Mathematica: L'outil de Calcul Technique le Plus Abouti With energetic development and consistent vision for three decades, Mathematica stands alone in a huge range of dimensions, unique in its support for today's technical computing environments and workflows. A Vast System, All Integrated Mathematica has over 6,000 built-in functions covering all areas of technical computing—all carefully integrated so they work perfectly together, and all included in the fully integrated Mathematica system. Not Just Numbers, Not Just Math—But Everything Building on three decades of development, Mathematica excels across all areas of technical computing—including neural networks, machine learning, image processing, geometry, data science, visualizations and much more. Unimaginable Algorithm Power Mathematica builds in unprecedentedly powerful algorithms across all areas—many of them created at Wolfram using unique development methodologies and the unique capabilities of the Wolfram Language. Higher Level Than Ever Before Superfunctions, meta-algorithms...
Public preview of project codename “GeoFlow” for Excel delivers 3D data visualization and storytelling Editor’s note: Since this article was originally published in April 2013, Project codename “GeoFlow” has been renamed Power Map as part of the new Power BI for Office 365 offering. Today we are announcing the availability of the project codename “GeoFlow” Preview for Excel 2013, a result of collaborations between several teams within Microsoft. GeoFlow lets you plot geographic and temporal data visually, analyze that data in 3D, and create interactive “tours” to share with others. GeoFlow originated in Microsoft Research, evolving out of the successful WorldWide Telescope project for scientific and academic communities to explore large volumes of astronomical and geological data. With GeoFlow, you can: Map Data: Plot more than one million rows of data from an Excel workbook, including the Excel Data Model or PowerPivot, in 3D on Bing maps. Unlocking insights within geospatial data like ticket sales is now possible with GeoFlow. Find out more about Microsoft BI.
Four steps to analyzing big data with Spark By Andy Konwinski, Ion Stoica, and Matei Zaharia In the UC Berkeley AMPLab, we have embarked on a six year project to build a powerful next generation big data analytics platform: the Berkeley Data Analytics Stack (BDAS). We have already released several components of BDAS including Spark, a fast distributed in-memory analytics engine, and in February we ran a sold out tutorial at the Strata conference in Santa Clara teaching attendees how to use Spark and other components of the BDAS stack. In this blog post we will walk through four steps to getting hands-on using Spark to analyze real data. What makes Spark so fast? Follow these four steps and see for yourself how easy it is to get up and running with Spark: Familiarize yourself with the Spark project. Our vision is to build the next generation stack of open-source data analytics software, and the Spark cluster computing framework is a major step towards that vision. Related:
Spreadsheet converts tweets for social network analysis in Gephi EDIT 05/15/13: I’ve posted two scripts, one in PHP and one in Python, that overcome the main limitation of this spreadsheet–they pull in all mentioned names rather than just the first one. Download one or both here. If you’ve ever wanted to visualize Twitter networks but weren’t sure how to get the tweets into the right format, this spreadsheet I’ve been using in my classes might be worth a try. Download the file and open it locally in Excel or OpenOffice to add your own data (right now it uses some of my recent tweets as example data). Add the username(s) of your tweet author(s) to column A of the “code lives here” worksheet.Add your author(s)’ tweets to column B.Copy columns C through H as far down as your tweets go.Export the “output lives here” worksheet as a CSV and open it in Gephi (you may need to copy the formulae in columns A and B as far down as your data go). Here is a network graph of the example data.
Chart and image gallery: 30+ free tools for data visualization and analysis The chart below originally accompanied our story 22 free tools for data visualization and analysis (April 20, 2011). We're updating it as we cover additional tools, including 8 cool tools for data analysis, visualization and presentation (March 27, 2012) and Six useful JavaScript libraries for maps, charts and other data visualizations (March 6, 2013). Click through to those articles for full tool reviews. Features: You can sort the chart by clicking on any column header once to sort in ascending order and a second time to sort by descending (browser JavaScript required). Skill levels are represented as numbers from easiest to most difficult to learn and use: Users who are comfortable with basic spreadsheet tasksUsers who are technically proficient enough not to be frightened off by spending a couple of hours learning a new applicationPower usersUsers with coding experience or specialized knowledge in a field like GIS or network analysis. Data visualization and analysis tools
The Graphic Continuum Jon Schwabish and Severino Ribecca recently released a poster taxonomy of different types of charts, and how they all relate to each other. We think this is a great resource for designers everywhere, so we were especially interested in their take on the project. The Graphic Continuum began as I thought about the different ways we can plot data into different types of charts. My understanding of the different relationships between charts evolved over time by reading a variety of data visualization books, sketching different ideas and layouts, and presenting my ideas to different audiences. Simply put, one of the biggest challenges of visualizing chart types is that there are just a lot of ways to visualize data. But how do you create a visualization of an inherently nonlinear, complex system of graphic types? The first drafts of The Graphic Continuum were laid out in a grid with a single dot in the top-left. Feeling stuck, we went analog.
30 Simple Tools For Data Visualization There have never been more technologies available to collect, examine, and render data. Here are 30 different notable pieces of data visualization software good for any designer's repertoire. They're not just powerful; they're easy to use. In fact, most of these tools feature simple, point-and-click interfaces, and don’t require that you possess any particular coding knowledge or invest in any significant training. Let the software do the hard work for you. Your client will never know. 1. iCharts 2. FusionCharts Suite XT is a professional and premium JavaScript chart library that enables us to create any type of chart. 3. Modest Maps is a small, extensible, and free library for designers and developers who want to use interactive maps in their own projects. 4. Pizza Pie Charts is a responsive pie chart based on the Snap SVG framework from Adobe. 5. Raw is a free and open-source web application for visualizing data flexibly and as easy as possible. 6. 7. 8. 9. 10. 11. 12. jsDraw2DX 13.
15 outils de curation incontournables Que ce soit dans le cadre d’une veille ou pour organiser le flux incessant d’informations qui nous submerge tous, les outils de curation sont devenus des services indispensables. La curation est plus qu’une mode passagère, elle s’inscrit dans un mouvement de fond sur le web pour répondre à l’infobesité et au surf permanent. La curation est aussi un bon moyen pour promouvoir une marque , sa réputation en ligne ou encore pour générer du traffic vers son site en ligne. Les outils et services de curation sont très nombreux. Trop nombreux ? En tout cas voici une sorte de curation des outils de curation Ma liste personnelle des 15 outils incontournables pour votre curation de contenus. Scoop.it Incontestablement mon préféré dans cette liste d’outils de curation. Paper.li C’est le concurrent direct de Scoop.it. Pearltrees Encore une succès story dans l’univers des outils de curation. Flipboard C’est l’outil idéal pour la curation sur dispositifs mobiles, tablettes et smartphones.
Datavisualization.ch Selected Tools Let's Make a Bar Chart with Lyra - Jim Vallandingham A few days ago Arvind Satyanarayan from the UW Interactive Data Lab released an alpha version of Lyra that promises to be a way to create complex data visualizations without code. Think of it like an open source Adobe Illustrator, for data visualizations. Sounds pretty awesome, right? Let’s find out. There are a number of very interesting examples to learn from on the Lyra main page. I wanted to see what would be required to create a really basic bar chart – as a way to start to learn more about this interesting tool. Here’s the final product: Pretty simple right? WARNING: Lyra is labelled as alpha and while already a great tool, its got some issues . Your Visualization Development Environment Here’s what it looks like when you first open Lyra : I’ve annotated the app with my own terminology to provide a bit of orientation. The far left panel provides capabilities to add data to the visualization and manipulate this data. These marks are organized into layers (just like Illustrator!).
22 outils gratuits en ligne pour créer des nuages de mots-clés En janvier 2012, NetPublic a publié l’article ressource : 6 solutions gratuites en ligne pour créer des nuages de mots-clés. Les nuages de mots-clés permettent de représenter des mots-clés les plus utilisés dans un texte, de donner une représentation visuelle formalisée de termes, de créer à partir de mots… Avec des variantes de fonctionnalités selon les applications. Liste de solutions gratuites pour réaliser des nuages de mots-clés Le service Ecoles-Médias de la République et Canton de Genève (Suisse) va aujourd’hui plus loin en recensant 22 outils gratuits en ligne pour créer des nuages de mots-clés. Chaque solution est présentée dans un classement par popularité sur le Web et également avec une vignette qui présente un résultat de nuage de mot-clé généré via chaque outil. Les 22 outils