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Bring data to life with SVG, Canvas and HTML. :bar_chart::chart_with_upwards_trend::tada:
Apache ECharts is a powerful, interactive charting and data visualization library for browser
The easy-to-use open source Business Intelligence and Embedded Analytics tool that lets everyone work with data :bar_chart:
✨ Innovative and open-source visualization application that transforms various data formats, such as JSON, YAML, XML and CSV into interactive graphs.
Make Your Company Data Driven. Connect to any data source, easily visualize, dashboard and share your data.
Database diagrams editor that allows you to visualize and design your DB with a single query.
Open-source IoT Platform - Device management, data collection, processing and visualization.
Interactive Data Visualization in the browser, from Python
The interactive graphing library for Python :sparkles:
Open-source JavaScript charting library behind Plotly and Dash
PyGWalker: Turn your dataframe into an interactive UI for visual analysis
Tool for shell commands execution, visualization and alerting. Configured with a simple YAML file.
WebGL2 powered visualization framework
Open3D: A Modern Library for 3D Data Processing
📊 The concise and progressive visualization grammar.
♾ A Graph Visualization Framework in JavaScript.
A visualization grammar.
Meshery, the cloud native manager
Graph theory (network) library for visualisation and analysis
Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python, ML, visualization and exploration of big tabular data at a billion rows per second 🚀
tensorboard for pytorch (and chainer, mxnet, numpy, ...)
Multi-Dimensional charting built to work natively with crossfilter rendered with d3.js
Portfolio analytics for quants, written in Python
Gephi - The Open Graph Viz Platform
Create beautiful JavaScript charts with one line of Ruby
curl statistics made simple
Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.
Automate code & data workflows with interactive Elixir notebooks
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.
🍊 :bar_chart: :bulb: Orange: Interactive data analysis