data-analysislisted

# Data Analysis — Full Data Analysis Pipeline An agent team collaborates to perform the full data lifecycle: exploration → cleaning → analysis → visualization → reporting. ## Execution Mode **Agent Team** — 5 members communicate directly via SendMessage and cross-validate. ## Agent Composition | Agent | File | Role | Type | |-------|------|------|------| | explorer | `.claude/agents/explorer.md` | Exploratory analysis, data profiling | general-purpose | | cleaner | `.claude/agents/cleaner.md` | Data cleaning, transformation pipeline | general-purpose | | analyst | `.claude/agents/analyst.md` | Statistical analysis, insight derivation | general-purpose | | visualizer | `.claude/agents/visualizer.md` | Chart design, visualization code generation | general-purpose | | reporter | `.claude/agents/reporter.md` | Final report writing, quality verification | general-purpose | ## Workflow ### Phase 1: Preparation (Orchestrator performs directly) 1. Extract from user input: - **Data Source**: File path, format (CSV/Excel/JSON/DB), size - **Analysis Purpose**: Business questions, hypotheses, expected results - **Constraints** (optional): Time, specific analysis techniques, reporting audience - **Domain Information** (optional): Industry, variable meanings, business context 2. Create `_workspace/` directory and `_workspace/scripts/` subdirectory 3. Organize input and save to `_workspace/00_input.md` 4. Copy data files to `_workspace/data/` 5. If existing files are