Open Source TypeScript Data Visualization Software
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TypeScript Data Visualization Software
View 448 business solutionsBrowse free open source TypeScript Data Visualization Software and projects below. Use the toggles on the left to filter open source TypeScript Data Visualization Software by OS, license, language, programming language, and project status.
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Superset
Apache Superset is a data visualization and data exploration platform
Apache Superset is a modern data exploration and visualization platform. Superset is fast, lightweight, intuitive, and loaded with options that make it easy for users of all skill sets to explore and visualize their data, from simple line charts to highly detailed geospatial charts. Quickly and easily integrate and explore your data, using either our simple no-code viz builder or state-of-the-art SQL IDE. Superset can connect to any SQL-based data source through SQLAlchemy, including modern cloud-native databases and engines at a petabyte-scale. Superset is lightweight and highly scalable, leveraging the power of your existing data infrastructure without requiring yet another ingestion layer. Superset ships with a wide array of beautiful visualizations. Our visualization plug-in architecture makes it easy to build custom visualizations that drop directly into Superset. -
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tabix
Tabix.io UI
Open source simple business intelligence application and sql editor tool for Clickhouse. Auto-completion of fields, dictionaries and functions. Tips on fields and functions in Russian and English. Reformatting queries / autoformat. Minimizes brackets and subqueries. Setting the autocompletion / enableLiveAutocompletion. Backlight brackets. The list of functions is loaded based on the capabilities of the server. Displays which query is running. Display the number of tables at the database. The icon of the table depends on its engine. List of fields in the table and inserting the field when clicking in the editor. DB selection via double click in the tree, pop-up window about selection. Search in the tree of objects, filtering the tree. Rebuilding the list of databases / tables after the query is executed. Table with information about completed requests at the end of the list / Requests in the tab are logged for performance comparison. -
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Neuroglancer
WebGL-based viewer for volumetric data
Neuroglancer is a WebGL-based visualization tool designed for exploring large-scale volumetric and neuroimaging datasets directly in the browser. It allows users to interactively view arbitrary 2D and 3D cross-sections of volumetric data alongside 3D meshes and skeleton models, enabling precise examination of neural structures and biological imaging results. Its multi-pane interface synchronizes multiple orthogonal views with a central 3D viewport, making it ideal for analyzing complex brain imaging data such as connectomics datasets. Neuroglancer operates entirely client-side, fetching data over HTTP in a variety of supported formats including Neuroglancer precomputed, N5, Zarr, and NIfTI, among others. The viewer is built with a multi-threaded architecture, separating rendering and data processing to ensure smooth performance even with massive datasets. Extensively used in neuroscience research, Neuroglancer supports integration with tools. -
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luma.gl
High-performance Toolkit for WebGL-based data visualization
luma.gl is a GPU toolkit for the Web-focused primarily on data visualization use cases. luma.gl aims to provide support for GPU programmers that need to work directly with shaders and want a low abstraction API that remains conceptually close to the WebGPU and WebGL APIs. Unlike other common WebGL APIs, the developer can choose to use the parts of luma.gl that support their use case and leave the others behind. While generic enough to be used for general 3D rendering, luma.gl's mandate is primarily to support GPU needs of data visualization frameworks in the vis.gl suite. -
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F2
An elegant, interactive and flexible charting library for mobile
F2 is an out-of-the-box visualization engine focused on the mobile terminal, oriented to conventional statistical charts, perfectly supporting the H5 environment and compatible with multiple environments (Node, applet), complete graphics grammar theory, to meet your various visualization needs , professional mobile design guidelines to bring you the best mobile graphics experience. Best practices for moving side charts around design, performance and heterogeneous environments. Based on the grammar of graphics, Flexible construction of various charts (50+), complete components, covering various scenarios. Plugin, graphics, animation and interaction can be flexibly expanded and freely used. Covering business scenarios such as Ant membership, Alipay monthly bills, personal total assets, etc., it helps you understand your consumption data faster and better through visualization. -
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md2googleslides
Generate Google Slides from markdown
Generate Google Slides from markdown & HTML. Run from the command line or embed in another application. This project was developed as an example of how to use the Slides API. While it does not yet produce stunningly beautiful decks, you are encouraged to use this tool for quickly prototyping presentations. The first time the command is run you will be prompted for authorization. OAuth token credentials are stored locally in a file named ~/.md2googleslides/credentials.json. Each time you will run the above comment, new slide deck will be generated. In order to work on exactly the same deck, just get the ID of the already generated slides. md2googleslides does not edit or control any theme-related options. Just set a base theme you want on Google Slides directly. Even if you will use, append option for deck reuse, theme will be not changed. Images can be placed on slides using image tags. Multiple images can be included. -
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G2
Interactive data-driven visualization grammar for statistical charts
G2 is a highly interactive data-driven visualization grammar for statistical charts. with a high level of usability and scalability. It provides a set of grammar, and takes users beyond a limited set of charts to an almost unlimited world of graphical forms. With G2, you can describe the visual appearance and interactive behavior of visualization just by one statement, and generate web-based views using Canvas or SVG. We have summarized a series of story design templates from lots of real data visualization cases so that users can use them directly. Any chart can be drawn flexibly based on graphical grammar to meet your unlimited creativity. A large number of product practices, providing a graphics engine, complete graphical grammar, and professional design specifications.Powerful interactive grammar to help visual analysis and make charts vivid. -
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React Chart.js
React components for Chart.js, the most popular charting library
React components for Chart.js, the most popular charting library. With v4, this library introduces a number of breaking changes. In order to improve performance, offer new features, and improve maintainability, it was necessary to break backwards compatibility, but we aimed to do so only when worth the benefit. You will find that any event which causes the chart to re-render, such as hover tooltips, etc., will cause the first dataset to be copied over to other datasets, causing your lines and bars to merge together. This is because to track changes in the dataset series, the library needs a key to be specified. If none is found, it can't tell the difference between the datasets while updating. Specify a different property to be used as a key by passing a datasetIdKey prop to your chart component. -
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visx
Visualization components
visx a collection of expressive, low-level visualization primitives for React. At Airbnb, we made it a goal to unify our visualization stack across the company and in the process, we created a new project that brings together the power of D3 with the joy of React. visx is split into multiple packages. Start small and use only what you need. Bring your own state management, animation library, or CSS-in-JS solution. Odds are good your React app already has an opinion on how animation, theming, or styling is done. visx is careful not to add another one and integrates with all of them. As you start using visualization primitives, you’ll end up building your own charting library that’s optimized for your use case. You’re in control. And most importantly, it’s just React. If you know React, you can make visualizations. It’s all the same standard APIs and familiar patterns. visx should feel at home in any React codebase. -
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Davinci
Davinci is a DVsaaS (Data Visualization as a Service) Platform
Davinci is oriented towards product managers, business people, data engineers, data analysts, data scientists, etc. It aims to provide a one-stop data visualization solution, which could be both independently used as a public cloud/private cloud and integrated into third-party systems as plugin. A simple configuration on Davinci UI can meet multiple visualization requirements. It also supports other visualization features like advanced interaction, industry analysis, pattern searching, social intelligence, etc. Sharing and intelligence capability means users could share their dashboards with others, which stimulates them to improve the visualization ability both in aesthetic perception and technical skills. In the field of data visualization, Davinci attaches great importance to basic interaction ability and various chart options; meanwhile, it lays more stress on integration and customization capability as well as sharing and intelligence capability. -
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Graffle
Simple GraphQL Client for JavaScript
Graffle is a simple, minimal, and extensible GraphQL client for JavaScript, designed to provide type-safe queries and run in various environments. -
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D-Tale
Visualizer for pandas data structures
D-Tale is the combination of a Flask backend and a React front-end to bring you an easy way to view & analyze Pandas data structures. It integrates seamlessly with ipython notebooks & python/ipython terminals. Currently, this tool supports such Pandas objects as DataFrame, Series, MultiIndex, DatetimeIndex & RangeIndex. D-Tale was the product of a SAS to Python conversion. What was originally a perl script wrapper on top of SAS's insight function is now a lightweight web client on top of Pandas data structures. To help guard against users loading the same data to D-Tale multiple times and thus eating up precious memory, we have a loose check for duplicate input data. If you are running ipython<=5.0 then you also have the ability to adjust the size of your output cell for the most recent instance displayed. JupyterHub has an extension that allows to proxy port for user, JupyterHub Server Proxy. -
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DataStation Community Edition
App to easily query, script, and visualize data from every database
DataStation is an open-source data IDE for developers. It allows you to easily build graphs and tables with data pulled from SQL databases, logging databases, metrics databases, HTTP servers, and all kinds of text and binary files. Need to join or munge data? Write embedded scripts as needed in languages like Python, JavaScript, R or SQL. All in one application. Build reports with graphs, charts and tables. Script against data. Cross-platform: Windows, macOS, and Linux. Easily fetch your data, wherever it is: 18 SQL and non-SQL databases, files, HTTP server. Over 20 supported databases out of the box including: PostgreSQL, MySQL, MariaDB, SQLite, SQL Server, Oracle, ClickHouse, Influx 1 (InfluxQL), Influx 2 (Flux), Prometheus, Elasticsearch, AWS Athena, Google BigQuery, Snowflake, Cassandra, Scylla, TimescaleDB, YugabyteDB, CockroachDB, CrateDB, QuestDB, and Airtable. -
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Foxglove Studio
Robotics visualization and debugging
Foxglove Studio is an open-source visualization and debugging tool for robotics. Use customizable layouts to arrange interactive visualizations and quickly understand what your robot is doing. Use Foxglove Studio's rich interactive visualizations to analyze live connections and pre-recorded data. Experience the world as your robot does. Visualize images and point clouds, overlay bounding boxes, add classification labels and planned movements, and drill down into your data with plots or raw message views. Upload recordings to your private data lake for easy storage, searching, and analysis. Stream recorded data directly into Foxglove Studio to get insights into your robots' behavior. We're long-time fans and beneficiaries of open source software. Join our community on Github and Slack to contribute bug reports, feature requests, or pull requests. -
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RevoGrid
Powerful virtual data grid smartsheet with advanced customization
Support Millions of cells and thousands of columns easy and efficiently for fast data rendering. Easy to use. For large organizations managing massive datasets. Performance and scalability to handle even the most complex data tables. Rapid prototyping with intuitive and extendable codebase. Agility to build robust data-driven applications in no time. Quickly build elegant and efficient data grids. Lightweight yet powerful architecture lets you easily scale as your needs grow. -
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Vue Clock Visualizer
Simple clock component written in Vue
Simple clock component is written in Vue. -
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billboard.js
Re-usable, easy interface JavaScript chart library based on D3.js
billboard.js is a re-usable, easy interface JavaScript chart library, based on D3.js. The name "billboard" comes from the famous "billboard chart" which everybody knows. billboard.js provides the easiest way to create a 'chart' instantly. Chart generation is super easy. With extensive options, you can create a chart instantly! Yes, billboard.js works on D3 v4+; what everybody was waiting for! All of the code was written as an ESM(ES Module) with ES6+ syntax. Combine hundreds of options to satisfy your needs. Checkout the examples to see in action! Play with the diverse options generated on the fly! If you want to use 'billboard.js' without installation, load files directly from one of the CDN providers. -
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BizCharts
Powerful data visualization library based on G2 and React
BizCharts is Alibaba's general charting component library, dedicated to creating efficient, professional and convenient data visualization solutions in the middle and backend of enterprises. Based on the React charting library packaged by G2 and G2Plot, it has experienced three years of baptism in Alibaba's complex business scenarios. In terms of convenience, ease of use, and richness, it satisfies the business implementation of conventional charts and highly customized charts. After years of accumulation and continuous polishing, BizCharts 4.0 has been newly upgraded; in addition to having a flexible graphics syntax, it has added an interactive syntax and a better animation experience. At the same time, it enhances the React coding ability, and the writing is freer. The built-in encapsulation of responsive chart g2-plot works out of the box and complements the atomic capabilities of BizCharts to keep moving forward on the visual path of flexibility and ease of use. -
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Data Formulator
Create rich visualizations with AI
To create rich visualizations, data analysts often need to iterate back and forth among data processing and chart specification to achieve their goals. To achieve this, analysts need not only proficiency in data transformation and visualization tools but also efforts to manage the branching history consisting of many different versions of data and charts. Recent LLM-powered AI systems have greatly improved visualization authoring experiences, for example by mitigating manual data transformation barriers via LLMs' code generation ability. However, these systems do not work well for iterative visualization authoring, because they often require analysts to provide, in a single turn, a text-only prompt that fully describes the complex visualization task to be performed, which is unrealistic to both users and models in many cases. In this paper, we present Data Formulator 2, an LLM-powered visualization system to address these challenges. -
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Facets
Visualizations for machine learning datasets
The power of machine learning comes from its ability to learn patterns from large amounts of data. Understanding your data is critical to building a powerful machine learning system. Facets contains two robust visualizations to aid in understanding and analyzing machine learning datasets. Get a sense of the shape of each feature of your dataset using Facets Overview, or explore individual observations using Facets Dive. Explore Facets Overview and Facets Dive on the UCI Census Income dataset, used for predicting whether an individual’s income exceeds $50K/yr based on their census data. The census data contains features such as age, education level, and occupation for each individual. Overview gives users a quick understanding of the distribution of values across the features of their dataset(s). Uncover several uncommon and common issues such as unexpected feature values, missing feature values for a large number of observation, training/serving skew and train/test/validation set skew. -
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Hedgehog Lab
Run, compile and execute JavaScript for Scientific Computing
Hedgehog Lab is an open-source scientific computation tool in the browser. Before the development, Pleases make sure you are already installed and enabled the yarn. Once cloned, switch to the dev branch and navigate to the folder by typing cd hedgehog-lab and then running the provided commands. On each run the program compiles and it takes time. Please wait until it shows "Compiled successfully!" and instructions about with which IP:PORT to connect. -
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HiPlot
HiPlot makes understanding high dimensional data easy
HiPlot is an interactive visualization toolkit for exploring high-dimensional experiments, especially those produced during hyperparameter search or ablation studies. Its core view is a parallel-coordinates plot that lets you brush, filter, and highlight runs to spot trade-offs, correlations, and Pareto fronts at a glance. You can load results from simple CSV/JSON logs or programmatically push “experiments” with typed fields, metrics, and tags. The UI supports dynamic filtering, color mapping, and tooltip details so you can iteratively narrow to the most promising configurations. Because it renders as self-contained HTML, you can embed the visualization in notebooks, export it, or serve it as a lightweight web app for teammates. HiPlot also offers summary statistics, correlation hints, and outlier highlighting to surface patterns that aren’t obvious from raw tables. -
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MTTK Open BI
A user-friendly lightweight BI tool.
A user-friendly lightweight BI tool. It is a set of plugins of MTTK Lowcode Engine, so the user manual and develop manual are combined together with MTTK Low Code Engine. Code repository: https://github.com/jamie-mttk/mttk-lowcode-designer Online demo available at http://139.129.210.30:8825 (First visit may be slow) Username: admin Password: 123456 Lightweight No data processing engine offered, all the data processing depends on the target Databse Server. Easy to use For example ,to build an echart need to provide many many configurtaions/options, such as title location, grid position,etc. To simplified the usage ,only the important options should be configured by user with default setting, other options are set by BI system automatically. -
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SGraph
Create charts by retrieving data from Stata on-the-fly
SGraph is a web application that interacts with Stata for creating graphs. It is a demo application that demostrates how to exploit SWire for creating web applications that communicate with Stata. SGraph is an open source project and you can download the code from the project web site web site or try the app on-line here: http://sgraph-with-swire.sourceforge.net/ The source project is hosted in GitHub: https://github.com/lomagno/sgraph -
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SandDance
Visually explore, understand, and present your data
By using easy-to-understand views, SandDance helps you find insights about your data, which in turn help you tell stories supported by data, build cases based on evidence, test hypotheses, dig deeper into surface explanations, support decisions for purchases, or relate data into a wider, real world context. SandDance uses unit visualizations, which apply a one-to-one mapping between rows in your database and marks on the screen. Smooth animated transitions between views help you to maintain context as you interact with your data. This new version of SandDance has been rebuilt from scratch with the goal of being modular, extensible, and embeddable into your custom applications. We are open and driven by the community through contributions, feature requests, and discussion. SandDance was created by the Microsoft Research VIDA Group which explores novel technologies for visualization and immersive data analytics.
