Reviving the Statistical Atlas of the United States with New Data
▻http://flowingdata.com/2015/06/16/reviving-the-statistical-atlas-of-the-united-states-with-new-data
#visualisation #vintage avec #R
Reviving the Statistical Atlas of the United States with New Data
▻http://flowingdata.com/2015/06/16/reviving-the-statistical-atlas-of-the-united-states-with-new-data
#visualisation #vintage avec #R
Chart-Topping Songs as Graphs and Diagrams
▻http://flowingdata.com/chart-topping-songs-as-graphs-and-diagrams
Comme son nom l’indique :) #chanson #visualisation
Mapping plastic in the ocean
▻http://flowingdata.com/2014/08/21/mapping-plastic-in-the-ocean
In research efforts to understand marine debris, Andres Cozar Cabañas et al recently published findings on plastic debris in the open ocean. National Geographic and geographer Jamie Hawk mapped the data.
Network visualization game to understand how a disease spreads
▻http://flowingdata.com/2014/07/31/network-visualization-game-to-understand-how-a-disease-spreads
Getting started with visualization after getting started with visualization
▻http://flowingdata.com/2013/07/12/getting-started-with-visualization-after-getting-started-with-visualiza
Getting started with visualization after getting started with visualization
By Nathan Yau
Starting after started
Here’s where to go next once you’ve covered the basics of visualization. When it’s time to actually start making things.
It’s easy these days to get started with visualization. There are a lot of resources — books, tutorials, blogs, and classes — to help you learn, and the many new and old software applications let you work with data right away, point and click.
You don’t have to stop here though. A lot of people do stop at this point. They read the Tufte books (and by read, I mean casually flip through the pages and memorize the bold text), and stick them on a shelf or stack them on a desk like visualization diplomas. Maybe you’re one of these people. I was.
Mosquitos : The deadliest animal
▻http://flowingdata.com/2014/07/11/mosquitos-the-deadliest-animal
via Flowing Data
This graphic from the Gates Foundation is from a few months ago, but it was just National Mosquito Control Awareness Week. The small illustrations in this case make the graphic. Although I’m interested in seeing those “wide error margins.”
19 Maps That Will Blow Your Mind and Change the Way You See the World. Top All-time. You Won’t Believe Your Eyes. Watch.
▻http://flowingdata.com/2014/07/07/19-maps-that-will-blow-your-mind
J’ai eu quelque fois l’occasion de dire ici tout le mal que je pense des sites qui essayent désespérément de faire le buzz avec ce genre de titre et des cartes mille fois vues ailleurs. Je soupçonne l’excellent FlowingData (Nathan Yau) d’avoir eu la bonne idée se foutre de la gueule des petits apprentis-buzzers :)
19 Maps That Will Blow Your Mind and Change the Way You See the World. Top All-time. You Won’t Believe Your Eyes. Watch.
Mercator projection with pole shifted to where you liv
▻http://flowingdata.com/2014/06/09/mercator-projection-pole-shifts-to-where-you-live
Drew Roos made a thing that lets you move the poles of the Mercator projection to anywhere in the world.
▻http://mrgris.com/projects/merc-extreme
As you probably know, map projections all have their pros and cons since there are challenges that come with transforming a globe onto a two-dimensional surface. The Mercator projection, one of the most well-known, distorts as you approach the poles. The scale approaches infinity actually, which is why we’re used to seeing a Greenland that is bigger than Africa. (It’s not.)
Above shows the pole shifted to Washington, D.C. Trippy.
floatingsheep: The Beer Belly of America
▻http://www.floatingsheep.org/2010/02/beer-belly-of-america.html
The Beer Belly of America
At FloatingSheep, we’re willing to search for and analyze almost anything that falls within the realm of human experience. Sometimes this is mundane (pizza) and sometimes it is contentious (abortion) but most of the time it falls somewhere in between. Such as, where can I get a drink?
Voir aussi :
▻http://flowingdata.com/2014/05/29/bars-versus-grocery-stores-around-the-world
#états-unis #cartographie #visualisation #bars #bières #épiceries
Naked Statistics
▻http://flowingdata.com/2014/05/08/naked-statistics
Naked Statistics by Charles Wheelan promises a fun, non-boring introduction to statistics that doesn’t leave you drifting off into space, thinking about anything that is not statistics. From the book description:
For those who slept through Stats 101, this book is a lifesaver. Wheelan strips away the arcane and technical details and focuses on the underlying intuition that drives statistical analysis. He clarifies key concepts such as inference, correlation, and regression analysis, reveals how biased or careless parties can manipulate or misrepresent data, and shows us how brilliant and creative researchers are exploiting the valuable data from natural experiments to tackle thorny questions.
Fox News Makes the Best Pie Chart. Ever.
►http://flowingdata.com/2009/11/26/fox-news-makes-the-best-pie-chart-ever
Mais plus que le graphique lui même, ce qui est intéressant et marrant, ce sont les commentaires
Ah tiens, je l’avais raté... merci @simplicissimus pour la veille :)
In search of food deserts
▻http://flowingdata.com/2013/08/27/in-search-of-food-deserts
Très esthétique et assez efficace...
Last time I looked at where major grocery stores are across the United States. Where you shop for groceries changes depending on what region you live in, but hunger and nutrition carries less variance. It’s important that everyone has access to healthy food options, so I looked at the data, this time from Google and from a different angle. Instead of where stores are, I looked at how far away the nearest grocery store is.
The map above shows a sample of locations across the country, and line length represents distance to the nearest store. For example, in areas with a lot of lines headed to one spot is an area with fewer grocery stores. In contrast, mostly small line segments mean more grocery stores, and therefore less distance to travel to buy groceries.
#cartographie #infographie #visualisation #base_de_données #statistiques
British relationships throughout history
▻http://flowingdata.com/2013/08/26/british-relationships-throughout-history
Kindred Britain assembles and visualizes records of nearly 30,000 individuals, mainly (but not exclusively) British. Many of them are extremely well-known in the nation’s culture. The database in its entirety spans more than 1,500 years, but the time-period of densest concentration comes in the 19th century. Any person recorded here can be connected to any other person in the network through family relationships of ancestry, descent, siblinghood, marriage or some other type of familial affiliation. In Kindred Britain, family is all. The site is a panorama of engineers and painters, novelists and generals, scientists and merchants, and even a few reprobates, misanthropes and monsters.
#cartographie #visualisation #réseaux #database #base_de Données #big_data
#R : How to Visualize and Compare #Distributions
▻http://flowingdata.com/2012/05/15/how-to-visualize-and-compare-distributions
There are a lot of ways to show distributions, but for the purposes of this tutorial, I’m only going to cover the more traditional plot types like histograms and box plots.
(il m’a bien aidé ce #tuto)
Map shows illegal activity in San Francisco Chinatown, from 1885
▻http://flowingdata.com/2013/08/19/map-shows-illegal-activity-in-san-francisco-chinatown-from-1885
From the David Rumsey map collection, the detailed map of San Francisco Chinatown shows areas of known illicit activity.
In 1885, at the height of the anti-Chinese hysteria in California, the official Report of the Special Committee of the Board of Supervisors was issued, reporting on the “Condition of the Chinese Quarter and the Chinese in San Francisco.” This inflammatory report included the rare folding color map of Chinatown, but in the usual “small-scale” version (approx. 8½x19½ inches). This map was also issued in the San Francisco Municipal Report of 1884-85, and in Farwell’s The Chinese at Home and Abroad (see our 5807.000).
Google search suggestions by country
▻http://flowingdata.com/2013/08/08/google-search-suggestions-by-country
Google search suggestions have transformed into a never-ending source of entertainment and a candid peek into what people look for in the world. We’ve seen insecurities change with age and stereotypes of states in the US. Noah Veltman banked on the locality of suggestions for a country-specific view of the world. He shows suggestions for the same query for the United States, Canada, the United Kingdom, Australia, and New Zealand.
Climbing the income ladder
▻http://flowingdata.com/2013/07/22/climbing-the-income-ladder
Via Nathan Yau de Flowing Data et repris par le NYT. Toujours très intéressant...
In a study conducted by researchers at Harvard and UC Berkeley, data shows spatial variations for the chances of rising out of poverty into higher income brackets. The New York Times reports:
Climbing the income ladder occurs less often in the Southeast and industrial Midwest, the data shows, with the odds notably low in Atlanta, Charlotte, Memphis, Raleigh, Indianapolis, Cincinnati and Columbus. By contrast, some of the highest rates occur in the Northeast, Great Plains and West, including in New York, Boston, Salt Lake City, Pittsburgh, Seattle and large swaths of California and Minnesota.
“Where you grow up matters,” said Nathaniel Hendren, a Harvard economist and one of the study’s authors. “There is tremendous variation across the U.S. in the extent to which kids can rise out of poverty.”
Two things. First, the NYT piece is really nice. Graphics and interactives are typically shown separate from the written story, but NYT has been shifting as of late and I’m sure other publications will follow. (Although, as you can see in the credits, eight people made the graphics, and most places don’t have such resources yet.) The story is all tied together, so you read and interact in a continuous flow.
Second, the Harvard/UC Berkeley research group released the data, so you can have a go yourself.
Global migration and debt
▻http://flowingdata.com/2013/07/09/global-migration-and-debt
Ça c’est pas mal du tout
Global Economic Dynamics, in collaboration with 9elements, provides an explorer that shows country relationships through migration and debt. Inspired by a New York Times graphic from a few years ago, which was a static look at debt, the GED interactive allows you to select among 46 countries and browse data from 2000 through 2010.
Each outer bar represents a country, and each connecting line either indicates migration between two countries or bank claims, depending on which you choose to look at. You can also select several country indicators, which are represented with bubbles. (The image above shows GDP.) Although, that part of the visualization is tough to read with multiple indicators and countries.
#data #statistiques #visualisation #dette #agglomérations #villes
Grocery store geography
▻http://flowingdata.com/2013/06/26/grocery-store-geography
via flowingdata
I’ve been poking around grocery store locations, courtesy of AggData, the past few days.
There’s a grocery store just about everywhere you go in the United States, because, well, we gotta eat. They look similar in that they sell produce on one side, meat in the back, and snacks and soda on the side opposite the produce. Magazines and small candies are carefully situated at eye-level by the cash registers. There’s usually a deli counter and prepared foods near the bread section. And yet, despite the generic format and layout, these stores can remind us of places and specific periods of our lives.
#cartographie #états-unis #walmart #supermarchés #cartographie