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Using Charts Effectively

This guide is a general overview of creating and using charts including best practices in chart design.

Chart Checklist

Ten Design Standards for Charts and Graphs

While creating your chart, you will want to keep the following design standards in mind.

Design Standard Checklist

  1. Chart format: Select the appropriate chart format for your data and audience. Decide whether the chart will be printed, projected, or used on the web.
  1. Color: Use color sparingly. Use it to highlight a data point as a pre-attentive attribute. Consider using grayscale shading rather than color. Avoid thematic or decorative presentations. Consider the cultural meanings of the colors you select and the impact that may have on your audience. Ensure high contrast values. Test contrast by converting colors to grayscale.
  1. Text and labels: Use descriptive text and labels. For small series bar and line charts, remove the y-axis and place value labels directly on the data encodings. Use a legend when the chart encodings are too small to label and/or if they would impede readability. Add a description to guide readers in interpreting your visualization
  1. Readability: Font face, size, direction, and color affect the legibility. Do not set text at an angle or vertically.
  1. Scales: Keep the maximum value of the y-axis equal to or just above the highest value in the data set. Ensure a zero-point y-axis for vertical bar charts. Use natural increments for scales.
  1. Data integrity: Show your data accurately and avoid distortions. Avoid fake perspectives, such as 3D. Keep the lie factor equal to 1. Ensure that the size of the effect shown in graphic equals the size of the effect of the data.
  1. Chartjunk (Tufte, 2001): Remove the grid (or use a light gray grid) and non-essential elements. Avoid using shadows. Stick to white or match the chart background. Emphasize the data and reduce the non-data graphic elements.
  1. Data density: Consider how much information is shown in a graphic. Avoid small multiples to show comparisons of multivariate data.
  1. Data richness: Use accurate data and effective filtering of your data.
  1. Attribution: Provide a citation. Include year for data used and add a chart author.

 (Source: Data visualization made simple: insights into becoming visual, by Kristen Sosulski. New York: Routledge, 2019)

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