Apache Superset is a Data Visualization and Data Exploration Platform
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Streamlit — A faster way to build and share data apps.
Data Apps & Dashboards for Python. No JavaScript Required.
Chat with your database or your datalake (SQL, CSV, parquet). PandasAI makes data analysis conversational using LLMs and RAG.
matplotlib: plotting with Python
A reactive notebook for Python — run reproducible experiments, query with SQL, execute as a script, deploy as an app, and version with git. Stored as pure Python. All in a modern, AI-native editor.
Turns Data and AI algorithms into production-ready web applications in no time.
Impress your boss and turn a Jupyter notebook into a beautiful, shareable web app — no callbacks, no frontend, no rewrite.
Vizro is a low-code toolkit for building high-quality data visualization apps.
Visualize and compare datasets, target values and associations, with one line of code.
No-code in the front, Python in the back. An open-source framework for creating data apps.
Visualize large time series data with plotly.py
AI drew your research figure. Tavotto makes it publication-ready: edit matplotlib and AI-generated figures on a canvas, lay out multi-panel pages in mm, check journal rules before export. Scripts stay untouched.
Main yt repository
Engine for AI/ML/Data tracking, visualization, explainability, drift detection, and dashboards for Polyaxon.
High-assurance AI data visualization IDE & analytics workbench. Natural language to charts with local ground-truth table verification.
The power of Chart.js with Python
基于麦当劳官方 MCP 的对话式 AI Skill，支持餐品推荐、门店比价、优惠查询、营养计算和探索记录，并通过 Python 生成体素风格分享图片。
High performance, editable, stylable datagrids in jupyter and jupyterlab
Turn CSV, Excel, and read-only databases into verified, editable business reports.
Modern, interactive charts for Jupyter notebooks with Apache ECharts
A lightweight Python package for teaching computational methods through art history. Extract and analyze artist-specific works from WikiArt with built-in visualizations. Designed for digital humanities and computational design courses. Features genre/style analysis, matplotlib integration, and pedagogical clarity over algorithmic complexity.