If you piled up all of America’s surplus cheese, this is how large it would be.
Data visualization is a graphic representation of statistics. It involves creating images that communicate relationships between data to the user. To communicate information clearly and efficiently, data visualization uses statistical tables, graphs, and information graphics. Numerical data may be represented by using dots, lines, bars, or images (usually illustrations, but not always) to visually communicate an important message.
Data visualization is indeed both an art and a science; and it has been especially useful during the pandemic to help people understand the scale of the virus and its effects around the country and the world.
The Johns Hopkins COVID-19 Dashboard aggregates data from sources such as the World Health Organization, U.S. Centers for Disease Control and Prevention, the European Center for Disease Prevention and Control, and several others. Data visualizations can help make sense of complex and overwhelming data. When dealing with quantitative data that is so large, data visualization helps people to feel like they can understand what is going on.
Johns Hopkins University COVID-19 Map
Well designed data visualizations will allow the user to:
Comprehend information quickly - By using data visualizations, users are able to see large amounts of data in clear, cohesive ways–and draw conclusions from them.
Identify relationships and patterns - Even extensive amounts of complicated data start to make sense when visualized by identifying relationships and patterns within the data.
Communicate with others - The "user-friendliness" of data visualizations allow statisticians and other experts to share their research and findings with a wider range of users.
How The Economist designs charts for Instagram. Left: the original chart; right: the Instagram version with simplified categories.
According to the American statistician, Edward Tufte, effective data visualizations:
Not applying these principles may result in misleading graphs, which can distort the message or support a false conclusion.
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