{"id":11850,"date":"2020-12-18T20:29:01","date_gmt":"2020-12-18T20:29:01","guid":{"rendered":"https:\/\/www.anychart.com\/blog\/?p=11850"},"modified":"2020-12-18T20:49:15","modified_gmt":"2020-12-18T20:49:15","slug":"visual-graphics-make-data-talk","status":"publish","type":"post","link":"https:\/\/www.anychart.com\/blog\/2020\/12\/18\/visual-graphics-make-data-talk\/","title":{"rendered":"New Graphics That Make Data Talk \u2014 DataViz Weekly"},"content":{"rendered":"<p><img decoding=\"async\" class=\"alignnone size-full wp-image-11852\" src=\"https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2020\/12\/Data-Visualization-Weekly-December-11-18-2020-Blog.png\" alt=\"New Graphics That Make Data Talk - DataViz Weekly\" width=\"100%\" srcset=\"https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2020\/12\/Data-Visualization-Weekly-December-11-18-2020-Blog.png 1100w, https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2020\/12\/Data-Visualization-Weekly-December-11-18-2020-Blog-300x169.png 300w, https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2020\/12\/Data-Visualization-Weekly-December-11-18-2020-Blog-768x431.png 768w, https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2020\/12\/Data-Visualization-Weekly-December-11-18-2020-Blog-1024x575.png 1024w\" sizes=\"(max-width: 1100px) 100vw, 1100px\" \/>Get ready for another dose of amazing charts and maps! <a href=\"https:\/\/www.anychart.com\/blog\/category\/data-visualization-weekly\/\">DataViz Weekly<\/a>&#8216;s here to show you a set of new projects featuring graphics that make data talk \u2014 excellent examples of data visualization in action!<\/p>\n<p>Here are this week&#8217;s picks:<\/p>\n<ul>\n<li>Over 200 years of migrations in the American South \u2014 Edward Ayers, Nathaniel Ayers &amp; Justin Madron<\/li>\n<li>NBA fouls and violations, by referee \u2014 Owen Phillips<\/li>\n<li>U.S. unemployment change, by occupation \u2014 Nathan Yau<\/li>\n<li>U.S. hospital COVID-19 bed occupancy \u2014 Carlson School of Management at UMN<\/li>\n<\/ul>\n<p><!--more--><\/p>\n<h2>Data Visualization Weekly: December 11, 2020 \u2014 December 18, 2020<\/h2>\n<h3>200+ Years of Migrations in American South<\/h3>\n<p><a href=\"https:\/\/dsl.richmond.edu\/southernjourney\/\" target=\"_blank\" rel=\"nofollow\"><img decoding=\"async\" class=\"alignnone size-full wp-image-11856\" src=\"https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2020\/12\/southern-history-migration-map.png\" alt=\"Over 200 Years of Migrations in American South\" width=\"100%\" srcset=\"https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2020\/12\/southern-history-migration-map.png 943w, https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2020\/12\/southern-history-migration-map-300x199.png 300w, https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2020\/12\/southern-history-migration-map-768x508.png 768w\" sizes=\"(max-width: 943px) 100vw, 943px\" \/><\/a><br \/>\nFor inspiring maps, and especially if you like all things history, don&#8217;t miss a new <a href=\"https:\/\/lsupress.org\/books\/detail\/southern-journey\/\" target=\"_blank\" rel=\"nofollow\">book<\/a> by Edward L. Ayers, <em>Southern Journey<\/em>. Published with Louisiana State University Press, it offers a look at the history of the American South from 1790 to the present day through the lens of migration.<\/p>\n<p>To explain movement and settling patterns within the American South in the most insightful way, Ayers makes use of numerous color map visualizations created by Justin Madron and Nathaniel Ayers. Good news: You can view and explore them online, in a special storytelling <a href=\"https:\/\/dsl.richmond.edu\/southernjourney\/\" target=\"_blank\" rel=\"nofollow\">project<\/a> on the website of the Digital Scholarship Web at the University of Richmond.<\/p>\n<p>Check out the migrations of the American South mapped, across over 200 years.<\/p>\n<h3>NBA Foul Calls By Referee<\/h3>\n<p><a href=\"https:\/\/llewellynjean.shinyapps.io\/NBARefDatabase\/\" target=\"_blank\" rel=\"nofollow\"><img decoding=\"async\" class=\"alignnone size-full wp-image-11855\" src=\"https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2020\/12\/nba-referee-foul-called-stats-charts.png\" alt=\"NBA Foul Calls By Referee\" width=\"100%\" srcset=\"https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2020\/12\/nba-referee-foul-called-stats-charts.png 900w, https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2020\/12\/nba-referee-foul-called-stats-charts-300x233.png 300w, https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2020\/12\/nba-referee-foul-called-stats-charts-768x597.png 768w\" sizes=\"(max-width: 900px) 100vw, 900px\" \/><\/a><br \/>\nOwen Phillips, a data analyst known in particular for editorial contributions to FiveThirtyEight, compiled a database of all foul calls for each NBA referee since 2016 based on the NBA play-by-play datasets. Named &#8220;The Unofficial NBA Ref Ball Database,&#8221; it covers regular season and playoff games over four seasons, from 2016-2017 to 2019-2020, and is available in online data tables and in a CSV file.<\/p>\n<p>Right there, on the project&#8217;s <a href=\"https:\/\/llewellynjean.shinyapps.io\/NBARefDatabase\/\" target=\"_blank\" rel=\"nofollow\">website<\/a>, you can not only dive into raw data but also explore part of it in a lovely data visualization tool. Pick an NBA referee and a season from the corresponding dropdown lists. You will see a cool chart providing insights into how that person compares to the other referees \u2014 and to a league average \u2014 in terms of the number of foul and violation calls per game. (Note that the charts show data only for regular season games and playoffs are not taken into account.)<\/p>\n<p>Take a look and see what data can reveal about the referees&#8217; performance.<\/p>\n<h3>U.S. Unemployment Change By Occupation<\/h3>\n<p><a href=\"https:\/\/flowingdata.com\/2020\/12\/14\/unemployment-and-occupation\/\" target=\"_blank\" rel=\"nofollow\"><img decoding=\"async\" class=\"alignnone size-full wp-image-11854\" src=\"https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2020\/12\/unemployment-by-occupation-charts.png\" alt=\"U.S. Unemployment Change By Occupation\" width=\"100%\" srcset=\"https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2020\/12\/unemployment-by-occupation-charts.png 960w, https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2020\/12\/unemployment-by-occupation-charts-300x249.png 300w, https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2020\/12\/unemployment-by-occupation-charts-768x638.png 768w\" sizes=\"(max-width: 960px) 100vw, 960px\" \/><\/a><br \/>\nThe pandemic along with measures to combat it led to a surge in unemployment rates this year in the United States. However, the scale of job loss is not the same across all industries. Nathan Yau, a data scientist, decided to zoom on the impact with the help of data from the U.S. Bureau of Labor Statistics (BLS).<\/p>\n<p>So, he <a href=\"https:\/\/flowingdata.com\/2020\/12\/14\/unemployment-and-occupation\/\" target=\"_blank\" rel=\"nofollow\">plotted<\/a> the unemployment rates for November 2020 and November 2019 in a beeswarm chart, displaying the share of people without a job, by occupation: food preparation and serving, healthcare, production, sales, legal, personal care and service, transportation and material moving, arts and entertainment, building and grounds cleaning, and more.<\/p>\n<p>You can see the switch between the two years is nicely animated, making it easy to follow the changes by occupation and quickly notice the most striking differences. Feel free to compare.<\/p>\n<h3>U.S. Hospital COVID-19 Bed Occupancy<\/h3>\n<p><a href=\"https:\/\/carlsonschool.umn.edu\/mili-misrc-covid19-tracking-project\" target=\"_blank\" rel=\"nofollow\"><img decoding=\"async\" class=\"alignnone size-full wp-image-11853\" src=\"https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2020\/12\/covid-hospitalization-tracking-map-data-viz.png\" alt=\"U.S. Hospital COVID-19 Bed Occupancy\" width=\"100%\" srcset=\"https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2020\/12\/covid-hospitalization-tracking-map-data-viz.png 1080w, https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2020\/12\/covid-hospitalization-tracking-map-data-viz-300x192.png 300w, https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2020\/12\/covid-hospitalization-tracking-map-data-viz-768x491.png 768w, https:\/\/www.anychart.com\/blog\/wp-content\/uploads\/2020\/12\/covid-hospitalization-tracking-map-data-viz-1024x655.png 1024w\" sizes=\"(max-width: 1080px) 100vw, 1080px\" \/><\/a><\/p>\n<p>The U.S. Department of Health and Human Services started publishing detailed data on hospital COVID-19 capacity, displaying how full every facility is in terms of the number of beds for patients with the coronavirus. Previously, only aggregated data was available, by state.<\/p>\n<p>The new, per-hospital data, promised to be\u00a0updated by the HHS on a weekly basis, allowed the Carlson School of Management at the University of Minnesota to launch a new interactive map that they called &#8220;the first-ever visualization tool showing sub-state COVID-19 hospitalizations across the country.&#8221; The map makes it easy to explore the share of occupied regular and I.C.U. COVID-19 beds at the county level.<\/p>\n<p>The new data visualization is now part of the <a href=\"https:\/\/carlsonschool.umn.edu\/mili-misrc-covid19-tracking-project\" target=\"_blank\" rel=\"nofollow\">UMN Hospitalization Tracking Project<\/a> launched on March 26th. There is also a dashboard representing COVID-19 hospitalizations by state according to data from state websites.<\/p>\n<p>In case\u00a0you are also interested to view the HHS data on a per-facility basis, The New York Times made a <a href=\"https:\/\/www.nytimes.com\/interactive\/2020\/us\/covid-hospitals-near-you.html\" target=\"_blank\" rel=\"nofollow\">map<\/a> that can tell you about the I.C.U. occupancy in hospitals near you.<\/p>\n<p>***<\/p>\n<p>Thank you for your attention. Stay tuned for great visualizations.<\/p>\n<!-- AddThis Advanced Settings generic via filter on the_content --><!-- AddThis Share Buttons generic via filter on the_content -->","protected":false},"excerpt":{"rendered":"<p>Get ready for another dose of amazing charts and maps! DataViz Weekly&#8216;s here to show you a set of new projects featuring graphics that make data talk \u2014 excellent examples of data visualization in action! Here are this week&#8217;s picks: Over 200 years of migrations in the American South \u2014 Edward Ayers, Nathaniel Ayers &amp; [&hellip;]<!-- AddThis Advanced Settings generic via filter on get_the_excerpt --><!-- AddThis Share Buttons generic via filter on get_the_excerpt --><\/p>\n","protected":false},"author":9,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[175],"tags":[260,284,258,1766,1771,1772,1800,1769,49,471,266,620,54,256,130,145,383,144,237,543,131,459,326,309],"class_list":["post-11850","post","type-post","status-publish","format-standard","hentry","category-data-visualization-weekly","tag-best-data-visualization-examples","tag-chart-examples","tag-charts","tag-coronavirus","tag-coronavirus-data","tag-coronavirus-data-visualization","tag-coronavirus-pandemic","tag-covid-19","tag-dashboards","tag-data-analysis","tag-data-analytics","tag-data-analytics-examples","tag-data-visualization","tag-data-visualization-examples","tag-data-visualization-weekly","tag-dataviz-weekly","tag-flowingdata","tag-infographics","tag-maps","tag-new-york-times","tag-recap-of-the-week","tag-statistics","tag-the-new-york-times","tag-united-states","wpautop"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.1.1 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>New Visual Graphics That Make Data Talk | DataViz Weekly<\/title>\n<meta name=\"description\" content=\"Get ready for another dose of amazing charts and maps! 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