# Inset

> 诊断并处理缺失值（missing value 缺失值处理）

- Skill: `zafer-liu/inset` (Agent Skill)
- Install (CLI): `npx skillmds add zafer-liu/inset`
- Raw SKILL.md: https://api.skillmd.com/api/skills/zafer-liu/inset/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: Zafer-Liu (https://skillmd.com/u/zafer-liu)
- Updated: 2026-09-09
- Page: https://skillmd.com/skills/zafer-liu/inset

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# 缺失值处理

先量化字段和行级缺失，判断缺失机制及业务含义，再选择删除、常数、统计量或分组插补。修改前说明影响，保留可追溯结果，并在处理后验证缺失率和分布变化。

## Tool routing

1. Use `get_schema` to identify tables, nullable fields, and candidate columns.
2. Use `profile_data` to quantify missingness before any modification.
3. Use `clean_data` with the appropriate missing-value operation only when the user intent is clear.
4. Use `query_data` after cleaning to verify row counts, remaining nulls, and distribution changes.

## Implementation reference

- Tool entries: `agent/tools/business/data.py::_tool_profile_data`, `agent/tools/business/data.py::_tool_clean_data`
- Profiling implementation: `Function/Clean/data_profile.py`
- Missing-value implementation: `Function/Clean/missing_handler.py`