Pandas for Customer Support Analytics

关于

This skill equips Claude with specialized expertise in pandas for deep-dive customer support analytics, covering everything from ticket management to SLA tracking. It provides optimized patterns for DataFrame operations, time series analysis, and multi-level aggregations tailored specifically for support operations. Whether you need to build production-ready ETL pipelines from PostgreSQL or generate detailed agent performance reports, this skill ensures data accuracy and performance through proven implementation patterns and automated cleaning routines.

主要功能

• 17 GitHub stars
• Comprehensive agent performance and CSAT metric calculation
• Advanced data cleaning and validation for support datasets
• Time series resampling for ticket volume trend reporting
• SLA compliance and response time analysis patterns
• PostgreSQL database integration via SQLAlchemy and ETL logic

使用场景

• Calculating and reporting on weekly SLA compliance rates across support teams
• Analyzing customer satisfaction trends relative to response times and ticket priority
• Building automated data pipelines to transform raw ticket logs into performance dashboards