Individual skill

numeric-format-normalization

对 Excel 数据进行数值格式标准化与清洗,支持大规模数据的 Parquet 转换流程,并完成关键指标的合计核对与结果文件导出。

skills/sn-da-excel-workflow/capability/excel-data-cleaning/numeric-format-normalization/SKILL.md

Read pinned source

Source commit 004a2426fa092097d65ac9233ca0bcb2be793f57

What was checked

Matches the observed repository HEAD
Yes
Scanner rules are current
Yes
Repository scan complete
No
Skill scan complete
No
Observed behavior
Network or broad shell
Last checked
Nov 9, 2026

These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.

Install this skill

Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.

An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.

Repository context

Repository stars (not skill ratings)
6,068
Repository last updated
Nov 3, 2026
License
MIT

Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.

Files and excerpt

File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.

Browse files
Read excerpt

## Skill Steps

> This sub-skill covers one capability of the Excel workflow. For reading/counting/Parquet optimization, see the parent workflow SKILL.md.

Step1 对目标列进行数据清洗(去除空值、标准化数值格式),计算合计值,并与指定汇总 Sheet 中的合计行进行精确核对。
```python
target_col = '目标数值列'  # 示例:'建筑面积'
summary_sheet_name = 'Summary' # 示例汇总Sheet名
summary_item_col = '项目'
summary_value_col = '数值'

# 数据清洗:去除空值、强制转换为数值格式
df_cleaned = df_processed.dropna(subset=[target_col]).copy()
df_cleaned[target_col] = pd.to_numeric(df_cleaned[target_col], errors='coerce')
Back to top