data-exploration-visualization
数据探索可视化技能
技能概述
数据探索可视化技能是一个基于《数据分析咖哥十话》第2课理论的自动化EDA工具包，提供从数据加载到专业分析报告生成的完整解决方案。该技能集成了最先进的数据探索、可视化和机器学习技术，帮助用户快速深入理解数据特征和规律。
核心功能
🔍 智能数据探索
- 自动数据诊断: 检测数据质量问题、异常值和缺失值模式
- 统计描述分析: 生成全面的统计摘要和分布特征
- 相关性分析: 识别特征间关系和依赖模式
- 数据质量报告: 专业级数据质量评估和建议
More from liangdabiao/claude-data-analysis-ultra-main
content-analysis
Analyze text content using both traditional NLP and LLM-enhanced methods. Extract sentiment, topics, keywords, and insights from various content types including social media posts, articles, reviews, and video content. Use when working with text analysis, sentiment detection, topic modeling, or content optimization.
62funnel-analysis
Analyze user conversion funnels, calculate step-by-step conversion rates, create interactive visualizations, and identify optimization opportunities. Use when working with multi-step user journey data, conversion analysis, or when user mentions funnels, conversion rates, or user flow analysis.
59rfm-customer-segmentation
Perform RFM (Recency, Frequency, Monetary) customer segmentation analysis on e-commerce data. Use when you need to analyze customer value, identify VIP customers, or create marketing segments. Automatically cleans data, calculates RFM metrics, applies K-means clustering, and generates visualization reports with Chinese language support.
43retention-analysis
Analyze user retention and churn using survival analysis, cohort analysis, and machine learning. Calculate retention rates, build survival curves, predict churn risk, and generate retention optimization strategies. Use when working with user subscription data, membership information, or when user mentions retention, churn, survival analysis, or customer lifetime value.
31ab-testing-analyzer
全面的AB测试分析工具，支持实验设计、统计检验、用户分群分析和可视化报告生成。用于分析产品改版、营销活动、功能优化等AB测试结果，提供统计显著性检验和深度洞察。
25recommender-system
智能推荐系统分析工具，提供多种推荐算法实现、评估框架和可视化分析。使用时需要用户行为数据、商品信息或评分数据，支持协同过滤、矩阵分解等推荐算法，生成个性化推荐结果和评估报告。
24