Dynamic Large File Parquet Analysis

OrganizationPopular

OpenSenseNova

dynamic-large-file-parquet-analysis

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。

Overview

Publisher	OpenSenseNova
Repository	`SenseNova-Skills`
Skill name	`dynamic-large-file-parquet-analysis`
Stars	5.6K
Forks	392
Bundled files	Instructions only
License	MIT
Links	Skill source Repository

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by OpenSenseNova on GitHub. Read the source before you install it.

Installation

Install the Dynamic Large File Parquet Analysis AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/OpenSenseNova/SenseNova-Skills/tree/main/skills/sn-da-excel-workflow/capability/excel-table-styling/table-theme-styling

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/OpenSenseNova/SenseNova-Skills.git /tmp/SenseNova-Skills
mkdir -p .claude/skills
cp -r /tmp/SenseNova-Skills/skills/sn-da-excel-workflow/capability/excel-table-styling/table-theme-styling .claude/skills/dynamic-large-file-parquet-analysis

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Dynamic Large File Parquet Analysis in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Dynamic Large File Parquet Analysis on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Dynamic Large File Parquet Analysis is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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）。

python
# 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）。

python
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。

python
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}")

Frequently asked questions

What does the Dynamic Large File Parquet Analysis AI skill do?

Why use Dynamic Large File Parquet Analysis on TypingMind?

Because you install it once and use it with any model. Dynamic Large File Parquet Analysis is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Dynamic Large File Parquet Analysis in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/OpenSenseNova/SenseNova-Skills/tree/main/skills/sn-da-excel-workflow/capability/excel-table-styling/table-theme-styling. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Dynamic Large File Parquet Analysis?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Dynamic Large File Parquet Analysis?

As many as you like. As long as a model supports skills, you can use Dynamic Large File Parquet Analysis with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Dynamic Large File Parquet Analysis AI skill free?

Yes. It is published on GitHub by OpenSenseNova under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Skill Steps

Frequently asked questions

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