New Cool Graphics From Around the Web — DataViz Weekly July 10th, 2020 by AnyChart Team
It’s Friday and we’re glad to share with you some of the most interesting third-party visualizations we’ve recently come across. Here’s what DataViz Weekly has for you to check out this time — look at these cool graphics:
- Future of jobs in the regions of Europe — McKinsey Global Institute, Google, et al.
- Flood risk factor database for the United States — First Street Foundation, et al.
- Changes in new cases against testing — Axios
- All we know about SARS-CoV-2 — Scientific American
Information Visualization Techniques in Action on Democracy, Covid-19, Inequality & Gerrymandering — DataViz Weekly June 26th, 2020 by AnyChart Team
DataViz Weekly is here exhibiting new interesting projects from around the web that demonstrate a great use of different information visualization techniques to deliver better insight. See our new picks:
- Democracy Perception Index 2020 — Dalia
- Government reactions to the Covid-19 pandemic — Bloomberg News
- Gaps between Black and White America — The New York Times Opinion
- Antimander, a tool to expose gerrymandering in congressional districts — Joel Simon
Visualizing COVID-19 Pandemic Data for Austria Using AnyChart JS Charts June 25th, 2020 by AnyChart Team
The COVID-19 pandemic persists as a global emergency, and we continue to support initiatives that contribute to tackling the coronavirus crisis. Specifically, we allow COVID-19 analytics projects to use our data visualization tools for free under a non-profit license.
We asked Juergen a few questions to learn more about this project and his experience visualizing COVID-19 pandemic data with the help of AnyChart. Read the answers and take a glance at several quick chart examples from his website. (Stack: HTML/CSV.)
New Data Graphics to Check Out This Weekend — DataViz Weekly June 12th, 2020 by AnyChart Team
Hey everyone! Here’s DataViz Weekly with a quick presentation of four new data graphics projects that we’ve found worth checking out. Look at these stunning examples of charts and maps in action!
- Areas with the humanity’s lowest impact on the natural world — National Geographic
- COVID-19 in Austria (and worldwide) — Jürgen Höfer
- Age of buildings in Saint Petersburg (Russia) — Nikita Slavin
- Chronic health conditions by income and race — NYT
To demonstrate this way, which is quite simple to master even if you only have basic HTML coding skills, I am going to visualize official data about the outbreak of the COVID-19 pandemic in Italy. The visualizations built along the tutorial will display how the numbers of cases, recoveries, and deaths have been changing — from January 31, when the first two cases were confirmed, to yesterday, June 9, when the total number of coronavirus cases in Italy reached 235,561.
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Visual Presentations of Data About Jobs, Simpsons, NYC and Journals — DataViz Weekly June 5th, 2020 by AnyChart Team
Every week, we meet a number of new visual presentations of data around the web. Then, on Friday, we pick the four most interesting of them to tell you about. The following projects made it to DataViz Weekly this time:
- Job losses in the United States, the second wave — Bloomberg
- Predictions from The Simpsons that came true — Seffana Mohamed-Ajaz
- Morphocode’s city explorer — Morphocode
- Dodgy academic journals — The Economist
StopCorona Creator Shares How They Visualize COVID-19 Data Using AnyChart May 21st, 2020 by AnyChart Team
Earlier, we introduced you to a new, ever-updating COVID tracker that uses AnyChart to visualize the latest pandemic data in insightful charts, StopCorona.info. To let you know more, we also talked to Vadim Peskov, CEO at Diffco, the app development company behind StopCorona, and asked him a few questions.
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Charting COVID-19 Data and Models — DataViz Weekly May 15th, 2020 by AnyChart Team
Check out new interesting examples of charting COVID-19 data in action. We have seen a lot of visualizations over the past few days and selected the following projects to share with you today in DataViz Weekly:
- Fatality models for the United States – FiveThirtyEight
- Impact on climate change – Bloomberg Green
- (Now broken) correlation between the stock market and unemployment rates in America – The Washington Post
- Situation in Spain – The New York Times
COVID-19 Vaccine, Future, Impact, and Non-COVID Wiki Atlas Visualizations — DataViz Weekly May 8th, 2020 by AnyChart Team
Without any exaggeration, the vast majority of data visualizations made public these weeks (and already months) are about the novel coronavirus pandemic. In compliance with the general trend, three of the four projects presented in the new DataViz Weekly article shed light on issues related to COVID-19. Take a glance at a quick list of the featured data visualization works and read more to meet them.
- COVID-19 vaccine development timeframe and how to reduce it – NYT
- COVID-19 future, in playable simulators – M. Salathé & N. Case
- COVID-19 impact on traffic and air pollution in Europe – European Data Portal
- Atlas of places featured in Wikipedia – T. Noulas, R. Schifanella, D. Sáez-Trumper & J. Tan
Basic knowledge of HTML5 and JS is always helpful, but even if you are a beginner in this field, understand these four simple steps and you will be able to quickly get a good-looking cross-platform interactive choropleth map data visualization for your app or website!
What exactly are choropleth maps? When you break down the word, you see that choro- (“choros”) means “area” and pleth- (“plethos”) means “multitude.” Exactly, these maps are used to visualize statistical data related to multiple geographic areas. Each area is colored or shaded differently according to the value of the given data, making it easy to grasp how a measurement varies across a territory.
For this JS mapping tutorial, I will use open COVID-19 data to show the distribution of confirmed cases and deaths around the world by country. I will start with a basic choropleth map that will graphically represent the confirmed cases. Then I will add a legend, customize the tooltip, and add bubbles to visualize the number of deaths.
Let’s get started!
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