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Data Visualization

Use this guide to learn basics of data visualization.

Evaluating data visualization

We can easily visualize a small dataset, and data scientists can visualize more complex data using more sophisticated tools. Does it describe what the data shows? We need to determine if the visualization actually tells the true story of the data. To do this, ask yourself these questions:


  • Do numbers seem too big or too conveniently rounded? 
  • Are the units of measure consistent, or are different units used to describe a single phenomenon? 
  • Is the data cherry-picked? Are date ranges or time boundaries specifically chosen because they demonstrate a desired result? 


  • Is this the best way to visualize this data? 
  • Ask questions of text and labels. Does the title convey a thesis or put forth an argument? Can you spot emotionally-laden words or is the language neutral and purely descriptive? Read the fine print for important details that the creator may have tried to de-emphasize. 
  • What does the color choice tell us? How do the colors used make you feel? Red usually signals trouble, or at least emphasis. Are the colors communicating emotion that is supported by the data? Or distracts from or over-emphasizes it? 
  • Is the graphic layout designed to emphasize or deemphasize some of the data?