Open Source JavaScript Data Visualization Software for Mac
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JavaScript Data Visualization Software for Mac
View 92 business solutionsBrowse free open source JavaScript Data Visualization Software for Mac and projects below. Use the toggles on the left to filter open source JavaScript Data Visualization Software for Mac by OS, license, language, programming language, and project status.
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D3.js
A JavaScript library for visualizing data using web standards
D3.js (or D3 for Data-Driven Documents) is a JavaScript library that allows you to produce dynamic, interactive data visualizations in web browsers. With D3 you can bring data to life using SVG, Canvas and HTML. Powerful visualization and interaction techniques plus a data-driven approach to DOM manipulation means D3.js gives you greater design freedom and control over the final result. -
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plotly.js
JavaScript charting library behind Plotly and Dash
Plotly JavaScript Open Source Graphing Library. Built on top of d3.js and stack.gl, Plotly.js is a high-level, declarative charting library. plotly.js ships with over 40 chart types, including 3D charts, statistical graphs, and SVG maps. plotly.js is free and open source and you can view the source, report issues or contribute on GitHub. For plotly.js to build with Webpack you will need to install ify-loader@v1.1.0+ and add it to your webpack.config.json. This adds Browserify transform compatibility to Webpack which is necessary for some plotly.js dependencies. When users hover over a figure generated with plotly.js, a modebar appears in the top-right of the figure. This presents users with several options for interacting with the figure. When users hover over a figure generated with plotly.js, a modebar appears in the top-right of the figure. This presents users with several options for interacting with the figure. -
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SQLPad
Web-based SQL editor run in your own private cloud
A web app for writing and running SQL queries and visualizing the results. Supports Postgres, MySQL, SQL Server, ClickHouse, Crate, Vertica, Trino, Presto, SAP HANA, Cassandra, Snowflake, Google BigQuery, SQLite, TiDB, and many more via ODBC. The docker image runs on port 3000 and uses /var/lib/sqlpad for the embedded database directory. latest tag is continuously built from latest commit in repo. Only use that if you want to live on the edge, otherwise use specific version tags to ensure stability. See docker-examples directory for example docker-compose setup with SQL Server. -
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Cytoscape.js
Graph theory library for visualization and analysis
A fully featured graph library written in pure JS. Permissive open source license (MIT) for the core Cytoscape.js library and all first-party extensions. Used in commercial projects and open-source projects in production. Designed for users first, for both frontfacing app usecases and developer usecases. Highly optimized. Compatible with All modern browsers. Legacy browsers with ES5 and canvas support. ES5 and canvas support are required, and feature detection is used for optional performance enhancements. Browsers circa 2012 support ES5 fully: IE10, Chrome 23, Firefox 21, Safari 6 (caniuse). Browsers with partial but sufficient ES5 support also work, such as IE9 and Firefox 4. The documentation and examples are not optimized for old browsers, although the library itself is. Some demos may not work in old browsers in order to keep the demo code simple. -
MongoDB Atlas | Run databases anywhereMongoDB Atlas allows you to build and run modern applications across 125+ cloud regions, spanning AWS, Azure, and Google Cloud. Its multi-cloud clusters enable seamless data distribution and automated failover between cloud providers, ensuring high availability and flexibility without added complexity.
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ECharts
A powerful, interactive charting and visualization library for browser
ECharts is a free and open source charting and visualization library that gives you an easy way to add interactive, intuitive, custom charts to your commercial products, projects, presentations and more. It offers a rich set of features that includes rendering ability for ten-million-level data, Wechart and Powerpoint support, multi-dimension data analysis, and more. It also has a number of extensions for various applications. ECharts is written in pure JavaScript, and is based on zrender, a new and lightweight canvas library. -
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GoJS
JavaScript diagramming library for interactive flowcharts & org charts
Build interactive flowcharts or flow diagrams. Let your users build, modify, and save diagrams with JSON model output. Visualize state charts and other behavior diagrams. Create diagrams with live updates to monitor state, or interactive diagrams for planning. GoJS allows considerable customization of links and nodes to build all kinds of diagrams. Visualize flow, or connect pipes. Create genogram and medical diagrams, or editable family trees with collapsible levels. Create classic org charts for viewing or editing. Automatic layouts make different visualization options easy. Dynamically add ports and custom link routing. Use data-bindings to save and load routes within the Model JSON. Use groups as containers and subgraphs, with group members bound by their own rules and layouts. Model industrial processes, workflows, SCADA diagrams and more. -
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Apexcharts.js
Interactive JavaScript Charts built on SVG
A modern JavaScript charting library that allows you to build interactive data visualizations with simple API and 100+ ready-to-use samples. Packed with the features that you expect, ApexCharts includes over a dozen chart types that deliver beautiful, responsive visualizations in your apps and dashboards. ApexCharts is an MIT-licensed open-source project that can be used in commercial and non-commercial projects. You can create a combination of different charts, sync them and give your desired look with unlimited possibilities. Below is an example of synchronized charts with github style. Zoom, Pan, Scroll through data. Make selections and load other charts using those selections. An example showing some interactivity. Another approach to Drill down charts where one selection updates the data of other charts. Annotations allows you to write custom text on specific values or on axes values. Valuable to expand the visual appeal of your chart and make it more informative. -
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Chokidar
Minimal and efficient cross-platform file watching library
Chokidar is a solution for all the users of Node.js fs.watch who are tired of it not reporting filenames on MacOS and events at all when using editors like Sublime on MacOS. Node.js fs.watch often reports events twice, emits most changes as rename, and it does not provide an easy way to recursively watch file trees nor supports recursive watching on Linux. Same as with Node.js fs.watchFile. Therefore, Chokidar resolves these problems. Initially made for Brunch (an ultra-swift web app build tool), it is now used in Microsoft's Visual Studio Code, gulp, karma, PM2, browserify, webpack, BrowserSync, and many others. It has proven itself in production environments. Chokidar does still rely on the Node.js core fs module, but when using fs.watch and fs.watchFile for watching, it normalizes the events it receives, often checking for truth by getting file stats and/or dir contents. -
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heatmap.js
JavaScript Library for HTML5 canvas based heatmaps
heatmap.js is a lightweight, easy to use JavaScript library to help you visualize your three dimensional data! Use it to add new value to your project, build a business based on it, study and visualize user behaviour, or why not build something completely crazy/awesome? Whether you want to have an aggregated overview of your users behaviour, or look at thousands of events distributed on a map, heatmap.js has all your heatmap visualization needs covered! Because it is the most advanced heat map visualization library on the web. It has a light footprint (~3kB gzip) and with the new 2.0 release heatmap.js just got faster and better. With only a few lines of code you can create your own interactive web heatmap. heatmap.js' API is all documented, also prioritized, so you can start developing right away! Heatmap.js is not a user behaviour tracking script. It simply creates dynamic heatmaps based on the data you feed it. -
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textures.js
SVG patterns for data visualization
Textures.js is a JavaScript library for creating SVG patterns. Made on top of d3.js, it is designed for data visualization. Import textures.js from NPM. You can also use textures.js in your HTML page with a <script> tag by downloading textures.js to a local folder or by using the Unpkg CDN network. Textures.js can be used alongside d3. -
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deck.gl
WebGL2 powered visualization framework
deck.gl is designed to simplify high-performance, WebGL-based visualization of large data sets. Users can quickly get impressive visual results with minimal effort by composing existing layers, or leveraging deck.gl's extensible architecture to address customer needs. deck.gl maps data (usually an array of JSON objects) into a stack of visual layers - e.g. icons, polygons, texts; and look at them with views: e.g. map, first-person, orthographic. deck.gl handles a number of challenges out of the box. Deck.gl is designed to be highly customizable. All layers come with flexible APIs to allow programmatic control of each aspect of the rendering. All core classes such are easily extendable by the users to address custom use cases. deck.gl is part of vis.gl, an OpenJS Foundation project. Read the contribution guidelines if you are interested in contributing. -
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This Java application serves to transform W3C XML Schema instances into interactive diagrams in SVG format. The diagram represents structure of XML files and provides information about individual items – elements and attributes.
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DICOM Image Reader
A minimal Medical application to read and view DICOM (dcm) image file
Dicom Image Reader is opensource medical image viewer built with JavaScript, HTML5, NodeJS and Electron framework. It can load data in DICOM format (single image dcm) and provides standard tools for its manipulation such as contrast, zoom, drag, possibility to draw regions on top of the image and imaging filters such as threshold and sharpening. It is based DWV JavaScript opensource library. =============== Requirements: - Processor: Intel Pentium 4 processor or later that's SSE2 capable - RAM: 512 MB - Hard Disk: 1500 MB - Video Card: nVidia, ATI and Intel Shader Model 2 and Shader Model 3 video cards with 512 megabytes of RAM minimum - Supported OS: Windows 10, Windows 8, Windows 8.1, Windows 7 =============== Alternative software for Windows: Available on Ecwid - https://goo.gl/twBcAq =============== Android App: https://goo.gl/i4NX9K -------------- Chrome app Release Pro: https://goo.gl/p456N5 -
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Britecharts
Composable Charting Library based on reusable D3.js components
Britecharts is a client-side reusable Charting Library based on D3.js v5 that offers easy and intuitive use of charts and components that can be composed together to create amazing visualizations. Britecharts components have been written in ES2016 with a Test Driven methodology, so they are fully tested, and we are committed to keeping them that way. The typical use of Britecharts involves creating a chart using its simple API, then rendering it on a container that has previously had data applied to it. All the components expose some common API methods like width, height, and margin. Additionally, each chart or component can expose specific methods you can find in the documentation. Britecharts components are distributed in UMD modules, each one exposing a D3.js component written with the Reusable API pattern. To use any of the Britecharts modules, you will need to require the chart in your JS file using AMD/CommonJS modules or adding a script tag with the src pointing to the file. -
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Compiere MFG+SCM Manufacturing Extended System (MES). Include Shop Floor Control, Supply chain management, Quality management, modbus interface, iReport barcode extension etc. Support batch and on demand manufacturing. Works alone or connected to ERP.
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ExplorViz
Live Trace Visualization for Large Software Landscapes
ExplorViz is a web-based software visualization for large software landscapes. It features two different perspectives: the landscape-level perspective and the application-level perspective. The former visualizes the systems, nodes, and application existing in the software landscape. The latter one utilizes the city metaphor to visualize the entities and communication happening in one application. For installation instructions and downloads see http://www.explorviz.net -
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G6
A Graph Visualization Framework in JavaScript
G6 is graph visualization engine with simplicity and convenience. Based on the ability to customize, it provides a set of elegant graph visualization solutions and helps developers to build up applications for graph visualization, graph analysis, and graph editor. G6 is a complete graph visualization engine, which focuses on relational data. According to practical business scenarios, we found the top solutions. Well-designed simple, flexible, and extendable interfaces will satisfy your infinite originality. A social network is an important scenario in graph visualization. The relationships become complicated with the development of social networks. Graph visualization and analysis do well in these complex cases. -
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Gio.js
A declarative 3D globe data visualization library built with Three.js
Gio.js is an open source library for web 3D globe data visualization built with Three.js. What makes Gio.js different is that it is simple to use Gio.js to customize a 3D data visualization model in a declarative way, add your own data, and integrate it into your own modern web application. Gio.js is an open source library for web 3D globe data visualization built with Three.js. What makes Gio.js different is that it is simple to use Gio.js to customize a 3D data visualization model in a declarative way, add your own data, and integrate it into your own modern web application. This library is inspired by the Arms Trade Visualization project developed by Michael Chang and presented during Google Ideas INFO 2012. See original post. With Gio.js, it is easy to reproduce this fantastic data visualization model, and integrate it into web applications. -
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Illustrated Algorithms
Interactive algorithm visualizations
Inspired by Grokking Algorithms and python-execution-trace, this project aims to reveal the mechanics behind algorithms via interactive visualizations of their execution. Visual representations of variables and operations augment the control flow, alongside actual source code. You can fast forward and rewind the execution to closely observe how an algorithm works. The same code that is displayed next to the illustration is also decorated using babel-plugin-trace-execution and executed to record the context at every step. Literally the same source file. Going back and forth between function execution (and call stack when algorithm uses recursion) is effortless. So is pausing and resuming. This project uses styled-jsx, but takes the idea of CSS-in-JS even further. Sizing, positioning and transition offsets are computed by JS, all before elements hit the DOM. -
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JVanish is a minimalistic 3D engine based solely on standard web technologies: Javascript, XHTML, CSS and SOAP. Its goal is to find a generic and useful XHTML-based 3D widget set, while staying mostly lightweight in an AJAX web environment.
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LostGrid
LostGrid is a powerful grid system built in PostCSS
Lost Grid is a powerful grid system built in PostCSS that works with any preprocessor and even vanilla CSS. LostGrid makes use of calc() to create stunning grids based on fractions you define without having to pass a lot of options. LostGrid relies on calc() to create the grid. Thus, LostGrid is limited to browsers that support calc(). The great thing is that calc() is widely supported in all current browsers and the LostGrid usage of calc() is supported as far back as IE9+. If using LostGrid in flexbox mode browser support is limited to IE 10+. To create a basic horizontal grid, just insert some elements into any containing element like so and pass a fraction to the `lost-column` property. To unset (or remove) a column rule, possibly at a larger breakpoint, use `lost-column: none;` -
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Marid
Free data acquisition and data visualization cross-platform software
Marid is a cross-platform data acquisition and visualization software intended to build complex and hierarchical data acquisition systems. The base concepts of its architecture include: * Graphical deploy configuration builders * Powerful Groovy scripting language * Embedded database ( H2 , HSQLDB) to store data * Cross-platform design (write once, run anywhere) * Embedded GUI-configurable binary/ascii device protocol parser/generator * Deploy manager to deploy firmwares to remote controllers/servers via secure channel * Embedded web-sever * Dynamically linked plugins available from Nexus Repository * Remote monitoring tools * Modular Marid IDE to manage them all -
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The Monitoring Infrastructure (MIS) is a toolkit for software developers. It provides a generic solution for monitoring events in applications and for graphical representation of those events in a Web Browser using SVG.
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Semiotic
A data visualization framework combining React & D3
Semiotic is a data visualization framework combining React & D3. It provides three types of frames XYFrame, OrdinalFrame, NetworkFrame, to deploy a wide variety of charts. XY data i.e. line charts and scatterplots. Categorical data i.e. bar charts, violin plots, parallel coordinates. Topological and network data i.e. flow diagrams, network visualization, and hierarchical views. A guide for creating a line chart, timeseries, difference line, and line percents using XYFrame along with hover behavior, responsive dimensions, and styling. XYFrame takes lines as an object or an array of objects. Each object represents a line. Every object needs a coordinates property with the array of points for that line. The points will be rendered in the order of that array. You can use a key other than coordinates by changing the lineDataAccessor props. -
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ipytracer
Algorithm Visualizer for IPython/Jupyter Notebook
Algorithm Visualizer for IPython/Jupyter Notebook. If you use the display(TracerObject) code from where you want to see, you can use it without any special modification.
