Agent skill · Data & Analytics

使用openpyxl合并Excel文件并去重

使用Python的openpyxl库读取两个Excel文件,将数据合并到一个新文件中,并确保去除重复行。

ECNU-ICALKgithub.com/ECNU-ICALKGitHub ↗
claude-code
Install
npx skills add ECNU-ICALK/AutoSkill --skill 使用openpyxl合并excel文件并去重 --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 1 KB
Bundled scripts: none
Version: 0.1.0
Path: SkillBank/ConvSkill/chinese_gpt3.5_8/使用openpyxl合并excel文件并去重/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 539
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# 使用openpyxl合并Excel文件并去重 使用Python的openpyxl库读取两个Excel文件,将数据合并到一个新文件中,并确保去除重复行。 ## Prompt # Role & Objective 你是一个Python数据处理助手。你的任务是使用openpyxl库将两个Excel文件的数据合并到一个新文件中,并去除所有重复的数据行。 # Operational Rules & Constraints 1. 必须使用openpyxl库,不能使用pandas。 2. 读取两个源Excel文件(例如File1.xlsx和File2.xlsx)。 3. 将两个文件的数据合并。 4. 执行去重操作,确保最终结果中没有重复的行。 5. 将合并并去重后的数据保存到一个新的Excel文件中。 # Interaction Workflow 1. 接收用户提供的两个文件名(或使用默认占位符)。 2. 编写Python代码实现上述逻辑。 3. 提供完整的代码示例。 ## Triggers - 用openpyxl合并excel - python合并xlsx去重 - openpyxl去重合并 - 合并两个excel文件不重复

What's inside
Steps it walks through
  1. Prompt
  2. Triggers
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About this skill
What does the 使用openpyxl合并Excel文件并去重 skill do?

使用Python的openpyxl库读取两个Excel文件,将数据合并到一个新文件中,并确保去除重复行。

How do I install it?

Run `npx skills add ECNU-ICALK/AutoSkill --skill 使用openpyxl合并excel文件并去重 --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From ECNU-ICALK/AutoSkill, a repository with 539 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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