O que data-analysis-jupyter faz?
Orientacão especializada para análise de dados, visualização e desenvolvimento de Jupyter Notebook com pandas, matplotlib, seaborn e numpy.
Orientação especializada para análise de dados, visualização e desenvolvimento de Jupyter Notebook com pandas, matplotlib, seaborn e numpy.
Esta habilidade fornece orientação especializada para análise de dados, visualização e desenvolvimento de Jupyter Notebook, utilizando bibliotecas populares do ecossistema Python como pandas, matplotlib, seaborn e numpy. É particularmente útil para engenheiros de software, cientistas de dados e desenvolvedores de agentes de IA que precisam automatizar ou realizar tarefas de análise exploratória, limpeza de dados, criação de gráficos e modelagem estatística diretamente em notebooks. A habilidade suporta plataformas que executam agentes de IA com acesso a ambientes Python, como Claude Code, Cursor ou Codex, e funciona interpretando comandos de alto nível para gerar código Python otimizado e documentado. Com base em sua documentação (SKILL.md), ela atua como um assistente focado em boas práticas, oferecendo soluções prontas para problemas comuns de análise de dados e garantindo que o código seja executável e eficiente.
npx skills add https://github.com/mindrally/skills/tree/main/skills/data-analysis-jupyterInstalled? Explore more Pesquisa e Análise de Dados skills: affaan-m/uspto-database, affaan-m/scholar-evaluation, affaan-m/literature-review · View all 6 →
Orientacão especializada para análise de dados, visualização e desenvolvimento de Jupyter Notebook com pandas, matplotlib, seaborn e numpy.
This repo contains 20 individual skills — each has its own dedicated page.
Implement web accessibility (a11y) best practices following WCAG guidelines to create inclusive, accessible user interfaces.
Expert guidelines for Chrome extension development with Manifest V3, covering security, performance, and best practices. Use when building browser extensions, creating popup UIs, implementing content scripts, working with Chrome APIs, managing extension permissions, or publishing to Chrome Web Store.
Expert guidance for computer vision development using OpenCV, PyTorch, and modern deep learning techniques for image and video processing.
Expert guidance for deep learning, transformers, diffusion models, and LLM development with PyTorch, Transformers, Diffusers, and Gradio.
Expert in Expo React Native TypeScript mobile development with best practices
Expert in FastAPI Python development with best practices for APIs and async operations
Expert guidelines for building performant animations with Framer Motion/Motion library in React applications
HTMX development guidelines for building dynamic web applications with minimal JavaScript using HTML attributes.
Guidelines for implementing JWT authentication with security best practices for token creation, validation, and storage
Machine learning development with JAX, functional programming patterns, and high-performance computing.
MySQL development best practices for schema design, query optimization, and database administration
Expert in TypeScript, Node.js, Next.js App Router, React, Shadcn UI, Radix UI and Tailwind
Full-stack Next.js 14 development with TypeScript, TailwindCSS, and Supabase for building production-ready web applications.
Expert guidance for Odoo ERP development including Python ORM, XML views, and module architecture
Expert guidance for browser automation using Puppeteer with best practices for web scraping, testing, screenshot capture, and JavaScript execution in headless Chrome.
Redis development best practices for caching, data structures, and high-performance key-value operations
Expert guidance for building web scrapers and crawlers using the Scrapy Python framework with best practices for spider development, data extraction, and pipeline management.
SCSS/Sassy CSS best practices and coding guidelines for maintainable, scalable stylesheets
Guidelines for developing with TypeORM, a full-featured ORM for TypeScript and JavaScript supporting multiple databases
Expert in web scraping and data extraction with Python tools
USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.
Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.
Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.
The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
Agent skill repository discovered by 10x-chat research.
Review backend code for quality, security, maintainability, and best practices based on established checklist rules. Use when the user requests a review, analysis, or improvement of backend files (e.g., `.py`) under the `api/` directory. Do NOT use for frontend files (e.g., `.tsx`, `.ts`, `.js`). Supports pending-change review, code snippets review, and file-focused review.