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Visualizing information through methods such as charts, graphs, and maps, can play a key role in helping an audience understand complex sets of data. When used correctly, these visual tools should augment existing information in order to make the subject at hand clearer by providing additional layers of understanding that the reader or viewer would not get simply by reading text. Some of my favorite data visualizations come from the graphics department at The New York Times. (Some of their recent examples can be found here and here).
Often times, however, visual information can become cluttered and disorienting—offering no meaningful insight into the data, or just flat out telling the wrong story. There is probably no greater example of this than in United States election maps. I’m sure that we can all agree that coloring an entire state, district, or county a stark red or blue based off of a 51/49% split is not an incredibly accurate representation of the voters as a whole in that specific area. If you want more information on this specific problem, you can read this great article.
There are plenty of these confusing and misleading infographics around, even ones that have been published by major, (supposedly) reputable organizations. I’ve compiled a list of some of my favorite, poorly-constructed data visualizations below, and offered a quick explanation for where exactly they went wrong.