6 مستودعات
Tools for transforming raw datasets into interactive charts with customizable axes, filters, and visual mappings.
Distinct from API Data Visualizers: Shortlist candidates focus on narrow visual styling or specific line charts rather than the general transformation of raw data into interactive visuals.
Explore 6 awesome GitHub repositories matching data & databases · Custom Data Visualizations. Refine with filters or upvote what's useful.
TensorFlow.js is a JavaScript machine learning library used for training and deploying models in web browsers and server-side environments. It functions as a browser-based model trainer, a WebAssembly inference engine, and a WebGPU accelerated tensor library for low-level linear algebra. The project also includes a model converter to transform Python-based models into optimized formats for JavaScript execution. The library distinguishes itself through a pluggable backend architecture that allows mathematical operations to be executed via CPU, WebGL, or WebGPU. It supports the conversion of Py
Integrates external charting libraries and custom views to extend model analysis visualizations.
This project is a collection of responsive CSS Grid dashboard templates and a data visualization UI kit. It provides a set of HTML layouts designed for building analytics interfaces and monitoring views for KPIs and business metrics that adapt to different screen sizes. The toolkit is library-agnostic, allowing the connection of static HTML templates to any external data source or third-party charting library without requiring custom adapter code. It uses a template-driven approach to separate the visual structure of the dashboard from the underlying data. The capabilities cover the assembly
Transforms raw datasets into interactive charts using customizable visual mappings.
Apache Zeppelin is a web-based notebook platform for interactive data analytics that supports executing code in over 20 languages within a single notebook. It provides a plugin-based interpreter architecture that allows the notebook to be extended with new languages and data sources, and includes a JDBC connector abstraction for connecting to any JDBC-compliant database. The platform also features session-isolated interpreter contexts, enabling separate interpreter instances per notebook or user with support for dependency injection and user impersonation. The platform distinguishes itself th
Builds custom visualizations and display widgets to render data as tables, graphs, or interactive elements.
Visual Insights is an automated exploratory data analysis platform and causal inference tool designed to discover patterns and cause-and-effect relationships within datasets. It functions as an interactive data visualization library using a grammar-of-graphics approach to generate multi-dimensional charts and dashboards. The project distinguishes itself through a natural language interface that translates plain-text questions into data answers and visualizations via a language model. It provides a specialized framework for causal discovery and inference, allowing users to identify variable li
Generates tailored, interactive charts via a drag-and-drop interface to explore discovered data patterns.
Chartbrew is a self-hosted business intelligence platform and data visualization engine designed to transform raw data from SQL databases and external API endpoints into interactive charts and dashboards. It serves as a tool for building analytics dashboards that monitor business metrics and KPIs through a privately hosted environment. The platform distinguishes itself with an embedded analytics workflow, allowing users to generate secure, time-limited shared links and iframes to display private charts on external websites. It also provides programmatic chart generation via API and integrates
Transforms raw data from SQL databases and APIs into interactive charts with custom axes and filters.
This project is an interactive, web-based notebook environment designed for distributed data science and large-scale computing. It serves as a development tool for executing code and performing data analysis specifically within the Apache Spark framework, providing a browser-based interface that combines code execution with reactive data visualization. The platform distinguishes itself through its deep integration with distributed infrastructure, allowing users to manage cluster resources, configure runtime dependencies, and isolate execution processes for individual notebooks. It supports co
Enables the definition of custom interactive data widgets by mapping data structures to rendering functions.