axis

Avoid distortion

  • For bar charts, the numerical axis (often the y axis) must start at zero. 
  • Our eyes are very sensitive to the area of bars, and we draw inaccurate conclusions when those bars are truncated.
  • See the difference between the original media chart and an un-truncated chart as generated by FlowingData. 
  • For line graphs it might be okay to truncate the y axis.

Wide ranges:

  • If you have one or two very tall bars, you might consider using multiple charts to show both the full scale and a "zoomed in" view.
  • This is also known as a Panel Chart. 

For more information:

Consistent intervals:

  • Using the full axis also means that you should not skip values when you have numerical data.  
  • The trend is distorted if you do not have even intervals between your dates.  
  • Make sure your spreadsheet has a data point for every date at a consistent interval, even if that data point is zero. 

2. Do simplify less important information.

  • Chart elements like gridlines, axis labels, colors, etc. can all be simplified to highlight what is most important/relevant/interesting.  
  • You may be able to eliminate gridlines or reserve colors for isolating individual data series and not for differentiating between all of the series being presented 

For more information:

3. Do be creative with your legends and labels.

Some examples include:

  • Label lines individually 
  • Rotate bars if the category names are long 
  • Put value labels on bars to preserve the clean lines of the bar lengths 

For more information:

4. Do pass the squint test.

  • Ask yourself: "When you squint at your page, so that you cannot read any of the text, do you still 'get' something about the page?" 
  • Additional questions to consider 
    • Which elements draw the most attention? What color pops out?
    • Do the elements balance? Is there a clear organization?
    • Do contrast, grouping, and alignment serve the function of the chart?
  • Note: Projectors often wash out figures. The squint test can simulate this. Try high contrast designs with clear trends.

For more information:

5. Do ask others for opinions.

  • Even if you don’t run a full usability test for your charts, have a fresh set of eyes look at what you’ve done and give you feedback. You may be surprised by what is confusing – or enlightening! – to others.

6. Don't use 3D or blow apart effects.

  • Studies show that 3D effects reduce comprehension. 
  • Blow apart effects likewise make it hard to compare elements and judge areas

For more information:

7. Don't use more than (about) six colors.

  • Colour choice is often culturally determined. For example, red is often used to represent loss, so it should not be used to reflect a positive value.
  • Avoid rainbow palettes as they create visual artifacts such as stripes which make it look as though there are dramatic patterns that do not exist.  They also result in loss of detail particularly in the yellow to light green range due to low contrast.
  • Different colors should be used for different categories (e.g., male/female, types of fruit), not different values in a range (e.g., age, temperature). 
  • If you want color to show a numerical value, use a range that goes from white to a highly saturated color in one of the universal color categories. 
  • Use Coblis Color Blind Simulator to test your images for colour blind accessiblity.
  • Print out your charts to test what it looks like in grayscale. (For grayscale to work, you need to vary both hue and saturation.) 

Explore these resources to learn more about colour:

8. Don't change styles midstream.

  • Use the same colors, axes, labels, etc. across multiple charts. 
  • One of the easiest ways to get the most out of charts is to rely on comparison to do the heavy lifting.
  • Our visual system can detect anomalies in patterns. Try keeping the form of a chart consistent across a series so differences from one chart to another will pop out.

9. Don't make users do "visual math."

  • If the chart makes it hard to understand an important relationship between variables, do the extra calculation and visualize that as well.
  • This includes using pie charts with wedges that are too similar to each other, or bubble charts with bubbles that are too similar to each other.  
  • Our visual processing system is not well suited to comparing these types of visual areas. 
  • We are also not good at holding precise visual imagery in our memory and comparing it to new stimuli; if you are giving a presentation and want the audience to be able to compare two charts, they need to be on the same slide. 

10. Don't overload the chart.

  • Adding too much information to a single chart eliminates the advantages of processing data visually; we have to read every element one by one!
  • Try changing chart types, removing or splitting up data points, simplifying colors or positions, etc. 

For more information:

Creative Commons License

This guide has been adapted by the University of Guelph Library. The original guide was created by the Duke University Libraries and is licensed under a Creative Commons Attribution-Share-Alike 3.0 Unported license unless otherwise marked.

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