https://ressources.data.sncf.com/explore/Related: Webmapping - Datavisualisations - Open data • Bases de données urbanisme et environnement • `test 1023
Une version python pour l’outil de synthèse colorée Dans le but de pouvoir analyser des images de grande taille plus rapidement, un re-développement de l’outil sous Python a été réalisé. Le code source est disponible librement sur ce dépôt Github : Description du fonctionnement Ce projet utilise la bibliothèque Flask, qui permet de créer des applications web multi-threads, c’est à dire avec plusieurs traitements possibles en parallèle. Cela permet d’offrir une interface graphique (page HTML) et de pouvoir suivre l’avancement des analyses (barre de progression). Martin Grandjean » Digital humanities, Data visualization, Network analysis » Mapping a Century of International Congresses International congresses, meetings of diplomats and experts, have been almost exclusively European events for more than a century. This map shows the location of the +8000 congresses held between 1840 and 1960 and highlights the domination of certain urban areas in Western Europe. A map of the distribution of international congresses with a focus on Europe (between 1840 and 1960, 6 congresses out of 7 took place in Europe).
See How the World’s Most Polluted Air Compares With Your City’s The floating particles on this page depict microscopic particulate pollution called PM2.5. The number of particles you see here represents the upper limit for “good” air quality, as defined by the United States Environmental Protection Agency: 12 micrograms per cubic meter over 24 hours. We made our best guess for your location, or you can pick another.This is pollution in New York City on the worst air quality day this year. Particulate concentrations reached 41 µg/m3 during the highest hour, a level that would be considered “unhealthy for sensitive groups.”
Visualisation de données dans R avec ggplot2 et autres packages owned this note owned this note Préparation de données (spatiales) avec R owned this note owned this note Movement data exploration and analysis MovingPandas implements Trajectory data structures and corresponding methods for handling movement data based on GeoPandas. The official documentation is hosted on ReadTheDocs. For an example use case, check out our movement data exploration tutorial. Features Convert GeoPandas GeoDataFrames of time-stamped points into MovingPandas Trajectories and TrajectoryCollections Add trajectory properties, such as movement speed and direction Split continuous observations into individual trips Generalize Trajectories Aggregate TrajectoryCollections into flow maps Create static and interactive visualizations for data exploration Tutorials
What's New in Revision 10? » Gridded Population of the World (GPW), v4 What's New in Revision 10? In July 2016, SEDAC released the Gridded Population of the World, version 4 (GPWv4) data collection which included seven raster data sets available at 30-arcsecond resolution in GeoTiff format, and one vector data set of administrative unit center points. For this latest release, the eight 4.0 data sets originally released with version 4 have been updated, and a ninth data set, on basic demographic characteristics (age and sex), has been added. The nine data sets, collectively referred to as the Revision 10 (or v4.10) data sets, incorporate boundary or population updates for 65 countries, additional attributes in the centroids and national identifier data sets, an updated water mask which includes more recent glacier data and local water data sources for high latitude countries, and additional format and resolution options.