Formatted Export With Parquet logo

Formatted Export With Parquet

OrganizationPopular
OpenSenseNova
formatted-export-with-parquet

从多Sheet Excel文件中识别指定条件的记录,并将筛选结果以整行标红格式导出为Excel文件,适用于数据清洗、条件筛选与可视化标记场景。

Overview

PublisherOpenSenseNova
RepositorySenseNova-Skills
Skill nameformatted-export-with-parquet
Stars
5.6K
Forks
392
Bundled files
Instructions only
LicenseMIT
Links
  • 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 Formatted Export With Parquet AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

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.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

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-result-export/formatted-export .claude/skills/formatted-export-with-parquet
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Formatted Export With Parquet 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 Formatted Export With Parquet 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 Formatted Export With Parquet 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.

Formatted_Export

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

Skill Steps

Step1 对所有 sheet 进行扫描,通过模糊匹配定位目标列,筛选出符合条件(如空值或无效字符)的记录。

python
empty_target_rows = []
for sheet_name, sheet_df in all_sheets.items():
    target_col = None
    
    # 优先匹配目标列名(示例:包含特定关键字的列)
    for col in sheet_df.columns:
        if 'keyword1' in str(col).lower() or 'keyword2' in str(col).lower():
            target_col = col
            break
            
    if target_col is None:
        # 尝试次级推断逻辑
        for col in sheet_df.columns:
            if 'keyword3' in str(col) and ('keyword4' in str(col)):
                target_col = col
                break
                
    if target_col is None:
        continue
    
    # 数据清洗:筛选空值和无效字符(如空格、'nan')行
    mask = sheet_df[target_col].isna() | (sheet_df[target_col].astype(str).str.strip() == '') | (sheet_df[target_col].astype(str).str.strip() == 'nan')
    empty_rows = sheet_df[mask].copy()
    
    if len(empty_rows) > 0:
        empty_rows.insert(0, '来源Sheet', sheet_name)
        empty_target_rows.append(empty_rows)

# 合并结果
result_df = pd.concat(empty_target_rows, ignore_index=True) if empty_target_rows else pd.DataFrame()

Step2 将筛选出的记录导出为 Excel 文件,整行标红显示以便于视觉识别,并生成下载链接。

python
from openpyxl import load_workbook
from openpyxl.styles import PatternFill

output_path = "filtered_results_highlighted.xlsx"

if not result_df.empty:
    # 导出基础数据
    result_df.to_excel(output_path, index=False)

    # 加载工作簿进行格式化
    wb = load_workbook(output_path)
    ws = wb.active
    
    # 定义红色填充样式
    red_fill = PatternFill(start_color="FF0000", end_color="FF0000", fill_type="solid")

    # 遍历所有数据行并标红(跳过表头)
    for row in range(2, ws.max_row + 1):
        for col in range(1, ws.max_column + 1):
            ws.cell(row=row, column=col).fill = red_fill

    wb.save(output_path)
    print(f"结果文件已保存: {output_path}")
    print(f"下载链接: [点击下载标红结果文件]({output_path})")
else:
    print("未找到符合条件的记录,无需导出。")

Frequently asked questions

What does the Formatted Export With Parquet AI skill do?

从多Sheet Excel文件中识别指定条件的记录,并将筛选结果以整行标红格式导出为Excel文件,适用于数据清洗、条件筛选与可视化标记场景。

Why use Formatted Export With Parquet on TypingMind?

Because you install it once and use it with any model. Formatted Export With Parquet 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 Formatted Export With Parquet 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-result-export/formatted-export. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Formatted Export With Parquet?

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 Formatted Export With Parquet?

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

Is the Formatted Export With Parquet 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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