https://www.youtube.com/watch?v=gDHCzj4yI4g
La pandemia de la COVID-19 ha puesto de manifiesto lo importantes que son los datos en general, y sus representaciones gráficas en particular, para la toma de decisiones, de lo personal a lo político, de lo económico a lo social. Hablaremos de las experiencias de visualizar datos del COVID-19 y de la relavancia de los datos en nuestras vidas.
The risk of contagion is highest in indoor spaces but can be reduced by applying all available measures to combat infection via aerosols. Here is an overview of the likelihood of infection in three everyday scenarios, based on the safety measures used and the length of exposure
Alberto Cairo escribe y diseña visualizaciones de datos. En esta entrevista nos cuenta sobre sus libros y sus descubrimientos. El nos dice que “Una visualización es un argumento visual. Necesita tiempo y atención para poder leerlo con cuidado.” Y que no tenemos que usar los gráficos para confirmar lo que creemos. También nos cuenta como son las clases para infografistas y como reflexionan a través de los gráficos. Hablamos de un futuro con más alfabetización visual, donde la gente está más entrenada a leer gráficos y las interpretaciones que proponen. El sostiene que para enseñar infografía es importante enseñar a interpretar los números y que la visualización de datos nos permite entender los números de una manera más crítica.
welcome to the year 2030.
there are 1.2 billion more people on the planet.
70% of us are living in cities now.
in order to house 1.2 billion more people,
all of us are sharing more household goods and services than ever before.
we refer to this sharing as co-living.
and many more of us are living this way now.
but it’s not a new thing.
communal living has always been a solution to common problems.
like rapid urbanisation, loneliness, and high living costs.
but what does co-living look like in the year 2030?
who is it for?
how has it changed our society?
what are we sharing?
with many more of us now co-living,
there is no one configuration.
discover what type of co-living would be uniquely suited for you.
reserve your spot for ONE SHARED HOUSE 2030.
The New York Times prepared a powerful front page for its May 24 print edition, marking the somber milestone of 100,000 coronavirus deaths in the United States.
The newspaper listed the names of 1,000 people who died of COVID-19 — just 1% of the total death toll.
The newspaper staff combed through obituaries and death notices for people whose cause of death was listed as COVID-19, and listed people’s names, ages, and facts about their lives.
Lo primero que me chocó es la gama de colores del mapa. Lo normal es que se use un color y se aplique una tonalidad que se va oscureciendo conforme los valores son más altos. En este caso el valor más alto es de un color diferente de la gama, El negro no es marrón.
Además, la diferencia de color es muy grande respecto a Italia con una variación del 5%. No sé si esto es intencionado o tan solo un error de diseño. Este mapa va a la galería de ejemplos de malas visualizaciones para mis alumnos. Para colmo, los datos no eran correctos.
Como ya se dieron cuenta @resd9 y @A_Sorines el dato de Bélgica era erróneo en vez de 15,70% era 65,67%. El mapa lo publicó la Vanguardia y ha rectificado el dato aunque mantiene el color negro.
COVID-19 (2019 novel Coronavirus) is a current epidemic as of today. Developers around the world are building applications for the public to get up-to-date and accurate information as quickly as possible.
If you are a developer, you may also be able to contribute to some of these projects.
Teams are making ready-to-use COVID-19 datasets easily accessible for the wider data visualization and analysis community. Johns Hopkins posts frequently updated data on their github page, and Tableau has created a COVID-19 Resource Hub with the same data reshaped for use in Tableau.
These public assets are immensely helpful for public health professionals and authorities responding to the epidemic. They make data from multiple sources easy to use, which can enable quick development of visualizations of local case numbers and impact.
At the same time, the stakes are high around how we communicate about this epidemic to the wider public. Visualizations are powerful for communicating information, but can also mislead, misinform, and — in the worst cases — incite panic. We are in the middle of complete information overload, with hourly case updates and endless streams of information.
This is a short tutorial introducing the basic elements and concepts of D3.
Audio Landscape is a novel music visualizer that constructs a landscape based on the MP3 that you give it.
From Data to Viz leads you to the most appropriate graph for your data. It links to the code to build it and lists common caveats you should avoid.
What kind of data do you have? Pick the main type using the buttons below. Then let the decision tree guide you toward your graphic possibilities.
Data visualizations are a powerful way to display and communicate data that otherwise would be impossible to transmit in effective and concise ways. The spread of broadband Internet, the easier access to reusable datasets, the rise in read/write digital media literacies, and the lower barrier to generate data visualizations are making mass media to intensively use of infographics. Newspaper and online news sites are taking advantage of new, affordable and easy to access data visualization tools to broadcast their messages. How can these new tools and opportunities be used effectively? What are good practices regarding data visualization for a general audience?
After an introduction to a series of key concepts about visualizing data the lecture will follow with an analysis of a series of significant data visualizations (tables, pie and bar charts, maps and other systems) from TV, daily newspapers and news websites to detect good and bad practices when visualizing statistical information. The lecturer will then analyze recent literature of visualization studies regarding persuasion, memorability and comprehension. What are more effective embellished or minimal data visualizations? Does graphical presentation of data make a message more persuasive?
Basically, women were slightly more liberal with the modifiers, but otherwise they generally agreed (and some of the differences may be sampling noise). The results were similar across the survey—men and women tended on average to call colors the same names.
Each user was shown a random color and asked to type in a name. We asked people provide the most generic name possible, dropping things like modifiers (blue instead of light blue). Instead of using the entire RGB spectrum (millions), we pruned the color set to 216 «web safe» colors. This helped ensure every color had many responses. We left it online for a week or so and collected 6,276 color responses.
City Roads hace una sola cosa y la hace bien. A partir del nombre de una ciudad, toma los datos de OpenStreetMap y los vuelca en una espartana imagen bicolor sin texto alguno, con excepción de la ciudad en cuestión. Las únicas opciones que da son elegir esos dos colores: el de las calles y el del fondo.
…a collection of simple charts made with d3.js.
This gallery displays hundreds of chart, always providing reproducible & editable source code.
El año en el que más se construyó en España fue 1960. Por primera vez en varias décadas, el país experimentó una estabilidad económica que permitió un pequeño salto en la calidad de vida. Coincidió con el éxodo rural, para el que hicieron falta nuevas construcciones que acogiesen a los recién llegados del campo, y con el origen de un turismo que capitalizaría la economía española hasta nuestros días. La época conocida como el ‘desarrollismo’ propició dos programas de planificación económica y social en torno a zonas industrializadas y de costa que dibujaron el desarrollo urbano de los años posteriores.
Según el castastro, el 17% de construcciones de todas las capitales de provincia data de esa década. Luego llegaron los PAU, que alejaron la vida del casco histórico de las capitales, las grandes urbanizaciones, la burbuja y, también, los cadáveres inmobiliarios de la crisis.
…la fabricación en cadena del Seat 600 hizo que el automóvil pasara de ser un artículo de lujo a una utilidad de clase media, dando lugar a un nuevo enfoque urbanístico: ¿por qué vivir en el centro si ya es posible hacerlo en una casa más amplia sin tardar más de 20 minutos al trabajo?
Nació así el fenómeno del ‘urban sprawl’ o la dispersión urbana, que dio lugar a casi todos los barrios fuera de la M-30, como Aluche, Móstoles o Vallecas, donde se construyeron principalmente edificios de ladrillo; o Fuencarral y Pozuelo, lugares al norte en los que proliferaron las primeras urbanizaciones de chalés.
…este nuevo concepto de Madrid supuso la ruptura de una ciudad centrada en la proximidad, en una ciudad dispersa, basada en el coche.
This is part of a series of examples that describe the basic operation of the D3.js force layout.
…linkDistance tells the force layout the desired distance between connected nodes. It may seem strange that D3 doesn’t simply compel all links to be that distance. The force layout, however, takes other factors into account as well, which sometimes prevents it from achieving the exact link distance in all cases.
…charge, so named because it’s a property that acts like electrical charge on the nodes. With force-directed graphs in particular, charge causes nodes in the graph to repel each other. This behavior is generally desirable because it tends to prevent the nodes from overlapping each other in the visualization.
The Amazon Echo as an anatomical map of human labor, data and planetary resources
Una exploración sobre los alimentos que pasan por Mercamadrid
Suite à la liste des sites web en .gouv.fr générée sur le dépôt GitHub gouvfrlist, voici une représentation des domaines et sous-domaines par ministère et administrations (déconcentrées). Nous nous sommes également appuyé sur la liste du top 250 des démarches administratives, la liste des sites en .gouv.fr datant de 2014 et surtout la liste des noms de domaine .fr de l’AFNIC en open data .
Les données ont été retraitées et sont accessible dans ce fichier d’import KUMU et sont publiées sur un jeu de données sur data.gouv.fr
Modes of access and tools to manipulate data have brought marginalized actors to collaboratively create alternative narratives to those delivered by dominant power structures. Non-profit organizations and activist groups increasingly base their campaigns on data, using visualization as an agency tool for change. Data-driven alternative narratives counteract the hegemony of information, questioning the status quo and promoting the non-flattening of the data society, seeking to strengthen democracy. Data visualization is a decisive adversarial tool (DiSalvo, 2012) for turning data into alternative narratives. Translating data into visual representations for alternative narratives is an activist practice that requires a critical approach to data to make a political position evident and coherent.
This is an open, ongoing, and collaborative archive of data visualizations in online projects that showcase alternative narratives. It seeks to encourage the creation of other narratives to those that dominate and to promote discussion of existing ones. If you know of a project, please add it.
The Leaflet DVF is an extension to the Leaflet JavaScript mapping library. The primary goal of the framework is to simplify data visualization and thematic mapping using Leaflet – making it easier to turn raw data into compelling maps.
Flapper is a jQuery plugin that replicates the split-flap (or «Solari») displays that used to be common in train stations and airports, and your dad’s alarm clock in the 70s.
To use, just attach Flapper to any input on your page. Whenever the input’s change event is fired, Flapper will update the display.
VivaGraphJS is designed to be extensible and to support different rendering engines and layout algorithms. Underlying algorithms have been broken out into ngraph.
The larger family of modules can be found by querying npm for «ngraph».
There are different ways of creating choropleth maps in Python. In a previous notebook, I showed how you can use the Basemap library to accomplish this. More than 2 years have passed since publication and the available tools have evolved a lot. In this notebook I use the GeoPandas library to create a choropleth map. As you’ll see the code is more concise and easier to follow along.
Many datasets are intrinsically hierarchical. Consider geographic entities, such as census blocks, census tracts, counties and states; the command structure of businesses and governments; file systems and software packages. And even non-hierarchical data may be arranged empirically into a hierarchy, as with k-means clustering or phylogenetic trees.
This module implements several popular techniques for visualizing hierarchical data:
Node-link diagrams show topology using discrete marks for nodes and links, such as a circle for each node and a line connecting each parent and child. The “tidy” tree is delightfully compact, while the dendrogram places leaves at the same level. (These have both polar and Cartesian forms.) Indented trees are useful for interactive browsing.
Adjacency diagrams show topology through the relative placement of nodes. They may also encode a quantitative dimension in the area of each node, for example to show revenue or file size. The “icicle” diagram uses rectangles, while the “sunburst” uses annular segments.
Enclosure diagrams also use an area encoding, but show topology through containment. A treemap recursively subdivides area into rectangles. Circle-packing tightly nests circles; this is not as space-efficient as a treemap, but perhaps more readily shows topology.
Descripción de las compañías que conforman Alphabet, el gran conglomerado de empresas cuyo principal subsidiaria es Google.
In the last two decades, states have relied on private contractors to support military operations in conflict situations. Without the necessary democratic scrutiny and public debate, Private Military and Security Companies (PMSCs) have provided services that traditionally were performed by national armies and public authorities –such as interrogation of detainees, protection of military assets, training of local armed forces, collection of intelligence and the performance of defensive and even offensive military activities-.
