pandas-data-analysis 是做什麼的?
掌握使用 Pandas、NumPy 和 Matplotlib 進行資料操作、分析與視覺化的技能
掌握使用 Pandas、NumPy 和 Matplotlib 進行資料操作、分析與視覺化的技能
這項技能使您能夠熟練地利用 Python 資料科學生態系統中的核心函式庫——Pandas、NumPy 和 Matplotlib——來處理資料。它涵蓋了從資料載入、清理與轉換(Pandas),到高效的數值計算(NumPy),以及建立各式靜態、互動式圖表(Matplotlib)的完整流程。這項技能特別適合需要在命令列環境(如 Claude Code、Codex)或筆記本(如 Jupyter)中進行快速資料探索、特徵工程與結果呈現的開發者與資料分析師。通過這項技能,您可以自動化繁瑣的資料處理任務,並產生高品質的分析報告。技能本身透過標準的 Python 套件管理工具(pip)安裝相關函式庫,並遵循常見的 pandas/numpy/matplotlib 使用慣例,讓您可以無縫整合到現有的資料工作流程中。
npx skills add https://github.com/pluginagentmarketplace/custom-plugin-python/tree/main/skills/pandas-data-analysisInstalled? Explore more 研究與資料分析 skills: affaan-m/uspto-database, affaan-m/scholar-evaluation, affaan-m/literature-review · View all 6 →
掌握使用 Pandas、NumPy 和 Matplotlib 進行資料操作、分析與視覺化的技能
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.