Dynamic Large File Parquet Analysis Agent Skill

by OpenSenseNova

动态统计Excel总行数，当数据量过大（≥10000行）时自动转换为Parquet格式加速读取，并对指定目标列进行条件筛选、分类汇总与结果导出，适用于超大体积Excel文件的快速读取与统计分析。

574 tokens

context cost

the whole folder, loaded on every use

files

instructions only

copies elsewhere

how many repositories repackaged it

4851

stars on the repo

on the repository, not the skill itself

Install

one command, takes just this skill from the repository

npx skills add https://github.com/OpenSenseNova/SenseNova-Skills --skill dynamic-large-file-parquet-analysis

The instruction itself

1 sections, as written by the author

Skill Steps

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

Step1 动态读取数据（Parquet加速或常规读取）。

# 若已加载 sn-da-large-file-analysis 技能，将 Excel 文件转换为 Parquet 格式加速读取
if 'da_large_file_analysis' in globals():
    # 假设 sn-da-large-file-analysis 转换后生成了 parquet 文件
    parquet_path = 'auto_converted_data.parquet'
    df = pd.read_parquet(parquet_path)
    print("已使用 Parquet 格式加速读取大文件。")
else:
    df = pd.read_excel(file_path, sheet_name='Sheet1', header=0)
    print("文件较小，使用常规方式读取。")

Step2 对目标列进行条件筛选，并按分组列进行分类汇总（包含占比与总计）。

target_col = '目标列名'  # 示例：'危险级别'
group_col = '分组列名'   # 示例：'分项工程'
target_value = 'TARGET_VALUE'  # 示例：'★★★★'

# 筛选包含特定值的记录
df_filtered = df[df[target_col].astype(str).str.contains(target_value, na=False)].copy()

# 分类汇总
result = df_filtered[group_col].value_counts()
result_df = pd.DataFrame({
    group_col: result.index,
    '数量': result.values
})

# 计算占比并添加总计行
if not result_df.empty:
    result_df['占比'] = (result_df['数量'] / result_df['数量'].sum()).apply(lambda x: f"{x:.2%}")
    total_row = pd.DataFrame({
        group_col: ['总计'], 
        '数量': [result_df['数量'].sum()], 
        '占比': ['100.00%']
    })
    result_df = pd.concat([result_df, total_row], ignore_index=True)

Step3 导出汇总结果并生成下载链接。

output_path = 'filtered_summary_output.xlsx'

# 将分类汇总结果保存为表格文件
result_df.to_excel(output_path, index=False)

# 输出下载链接供用户获取
print("数据处理与分类汇总完成。")
print(f"下载链接: {output_path}")

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How to use it

Copy the folder

Take opensensenova/dynamic-large-file-parquet-analysis from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

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