excel-conditional-filtering-optimization

by OpenSenseNova5.8k

根据多维数值条件筛选 Excel 数据并导出结果，支持大规模数据的自动性能优化处理。

Install

The skill file stays in the publisher's repository.

Paste the copied command in a terminal. It installs this SKILL.md into that agent.

npx skills add OpenSenseNova/SenseNova-Skills --skill range-filtering -a cursor -y

Download skill skills/sn-da-excel-workflow/capability/excel-data-filtering/range-filtering/SKILL.md on GitHub

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Questions

How do I install excel-conditional-filtering-optimization?: Download skills/sn-da-excel-workflow/capability/excel-data-filtering/range-filtering/SKILL.md from the publisher, or copy the path and open the repository. PlugMCP lists the skill and does not host the file.
Where does excel-conditional-filtering-optimization live?: The publisher keeps it at https://github.com/OpenSenseNova/SenseNova-Skills.
Which agents can use excel-conditional-filtering-optimization?: Claude, Cursor, and Codex can read a SKILL.md you add from the publisher's repository.

name: excel-conditional-filtering-optimization description: "根据多维数值条件筛选 Excel 数据并导出结果，支持大规模数据的自动性能优化处理。"

Excel_Conditional_Filtering_Optimization

Note: This sub-skill covers one step of the Excel analysis workflow. For the full pipeline (file reading, row counting, large-file optimization, export), see the parent workflow SKILL.md.

Step1 读取 Excel 文件中所有工作表的数据，统计各表行数并汇总，用于评估数据规模。

import pandas as pd

file_path = "input_data.xlsx"

# 读取所有 sheet，统计行数
xls = pd.ExcelFile(file_path)
print("Sheet names:", xls.sheet_names)

total_rows = 0
sheet_details = []
for sheet in xls.sheet_names:
    df_temp = pd.read_excel(file_path, sheet_name=sheet)
    row_count = len(df_temp)
    sheet_details.append({"sheet": sheet, "rows": row_count})
    total_rows += row_count

print(f"Sheet details: {sheet_details}")
print(f"Total rows across all sheets: {total_rows}")