{"id":62874,"date":"2012-06-07T00:00:00","date_gmt":"2012-06-07T00:00:00","guid":{"rendered":"https:\/\/rockcontent.com\/blog\/context-in-data-visualization\/"},"modified":"2025-09-15T15:30:09","modified_gmt":"2025-09-15T18:30:09","slug":"context-in-data-visualization","status":"publish","type":"post","link":"https:\/\/pingback.com\/en\/resources\/context-in-data-visualization\/","title":{"rendered":"The Importance of Being Earnest, or Showing Context in Data Visualization"},"content":{"rendered":"

The thing about telling stories through data is, sometimes you don’t know what the story is until you’ve visualized the data. And if the story isn’t what you expected, you may have to either: A.<\/strong> tell the “new” story as it is, or B.<\/strong> find another set of data and another story to tell. Unfortunately, sometimes the commissioner of the visualization may ask you to go with option C.<\/strong> tweak the visualization, or even the data, so it shows the story they want<\/em> to tell. In the past, the team at Visual.ly<\/a> has been asked to crop axes in order to exaggerate trends in a chart. The argument is that “as long as the axis is labeled correctly, it is okay”. It would be nice if this were true, but it is not. If we are to truly do visualization<\/strong>, then all of the information related to the chart should be visual. Properly labeled axes are always important, but they should never be part of the primary method of interpreting the data from a visualization. Often times, within a chart there are relationships that are shown between the blank spaces. The visual mark itself is not the only place that information is shown. One example of this is in a line chart showing percentages. (Data<\/a>) \"\"<\/a> \u00a0 Cropping the vertical axis on this chart could help to make the changes over time more apparent. \"\"<\/a> \u00a0 The problem with this is that the line itself is not the only part that shows data. You can see the pink section shows the percentage of the American population not in the labor force, while the blue section shows the percentage that is in the labor force. \"\"<\/a> \u00a0 When we look at the chart this way, we can see that it is more than just the line itself that matters.<\/p>\n

Sometimes, even small tweaks done with innocent intentions can end up telling a totally different story. I\u2019ve seen visualizations in presentations that left out just a tiny sliver of context\u2014to \u201cdeclutter\u201d things\u2014and suddenly the takeaway becomes much more dramatic. It happens faster than you\u2019d expect. In these moments, the absence is almost as persuasive as the data shown, quietly shifting a viewer\u2019s perception without anyone explicitly trying to mislead. That\u2019s why, for anyone playing with data, it really pays to pause and look at the whole image, not just the obvious bits.<\/p>\n

There is a part to whole relationship shown in the vertical, and cropping the y-axis would destroy that relationship. There is hidden context in many visualizations, and this context helps give an accurate depiction of the data, even if the viewer is unaware that the context exists. Percentage line charts are not the only charts where context is important. For example, in quantitative charts, showing an axis that starts at zero is important, so that the real quantity can be visualized. When multiple charts with the same units are used together, they should all have the same minimums and maximums so that each chart can be compared to the other.<\/p>\n

Honestly, this kind of thing comes up a lot when people try to condense complex reports onto a single slide for a meeting. Nobody (well, almost nobody) throws in a chart thinking \u201clet\u2019s mess with the axis and dupe our audience,\u201d but that\u2019s what happens. Once you realize how easily interpretation can sway, it gets hard not to scrutinize every graph you see. If a visualization makes you pause\u2014like, \u201cWait, is that really such a huge jump?\u201d\u2014that\u2019s a sign to look for what might be missing or manipulated. Asking questions is the only way to keep things grounded in reality, even if the chart looks polished at first glance.<\/p>\n

This higher level coordination within and between charts is good practice because it gives people a more clear understanding of the data, and it does not attempt to distort the data to exaggerate an existing pattern. That said, there are some cases where axis cropping is necessary. Sometimes the change in data is imperceptible despite being a significant increase or decrease. In cases like this, two charts should be shown, one with full context, another cropped, with an annotation in the full context chart that shows the region that the new chart has been cropped to. \"\"<\/a> \u00a0 In any case, make sure the visualization shows as much context as is reasonably possible. It is in the best interest of everyone involved that the data is shown clearly and accurately. Being dishonest with data is not only wrong, but getting caught in the act is not a happy situation for commissioner or visualizer. \u00a0 Drew Skau<\/a> is Visualization Architect at Visual.ly<\/a>, and a context-aware PhD Computer Science Visualization student at UNCC<\/a>, with an undergraduate degree in Architecture.<\/em><\/p>\n

}}<\/p>\n","protected":false},"excerpt":{"rendered":"

The thing about telling stories through data is, sometimes you don’t know what the story is until you’ve visualized the data. And if the story isn’t what you expected, you may have to either: A. tell the “new” story as it is, or B. find another set of data and another story to tell. Unfortunately, […]<\/p>\n","protected":false},"author":1,"featured_media":53040,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[26],"tags":[],"class_list":["post-62874","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized"],"yoast_head":"\nThe Importance of Being Earnest, or Showing Context in Data Visualization - Pingback<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/pingback.com\/en\/resources\/context-in-data-visualization\/\" \/>\n<meta property=\"og:locale\" content=\"pt_BR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"The Importance of Being Earnest, or Showing Context in Data Visualization - Pingback\" \/>\n<meta property=\"og:description\" content=\"The thing about telling stories through data is, sometimes you don’t know what the story is until you’ve visualized the data. 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