Dataisbeautiful

We love that submissions come from all over the world and that we get exposed to interesting data and visualizations that we otherwise never would. On top dataisbeautiful the great submissions, we often enjoy reading through the comments because many subreddit members leave great, actionable feedback for the original poster. Read on to find dataisbeautiful visualizations from May that we assess and grade for their quality, dataisbeautiful. Link to Original Reddit Post.

If someone submits a visualization they created themselves, the rules require them to put "[OC]" in the title of the submission, and to identify the source of data and software tool they used to create it. In January , Eleanor Peake noted that, because the subreddit had received so many submissions by Tinder users plotting their experiences on the app, one Reddit user set up a separate subreddit dedicated entirely to Tinder-related data visualizations. Individual posts in the subreddit have also been reported on by the National Post [9] and Vice. Contents move to sidebar hide. Article Talk.

Dataisbeautiful

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Dataisbeautiful did like the dark background and strong colors, as they make the overall visualization eye-catching.

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If someone submits a visualization they created themselves, the rules require them to put "[OC]" in the title of the submission, and to identify the source of data and software tool they used to create it. In January , Eleanor Peake noted that, because the subreddit had received so many submissions by Tinder users plotting their experiences on the app, one Reddit user set up a separate subreddit dedicated entirely to Tinder-related data visualizations. Individual posts in the subreddit have also been reported on by the National Post [9] and Vice. Contents move to sidebar hide. Article Talk. Read Edit View history. Tools Tools. Download as PDF Printable version. Subreddit focused on data visualization.

Dataisbeautiful

Published on March 11, by Dr. Randal S. Unfortunately, it was difficult to parse out mentions of the "R" language with the n-gram analysis, so we'll have to use ggplot2 as a proxy. If programming isn't your forte, Tableau is a much better option than Excel.

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What we love about this visualization is the choice to show four intervals in one graphic. So, at first glance, Detroit sticks out as the biggest decline, but that is only on an absolute number basis, not on a percentage basis. Icebreakers are activities designed to lighten the mood, help individuals know each other, break down barriers. On average, people pull from two to six data sources to assemble a weekly or monthly performance report. Toggle limited content width. Overall, this data visualization is really simple, but it is very well executed. The design is clear, it is relatively easy to understand, and the data is interesting. Further, the choice of a light yellow to show the population clustering creates a really nice contrast that ensures accessibility for any view of this visualization. Individual posts in the subreddit have also been reported on by the National Post [9] and Vice. We also like the use of a relatively unique measure - home price to median annual income. What is well executed about this data visualization is the clear labeling and data source explanations, the strong use of a color scale to represent the number of years, and clear and explanatory legend. February 14, ; 12 years ago [1]. Apparently we have a penchant for spotlighting visualizations that highlight the age distribution in the United States Congress, but I guess we find it interesting! This visualization is a good example of using grouping to communicate data clearly and succinctly to make it easy for the reader to understand. Further, we think that more intentional use of coloring and shading could have helped communicate the information better.

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While there are many cities that are growing like crazy in the US, there are others that are declining significantly. Overall, a great idea for a data visualization and kudos to Reddit User academiaadvice for taking a crack at a difficult graphic! However, this visualization suffers a bit in its attempt to communicate this information clearly. In January , Eleanor Peake noted that, because the subreddit had received so many submissions by Tinder users plotting their experiences on the app, one Reddit user set up a separate subreddit dedicated entirely to Tinder-related data visualizations. If you're working with Airtable visualizations or charts on Google Sheets data, be sure to try Superchart for free. You have joined our waitlist. We also like the use of a relatively unique measure - home price to median annual income. Further, the choice of a light yellow to show the population clustering creates a really nice contrast that ensures accessibility for any view of this visualization. Link to Original Reddit Post. National Post.