Materials for GWU DNSC 6279 and DNSC 6290.
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Python histogram library - histograms as updateable, fully semantic objects with visualization tools. [P]ython [HYST]ograms.
孩子生日想办麦当劳派对？全国281城3664家门店哪里能办，26款体验活动一图查完。基于官方MCP只读采集+可视化。
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
身材管控期也想吃麦当劳？这个专家会帮你根据每日消耗搭配麦麦套餐。基于 SP 矩阵理论，打通麦当劳官方 MCP Server 的营养选型与点餐闭环（35 个官方工具 · 14 个 REST 接口 · 零第三方前端依赖）。
Magic to display dynamic call graphs of Python function calls
AI-powered platform for OSINT intelligence analysis. Features archive discovery with hypothesis-driven investigation, GLiNER entity extraction, Mapbox geospatial visualization, network analysis, and document processing. Built with FastAPI, Next.js, Weaviate, and DSPy.
Go's answer to pandas + scikit-learn: a batteries-included data analysis library with dataframes, statistics, machine learning, quant, and GPU acceleration. Run Python with seamless two-way variable sharing, or explore data straight from the Insyra CLI.
MCP server for spatial transcriptomics analysis through natural language interfaces.
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.
Simple, modern ETH backtesting project using Pandas/Numpy: data prep, MA signals, portfolio simulation, and result visualization.