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Interactive Data Visualization for the Web

Interactive Data Visualization for the Web
Copyright © 2013 Scott Murray Printed in the United States of America. O’Reilly books may be purchased for educational, business, or sales promotional use. Online editions are also available for most titles ( For more information, contact our corporate/institutional sales department: 800-998-9938 or <>. Nutshell Handbook, the Nutshell Handbook logo, the cover image, and the O’Reilly logo are registered trademarks of O’Reilly Media, Inc. Interactive Data Visualization for the Web, the cover image of a long-tail bushtit, and related trade dress are trademarks of O’Reilly Media, Inc. Many of the designations used by manufacturers and sellers to distinguish their products are claimed as trademarks. While every precaution has been taken in the preparation of this book, the publisher and author assume no responsibility for errors or omissions, or for damages resulting from the use of the information contained herein.

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What D3.js is Not I have played with D3.js quite a bit recently. After exploring its API and building a rather complex chart, I come to realize that I have misunderstood D3 for a long time. It’s not only me, after talking to my friends, they also have misconceptions regarding D3. So I’ve decided to write this post to clear some of the common misunderstandings. D3 is Not a Charting Library These charts explain why BYOD security is critical I was 31 when I was diagnosed with breast cancer. My gynecologist called, and I ducked into the supply closet of our Union Square office for some privacy. She said something about a New York Times article, about estrogen receptors. It was February 2014—we’d just moved offices—and I was surrounded by unpacked bins of computer wire and post-it notes. I didn’t know how to extricate myself from the mess and re-enter the world with this information.

D3 <div id="js_warning"><strong>JavaScript is turned off, so this page won&rsquo;t be very interactive.</strong> Switch JavaScript back on in your web browser for the full experience.</div> These tutorials have been expanded into a book, Interactive Data Visualization for the Web, published by O’Reilly in March 2013. Purchase the ebook and print editions from O’Reilly.

Northwestern University Center for Interdisciplinary Exploration and Research in Astrophysics - Stellar Evolution The Formation of Nuclear Star Clusters by Fabio Antonini The three simulations correspond to different initial distributions for the cluster orbits. Most galaxies, including the Milky Way, contain massive (10^7 Solar masses) star clusters at their center. Understanding the formation of such nuclear star clusters is important as it could shed light on the processes that have shaped the central regions of galaxies and led to the formation of their central black holes. This visualization shows the (simulated) formation of a compact nuclear star cluster at the center of the dwarf starburst galaxy Henize 2-10.

How to Embed Graphs in a Blog or Website When you embed a Plotly graph, it means you’re sharing your graph, your data and the code that describes your graph all in one place. You can embed any Plotly graph. The embedding process is the same whether you're creating graphs from the online workspace or using one of Plotly's APIs. The 37 best tools for data visualization It's often said that data is the new world currency, and the web is the exchange bureau through which it's traded. As consumers, we're positively swimming in data; it's everywhere from labels on food packaging design to World Health Organisation reports. As a result, for the designer it's becoming increasingly difficult to present data in a way that stands out from the mass of competing data streams. One of the best ways to get your message across is to use a visualization to quickly draw attention to the key messages, and by presenting data visually it's also possible to uncover surprising patterns and observations that wouldn't be apparent from looking at stats alone. And nowadays, there's plenty of free graphic design software to help you do just that.

How to Find the Right Chart Type for your Numeric Data 22 Feb 2016 Charts help you visualize numeric data in a graphical format but the problem is there are just too many types of charts to choose from. This diagram will help you pick the right chart for your data type. couch mode print story Charts help you visualize numeric data in a graphical format but the problem is there are just too many types of charts to choose from. Path Transitions When implementing realtime displays of time-series data, we often use the x-axis to encode time as position: as time progresses, new data comes in from the right, and old data slides out to the left. If you use D3’s built-in path interpolators, however, you may see some surprising behavior: Why the distracting wiggle? There are multiple valid interpretations when interpolating two paths. Here’s the relevant code from the above chart: data.push(random()); data.shift(); path.transition().attr("d", line);

VisIt About VisIt VisIt is an Open Source, interactive, scalable, visualization, animation and analysis tool. From Unix, Windows or Mac workstations, users can interactively visualize and analyze data ranging in scale from small (<101 core) desktop-sized projects to large (>105 core) leadership-class computing facility simulation campaigns. Users can quickly generate visualizations, animate them through time, manipulate them with a variety of operators and mathematical expressions, and save the resulting images and animations for presentations.

How to Make Your Own Bad USB « Null Byte How to Make Your Own Bad USB Hello, everyone! Many of you don't even know about my existence here on Null Byte, so I thought of contributing something rather interesting. Recently, someone asked how to make your own "Bad USB," and I promised to make a how-to on this topic. Jambalaya: an interactive environment for exploring ontologies Margaret-Anne Storey, Natalya F. Noy, M.A. Musen, Casey Best, Ray Fergersen, Neil Ernst, “Jambalaya: an interactive environment for exploring ontologies”, International Conference on Intelligent User Interfaces, 2002 (Link) Abstract:This demonstration presents a visualization environment for exploring ontologies. An ontology defines a common vocabulary and structure of an information space for researchers and domain experts to exchange and share knowledge.

Creating a dynamic d3 visualization from the GitHub API As someone who works with data on a daily basis, I’m always impressed and inspired by interactive charts and dashboards. I’ve built plenty of dynamic dashboards within Excel and, more recently, within Google spreadsheets (here, here and here), but never my own custom web charts. I’ve wanted to learn d3 for a while, but until recently didn’t have the necessary Javascript chops to do this. D3.js Tips and Tricks Generate a heatmap with Leaflet.heat A heatmap is a two dimensional representation of values encodes as colours. In our case these colours are superimposed over a map generated using leaflet.js. The example here represents seismic activity in July / August of 2013 in central New Zealand, when they were unfortunate enough to experience a series of earthquakes.