large-file-conditional-formatting

by OpenSenseNova5.8k

根据Excel总行数自动切换Parquet加速读取，计算特定维度的时间序列平均值，并使用openpyxl输出带有条件格式（如低于均值标绿）和自定义样式的分析报告。

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 threshold-cell-coloring -a cursor -y

Download skill skills/sn-da-excel-workflow/capability/excel-cell-coloring/threshold-cell-coloring/SKILL.md on GitHub

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Questions

How do I install large-file-conditional-formatting?: Download skills/sn-da-excel-workflow/capability/excel-cell-coloring/threshold-cell-coloring/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 large-file-conditional-formatting live?: The publisher keeps it at https://github.com/OpenSenseNova/SenseNova-Skills.
Which agents can use large-file-conditional-formatting?: Claude, Cursor, and Codex can read a SKILL.md you add from the publisher's repository.

name: large-file-conditional-formatting description: "根据Excel总行数自动切换Parquet加速读取，计算特定维度的时间序列平均值，并使用openpyxl输出带有条件格式（如低于均值标绿）和自定义样式的分析报告。"

Skill Steps

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 读取文件并统计所有 sheet 的行数，汇总后打印总行数，用于判断是否需要大文件加速。

import pandas as pd
import openpyxl

file_path = "input_data.xlsx"

# 获取所有sheet名称
wb = openpyxl.load_workbook(file_path, read_only=True)
sheet_names = wb.sheetnames
print("Sheet列表:", sheet_names)
print("Sheet数量:", len(sheet_names))

# 统计每个sheet的行数
total_rows = 0
for name in sheet_names:
    df_temp = pd.read_excel(file_path, sheet_name=name, header=None)
    rows = len(df_temp)
    total_rows += rows
    print(f"Sheet '{name}': {rows} 行")

print(f"\n总行数 = {total_rows}")

from openpyxl import Workbook from openpyxl.styles import PatternFill, Font, Alignment, Border, Side wb = Workbook() ws = wb.active ws.title = "指标分析报告" # 定义样式 green_fill = PatternFill(start_color="92D050", end_color="92D050", fill_type="solid") header_fill = PatternFill(start_color="4472C4", end_color="4472C4", fill_type="solid") header_font = Font(bold=True, color="FFFFFF") thin_border = Border( left=Side(style='thin'), right=Side(style='thin'), top=Side(style='thin'), bottom=Side(style='thin') ) # 设置主标题 ws.merge_cells('A1:D1') ws['A1'] = f"目标实体指标分析 - 平均值: {avg_value:.2f}" ws['A1'].font = Font(bold=True, size=14) ws['A1'].alignment = Alignment(horizontal='center') # 设置表头 headers = ['时间维度', '指标数值', '与平均值比较', '是否标绿'] for col, header in enumerate(headers, 1): cell = ws.cell(row=3, column=col, value=header) cell.fill = header_fill cell.font = header_font cell.alignment = Alignment(horizontal='center') cell.border = thin_border # 写入数据并应用条件格式 for i, row_data in result_df.iterrows(): row_num = i + 4 time_label = row_data['时间维度'] value = row_data['指标数值'] below_avg = row_data['是否低于平均值'] # 写入各列数据 ws.cell(row=row_num, column=1, value=time_label).alignment = Alignment(horizontal='center') ws.cell(row=row_num, column=2, value=value).alignment = Alignment(horizontal='center') diff = value - avg_value ws.cell(row=row_num, column=3, value=f"{diff:+.2f}").alignment = Alignment(horizontal='center') ws.cell(row=row_num, column=4, value="是" if below_avg else "否").alignment = Alignment(horizontal='center') # 添加边框并根据条件标绿整行 for col in range(1, 5): cell = ws.cell(row=row_num, column=col) cell.border = thin_border if below_avg: cell.fill = green_fill # 调整列宽 ws.column_dimensions['A'].width = 15 ws.column_dimensions['B'].width = 20 ws.column_dimensions['C'].width = 18 ws.column_dimensions['D'].width = 12 output_path = "output_report.xlsx" wb.save(output_path) print(f"分析报告已保存至: {output_path}")