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Tutorials for Fusion Tables

Tutorials for Fusion Tables
Create with Fusion Tables These tutorials step you through using Fusion Tables’ features to accomplish neat things with your data. See what others have done in the Example Gallery. Basic tutorials Get started using Fusion Tables: Create a map Turn a table of locations into a map. Extending your knowledge Gathering data Create: Collaborative data gathering Give everyone their own table to update, while keeping the eagle-eye view on all of it. Maps Make an intensity map with custom boundaries Display polygons in different colors according to values in your data. Publishing / Embedding Embed visualizations in Google Sites Work around the JavaScript restrictions in Google Sites Merge tricks Use merge to apply map styles by category Want a different icon or color for the map? Working with other tools Use Overlays in Google MapMaker Host your location data in Google Fusion Tables to help while editing Google MapMaker. Search Clear search Close search Google apps Main menu Related:  Digital Humanities - Humanités Numériques

tuto Impure Impure is a new programming language designed to give non-programmers access to professional tools for data visualization. Users can use it to process and display data from social media feeds, financial information and more. Unlike Processing, a simple programming language for data visualization and art, Impure is a completely visual language - there's no need to learn any code. The programming language is also completely web hosted - there is no development environment to install. Above is a sceenshot of Impure being used to process a Twitter feed. Although it's targeted at non-programmers, some basic programming knowledge would clearly be useful. Given the data deluge that many enterprise face, easy tools for data visualization should be in high demand - especially in areas like social monitoring. For some background on the joys of data visualization, check out this TED talk.

Open Data Kit » Use To use ODK, you need to do three things -- design a form, setup a server, and connect the device to that server. Once those three things are done, you'll be ready to start data collection. You'll need three tools: Build or XLSForm -- to design your survey form.Collect -- running on an Android device to download and fill-in the survey.Aggregate -- for hosting the survey form and gathering the survey results. If any of this sounds complicated, we promise it's not! Below is a demo video of Collect, our Android-based data collection client. Fusion Tables - Gather, visualize, and share data tables online Bust your data out of its silo! Get more from data with Fusion Tables. Fusion Tables is an experimental data visualization web application to gather, visualize, and share data tables. Visualize bigger table data online Filter and summarize across hundreds of thousands of rows. Then try a chart, map, network graph, or custom layout and embed or share it. Two tables are better than one! Merge two or three tables to generate a single visualization that includes both sets of data. Make a map in minutes Host data online - and stay in control Viewers located anywhere can produce charts or maps from it. Visualize bigger table data online Import your own data Upload data tables from spreadsheets or CSV files, even KML. Visualize it instantly See the data on a map or as a chart immediately. Publish your visualization on other web properties Now that you've got that nice map or chart of your data, you can embed it in a web page or blog post. Two tables are better than one! Make a map in minutes

‘Stop-and-Frisk’ Is All but Gone From New York The widespread practice of stopping residents for what was deemed “suspicious” behavior, often called “stop-and-frisk,” was the defining tactic of the New York Police Department for a decade, pursued in the face of intensifying protests and dwindling crime, defended against civil-rights challenges, even declared indispensable to the continued safety of the streets. It has now all but vanished. Stops by Week January 2012 Stops peak with more than 16,000 per week. August 2013 A judge rules rules the tactic as employed is unconstitutional. Late 2013 Stops drop by more than 90% to fewer than 2,000 per week. It faded out at the end of the mayoral administration that promoted it so enthusiastically and the beginning of the administration that rode a wave of anger over it to a landslide victory. Stops by Race The stop-and-frisk tactic was employed exhaustively, but not evenly. A Steep Drop in Areas Once Targeted Stops in Central Brooklyn Has It Really Ended? Misdemeanor Arrests by Year Stops by Year*

GitHub - rkhatib/topotext Comment faire un Google Motion Chart Google Motion Chart est un outil puissant et simple d'utilisation qui permet d'interroger facilement un grand nombre de points de données. Voici en quelques étapes simples comment réaliser le sien. Faire parler des tableaux de données, c’est pas facile. On peut les décrire à la main, mais c’est long et fastidieux. On peut en faire des visualisations, mais ça coûte cher en design. OWNI l’a testé pour expliquer les causes de la crise grecque. Tutoriel par l’exemple : Tentons d’expliquer pourquoi un pays émet du CO2. 1. Trouvez une base de données. Sélectionnez les séries de données qui vous paraissent pertinentes. 2. Pour pouvoir travailler proprement, il disposer de données homogènes. On va ici se limiter à analyser les 27 pays de l’UE de 1990 à 2007. Les onglets AI et CA donnent accès à des données plus détaillées. 3. Mettez à jour le tableau et exportez. Exportez dans Microsoft Excel. On récupère maintenant chaque tableau dans Excel. 4. 1990 1991 Belgium 12 3 Bulgaria 15 4 5. 6. 7.

Gapminder: Unveiling the beauty of statistics for a fact based world view. 22 free tools for data visualization and analysis You may not think you've got much in common with an investigative journalist or an academic medical researcher. But if you're trying to extract useful information from an ever-increasing inflow of data, you'll likely find visualization useful -- whether it's to show patterns or trends with graphics instead of mountains of text, or to try to explain complex issues to a nontechnical audience. There are many tools around to help turn data into graphics, but they can carry hefty price tags. The cost can make sense for professionals whose primary job is to find meaning in mountains of information, but you might not be able to justify such an expense if you or your users only need a graphics application from time to time, or if your budget for new tools is somewhat limited. If one of the higher-priced options is out of your reach, there are a surprising number of highly robust tools for data visualization and analysis that are available at no charge. Data cleaning DataWrangler

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