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scikit-learn: machine learning in Python
⭐AI-driven public opinion & trend monitor with multi-platform aggregation, RSS, and smart alerts.🎯 告别信息过载，你的 AI 舆情监控助手与热点筛选工具！聚合多平台热点 + RSS 订阅，支持关键词精准筛选。AI 智能筛选新闻 + AI 翻译 + AI 分析简报直推手机，也支持接入 MCP 架构，赋能 AI 自然语言对话分析、情感洞察与趋势预测等。支持 Docker ，数据本地/云端自持。集成微信/飞书/钉钉/Telegram/邮件/ntfy/bark/slack 等渠道智能推送。
Turn any AI agent into an AI Scientist. The #1 Agent Skills library for science, used by 250,000+ scientists worldwide. 177 ready-to-use validated skills plus 100+ scientific databases covering biology, chemistry, medicine, and drug discovery. Compatible with Cursor, Claude Code, Codex, Pi, Antigravity, and the open Agent Skills standard.
Streamlit — A faster way to build and share data apps.
Chat with your database or your datalake (SQL, CSV, parquet). PandasAI makes data analysis conversational using LLMs and RAG.
1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
Open Machine Learning Course
A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning
Visualize and compare datasets, target values and associations, with one line of code.
What's in your data? Extract schema, statistics and entities from datasets
:truck: Agile Data Preparation Workflows made easy with Pandas, Dask, cuDF, Dask-cuDF, Vaex and PySpark
NFStream: a Flexible Network Data Analysis Framework.
Visualize large time series data with plotly.py
cell detection in calcium imaging recordings
High-assurance AI data visualization IDE & analytics workbench. Natural language to charts with local ground-truth table verification.
CLI utility and Python module for analyzing log files and other data.
The power of Chart.js with Python
Turn CSV, Excel, and read-only databases into verified, editable business reports.
Quanfima (Quantitative Analysis of Fibrous Materials)
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.