Backbone.js Gallery · d3/d3 Wiki Wiki ▸ Gallery Welcome to the D3 gallery! More examples are available for forking on Observable; see D3’s profile and the visualization collection. Please share your work on Observable, or tweet us a link! Visual Index Basic Charts Techniques, Interaction & Animation Maps Statistics Examples Collections The New York Times visualizations Jerome Cukier Jason Davies Jim Vallandingham Institute for Health Metrics and Evaluation Peter Cook Charts and Chart Components Bar Chart Histogram Pareto Chart Line and Area Chart Pie Chart Scatterplot and Bubble chart Parallel Coordinates, Parallel sets and Sankey Sunburst and Partition layout Force Layout Tree Misc Trees and Graphs Chord Layout (Circular Network) Maps Misc Charts Miscellaneous visualizations Charts using the reusable API Useful snippets Tools Interoperability Online Editors Products Store Apps
Raphaël—JavaScript Library jsoup Java HTML Parser, with best of DOM, CSS, and jquery jQuery Eclipse Collections - Features you want with the collections you need. History of Eclipse Collections The origin of Eclipse Collections was started off as a collections framework named Caramel at Goldman Sachs in 2004. Since then the framework has evolved, and in 2012, it was open sourced to GitHub as a project called GS Collections. GS Collections has been presented at number of conferences including JVM Summit in 2012 and JavaOne in 2014. Over the years, around 40 or so developers from the same company have contributed to the collections framework. To maximize the best nature of open source project, GS Collections has been migrated to the Eclipse Foundation, re-branded as Eclipse Collections in 2015. Reference Guide A comprehensive reference guide of the library is available on GitHub: Reference Guide.
Introducing PourOver and Tamper Client-side superfast collection management from the NYT This project was documented and released as part of the first OpenNews Code Convening. Today we’re open-sourcing two internal projects from The Times: PourOver.js, a library for fast filtering, sorting, updating and viewing large (100k+ item) categorical datasets in the browser, andTamper, a companion protocol for compressing categorical data on the server and decompressing in your browser. We’ve achieved a 3–5x compression advantage over gzipped JSON in several real-world applications. We invite you to explore the docs and examples for both projects; we also have some next examples over on the Times’ Open blog. Collections are important to developers, especially news developers. Dissatisfied with this state of the art, we made PourOver as an attempt to standardize an efficient and extensible model of client-side collection management and weaken reliance on server-side collection operations. Enter Tamper Buffered PourOvers In the Wild
Mockito in six easy examples Mockito is a fantastic mock library for Java. I’m fascinated by how easy it is to use, compared to other things out there both in the Java and .NET world. Here is everything you need to know to get started in six really easy examples. First of all, get mockito from To create a stub (or a mock), use mock(class). import static org.mockito.Mockito.*; import static org.junit.Assert.*; import java.util.Iterator; import org.junit.Test; .... This example creates a mock iterator and makes it return “Hello” the first time method next() is called. Stubs can also return different values depending on arguments passed into the method. @Test public void with_arguments(){ Comparable c=mock(Comparable.class); when(c.compareTo("Test")).thenReturn(1); assertEquals(1,c.compareTo("Test")); } This creates a stub Comparable object and returns 1 if it is compared to a particular String value (“Test” in this case). This stub comparable returns -1 regardless of the actual method argument.
Common Ports The following tables list the most common communication ports used by services, daemons, and programs included in Red Hat Enterprise Linux. This listing can also be found in the /etc/services file. For the official list of Well Known, Registered, and Dynamic ports as designated by the Internet Assigned Numbers Authority (IANA), refer to the following URL: Table C-1 lists the Well Known Ports as defined by IANA and is used by Red Hat Enterprise Linux as default communication ports for various services, including FTP, SSH, and Samba. Table C-1. Table C-2 lists UNIX-specific ports and cover services ranging from email to authentication and more. Table C-2. Table C-3 lists ports submitted by the network and software community to the IANA for formal registration into the port number list. Table C-3. Table C-4 is a listing of ports related to the Datagram Delivery Protocol (DDP) used on AppleTalk networks. Table C-4. Table C-5. Table C-6.
Docs As the starting point for the application, we use a Maven archetype called vaadin-archetype-application. Archetypes are project stubs that have some example code and a basic Maven build script. Start by choosing from the menu. Figure 4. If this is your first Vaadin app, creating a project might take a while, depending on the speed of your network, as Vaadin libraries and other dependencies are being downloaded. While the build is running, let us have a look at what the archetype created for you. The UI code (and the Servlet declaration) used by the application stub can be found in the MyUI.java file. To test your first Vaadin application, right-click on the project and choose . Figure 5. In the dialog, type Run in jetty to the Name input and jetty:run to the Goals input. Figure 6. Before clicking debug, to make sure debugging works properly, add your Java project to the source lookup path from the Source tab, as it is being done in Adding sources for debugging. Figure 7. Figure 8.
Beautiful Soup 4 Python Overview This article is an introduction to BeautifulSoup 4 in Python. If you want to know more I recommend you to read the official documentation found here. What is Beautiful Soup? Beautiful Soup is a Python library for pulling data out of HTML and XML files. BeautifulSoup 3 or 4? Beautiful Soup 3 has been replaced by Beautiful Soup 4. Installing Beautiful Soup If you run Debian or Ubuntu, you can install Beautiful Soup with the system package manager apt-get install python-bs4 Beautiful Soup 4 is published through PyPi, so if you can’t install it with the system packager, you can install it with easy_install or pip. easy_install beautifulsoup4 pip install beautifulsoup4 If you don’t have easy_install or pip installed, you can download the Beautiful Soup 4 source tarball and install it with setup.py. python setup.py install BeautifulSoup Usage Right after the installation you can start using BeautifulSoup. Filtering There are some different filters you can use with the search API. A string A list
16 Best Free Machine Learning Books in June 2016 - Hacker Lists The following is a list of free books on Machine Learning. A Brief Introduction To Neural Networks David Kriesel A Brief Introduction To Neural Networks provides a comprehensive overview of the subject of neural networks and is divided into 4 parts –Part I: From Biology to Formalization — Motivation, Philosophy, History and Realization of Neural Models,Part II: Supervised learning Network Paradigms, Part III: Unsupervised learning Network Paradigms and Part IV: Excursi, Appendices and Registers. A Course In Machine Learning (PDF) Hal Daumé III A Course In Machine Learning is designed to provide a gentle and pedagogically organized introduction to the field and provide a view of machine learning that focuses on ideas and models, not on math. According to the book: The audience of this book is anyone who knows differential calculus and discrete math, and can program reasonably well. A First Encounter With Machine Learning (PDF) Max Welling An Introduction To Statistical Learning David Barber D.