top-value-coloring

by OpenSenseNova5.8k

根据数据规模动态选择处理策略，对多表数据进行合并、统计筛选，并利用 openpyxl 实现关键指标的自动化样式高亮与格式化导出。

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 top-value-coloring -a cursor -y

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

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Questions

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

name: top-value-coloring description: "根据数据规模动态选择处理策略，对多表数据进行合并、统计筛选，并利用 openpyxl 实现关键指标的自动化样式高亮与格式化导出。"

Step1 提取并合并多个 Sheet 中的关键维度数据，进行数据清洗、类型转换及 Top-N 筛选。

# 示例：合并两个 Sheet 的数据
# 读取 Sheet1 并清洗
df1 = pd.read_excel(file_path, sheet_name='Sheet1', header=None)
# 假设 group_col 在第0列，value_col 在第2列
data1 = df1.iloc[20:, [0, 2]].copy()
data1.columns = ['group_col', 'value_col_1']
data1['value_col_1'] = pd.to_numeric(data1['value_col_1'], errors='coerce')
data1['group_col'] = data1['group_col'].ffill() # 处理合并单元格产生的缺失

# 读取 Sheet2 并清洗
df2 = pd.read_excel(file_path, sheet_name='Sheet2', header=None)
data2 = df2.iloc[5:, [0, 1]].copy()
data2.columns = ['value_col_2', 'value_col_3']

# 合并数据
merged_df = pd.concat([data1.reset_index(drop=True), data2.reset_index(drop=True)], axis=1)
merged_df = merged_df.dropna(subset=['value_col_1'])

# 筛选关键指标前五的数据
top_results = merged_df.nlargest(5, 'value_col_1').copy()

# 占位示例：修正特定缺失值
# top_results.loc[top_results['group_col'].isna(), 'group_col'] = 'Default_Value'

from openpyxl import Workbook from openpyxl.styles import Font, PatternFill, Alignment, Border, Side output_path = 'analysis_report.xlsx' # 创建工作簿 wb = Workbook() ws = wb.active ws.title = 'Analysis_Results' # 定义样式 header_fill = PatternFill(start_color='4472C4', end_color='4472C4', fill_type='solid') header_font = Font(bold=True, color='FFFFFF', size=12) red_font = Font(color='FF0000', bold=True) # 用于高亮异常或关键值 green_fill = PatternFill(start_color='C6EFCE', end_color='C6EFCE', fill_type='solid') # 用于高亮最大值 thin_border = Border(left=Side(style='thin'), right=Side(style='thin'), top=Side(style='thin'), bottom=Side(style='thin')) center_align = Alignment(horizontal='center', vertical='center') # 写入表头 headers = ['Rank'] + list(top_results.columns) for col, header in enumerate(headers, 1): cell = ws.cell(row=1, column=col, value=header) cell.font = header_font cell.fill = header_fill cell.alignment = center_align cell.border = thin_border # 写入数据并应用样式 for idx, (_, row) in enumerate(top_results.iterrows(), 2): # 写入排名 ws.cell(row=idx, column=1, value=idx-1).border = thin_border # 写入各列数据 for col_idx, value in enumerate(row, 2): cell = ws.cell(row=idx, column=col_idx, value=value) cell.border = thin_border # 逻辑高亮示例：对特定列（如第4列）应用红色字体 if col_idx == 4: cell.font = red_font # 逻辑高亮示例：对超过阈值的值应用绿色填充 # if isinstance(value, (int, float)) and value > threshold_val: # cell.fill = green_fill # 自动调整列宽 column_widths = {'A': 8, 'B': 30, 'C': 15, 'D': 15, 'E': 18} for col, width in column_widths.items(): ws.column_dimensions[col].width = width # 设置数字格式 for row in range(2, ws.max_row + 1): ws.cell(row=row, column=3).number_format = '#,##0' ws.cell(row=row, column=4).number_format = '#,##0.00' wb.save(output_path) print(f"Formatted file saved to: {output_path}")