![]() It quickly becomes apparent how the disparity in skill and stature between James and his next best teammates only widened over time (as Dwyane Wade and Chris Bosh aged), leading to his eventual departure back to Cleveland. The blue wedges represent his statistical playoff impact, whereas the pink and dark wedges represent the playoff impacts of his second and third best teammates, respectively. #FLORENCE NIGHTINGALE GRAPH HOW TO#Let’s take a look at LeBron’s Miami years from 2011–2013 for an example of how to read this graphic. After all, as I ask in the article, “what is basketball if not a war of attrition?” I turned her exploration of sanitation in army care facilities to something a shade more frivolous: the Diagram of Causes of Mortality for the GOAT in the East, a comparison of LeBron James’ best NBA teammates in the playoffs versus Michael Jordan in his stints with the Chicago Bulls. The Nightingale piece was one of the first ones to catch my eye. Which is why, as a learning exercise, I wanted to recreate historical data visualization but with data sets that interested me. (Oh how far I‘d like to think I’ve come when I showed Elijah Meeks a network diagram I’d rendered just three years ago, his first reaction was, “Gosh, that’s ugly.”) Borrowing inspiration from pioneers in the field has been key to spurring that growth. Learning how to effectively weave creative data visualizations into the cases that I present and being able to borrow from inspiration across diverse fields (the wonders of cross-pollination learning!) has been critical to my growth as an analyst and story-teller. I do data analytics for a bank as a day job, and when I get home in the evening, I do data analytics for basketball. The exercise of discovering, internalizing, then reverse-engineering those same principles that the original authors meticulously considered (this isn’t a Jackson Pollack splatter-paint job every detail is carefully planned out here) is an exercise that fundamentally improves one’s capacity for creating effective data visualization. Dubois, especially when that work goes against (at least on a surface level) a staid and uninspiring grain. There’s a lot to be learned from deconstructing historical works from pioneers such as Nightingale or W.E.B. And over the past year or so, I’ve been tracking down cool, funky, or otherwise interesting works of data visualization. Radial form factors are then optimized if the visualization naturally encodes traditionally radial or cyclical concepts (like launch angles in baseball, directionality of weather patterns, or time/seasons like with Nightingale’s original diagram).įor how it combines impact with enduring popularity, Florence Nightingale’s Diagram of the Causes of Mortality is an objectively cool piece of data visualization (in my absolutely subjective opinion). Metcalf’s NFL Draft Combine performance). Pac-man shape of former Ole Miss receiver D.K. It’s why radar or spider plots are as popular as they are (nobody is going to forget the Going one step further, our brain loves to provide geometric definitions to data. For starters, the polar stacked bar or coxcomb-style graph allows you to exaggerate the disparity between categories due to how the bars fan outwards. It brings into sharp relief one of the central tensions of data visualization to balance the precision and accuracy of information extraction with the challenge of how to engage, impact, and retain information for the end consumer. Radar plot of D.K.Metcalf’s NFL Draft Combine’s results Her rose diagram is an effective use of a radial graph. But mainly, data viz would be more boring that’s what’s important here, for this article at least. And also, probably more soldiers would have continued to die for a bit longer from preventable causes. But, my goodness, what a boring world we’d live in today if she had. It would have been the most precise way of capturing the data she spent so much time recording. Nightingale could have just taken a cue from her predecessors in the data visualization realm and drawn a bunch of bar charts (maybe throw in a line graph if she wanted to get edgy). It’s another thing entirely to effectively and actionably juxtapose it against the casualties encountered at the hands of the opposing army. ![]() It’s one thing to simply state that the disease killed a lot of soldiers. ![]() Her Diagram of the Causes of Mortality had a singular goal: to vividly demonstrate that the lack of proper sanitary caretaking facilities was a far more severe, but also far more avoidable, cause of death for soldiers than injuries suffered in battle. In 1858, Florence Nightingale published a study on the conditions of army hospitals, her seminal Notes on Matters Affecting the Health, Efficiency, and Hospital Administration of the British Army. ![]()
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