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lqiuee

excel application

by lqiuee · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install operation
Description
Compare two columns in an Excel or CSV file to find differences, unique values, and common values. This skill should be used when the user wants to upload an...
README (SKILL.md)

\r \r

Excel Column Compare\r

\r

Overview\r

\r Compare two specified columns in an Excel/CSV file to identify differences and commonalities between them. The skill produces a formatted Excel report showing values unique to each column, values shared by both, and a summary of the comparison.\r \r

When to Use\r

\r

  • User asks to compare two columns in an Excel file\r
  • User wants to find values that exist in one column but not another\r
  • User needs to identify differences or overlaps between two sets of data in a spreadsheet\r
  • User says things like "对比这两列的不同", "比较Excel两列数据", "find differences between columns", "compare column A and B"\r \r

Workflow\r

\r

Step 1: Understand the User's Request\r

\r Identify from the user's message:\r

  • The Excel/CSV file to compare (file path)\r
  • The two columns to compare (by column name, letter like A/B/C, or index)\r
  • Optional: specific sheet name, comparison mode, or output path\r \r If the user does not specify column identifiers, read the file first to display available columns and ask the user which two to compare.\r \r

Step 2: Preview the File (if needed)\r

\r If the column identifiers are unclear, read the file to show available columns:\r \r

import pandas as pd\r
df = pd.read_excel(input_file, nrows=5)\r
print(df.columns.tolist())\r
print(df.head())\r
```\r
\r
### Step 3: Run the Comparison Script\r
\r
Execute the bundled script `scripts/compare_columns.py`:\r
\r
```bash\r
python \x3Cskill_path>/scripts/compare_columns.py \x3Cinput_file> \x3Ccolumn_a> \x3Ccolumn_b> [--sheet \x3Csheet>] [--output \x3Coutput>] [--mode \x3Cmode>]\r
```\r
\r
**Parameters:**\r
- `input_file`: Path to the Excel (.xlsx, .xls) or CSV file\r
- `column_a`: Column name (e.g., "姓名"), letter (e.g., A, B), or 0-based index\r
- `column_b`: Column name, letter, or 0-based index for the second column\r
- `--sheet`: Sheet name or index (default: first sheet)\r
- `--output`: Output file path (default: `\x3Cinput>_comparison_result.xlsx`)\r
- `--mode`: Comparison mode:\r
  - `full` (default): Show all categories — only in A, only in B, common\r
  - `diff`: Show only differences (not in both)\r
  - `unique_a`: Show only items unique to column A\r
  - `unique_b`: Show only items unique to column B\r
  - `common`: Show only items common to both columns\r
\r
**Examples:**\r
\r
```bash\r
# Compare by column names\r
python scripts/compare_columns.py data.xlsx "姓名" "名字"\r
\r
# Compare by column letters\r
python scripts/compare_columns.py data.xlsx A B\r
\r
# Compare specific sheet, only show differences\r
python scripts/compare_columns.py data.xlsx "Email" "邮箱" --sheet "Sheet2" --mode diff\r
\r
# Specify output path\r
python scripts/compare_columns.py data.xlsx C D --output result.xlsx\r
```\r
\r
### Step 4: Present the Results\r
\r
After the script runs:\r
1. Display the console summary (unique counts for each category)\r
2. Open the generated output Excel file for the user to review\r
3. Summarize key findings: how many values are unique to each column, how many are shared\r
\r
## Output Format\r
\r
The output Excel file contains the following sheets:\r
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| Sheet | Content |\r
|-------|---------|\r
| Summary | Overview with column names, counts, and statistics |\r
| Only in [Column A] | Values found only in the first column, with row numbers |\r
| Only in [Column B] | Values found only in the second column, with row numbers |\r
| Common Values | Values present in both columns |\r
\r
Sheets are color-coded: blue for Column A, orange for Column B, green for common values, purple for summary.\r
\r
## Troubleshooting\r
\r
- **Column not found**: The script prints available column names. Suggest the correct column identifier to the user.\r
- **Same column selected**: The script will error if both references resolve to the same column. Ask the user to choose two different columns.\r
- **Large files**: For files with many rows, the comparison still works efficiently using set operations. Row number display is limited to first 10 occurrences per unique value.\r
- **Missing dependencies**: The script auto-installs `pandas` and `openpyxl` if not present.\r
\r
## Resources\r
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### scripts/\r
\r
- `compare_columns.py` — Main comparison script that reads an Excel/CSV file, compares two specified columns, and generates a formatted Excel report with the comparison results.\r
Usage Guidance
Install only if you are comfortable with the skill reading the spreadsheet files you provide, creating a local Excel report, and potentially running pip to install pandas and openpyxl if they are missing. In locked-down or enterprise environments, preinstall reviewed dependencies or run it in an isolated environment.
Capability Assessment
Purpose & Capability
The artifacts consistently describe a spreadsheet column-comparison utility that reads a user-specified Excel or CSV file, compares two selected columns, and writes a local Excel report.
Instruction Scope
The skill instructs the agent to preview user-provided spreadsheet data when column choices are unclear and to run the bundled comparison script; this is aligned with the stated purpose.
Install Mechanism
The script auto-installs hardcoded dependencies, pandas and openpyxl, if imports fail. This is disclosed in troubleshooting and supports the skill's function, but it is not opt-in and uses unpinned packages.
Credentials
Local file reads and report writes are proportionate to spreadsheet comparison. The runtime pip install can cause network access and modify the Python environment, so managed environments should treat it carefully.
Persistence & Privilege
No persistence, credential access, background workers, broad local indexing, destructive operations, or unrelated privilege use were found in the artifacts.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install operation
  3. After installation, invoke the skill by name or use /operation
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Excel column comparison skill initial release. - Enables comparison between any two columns in an Excel or CSV file. - Generates a formatted Excel report highlighting unique and common values for each column. - Accepts columns by name, letter, or index, with optional sheet and output path parameters. - Offers multiple comparison modes: full, diff, unique_a, unique_b, and common. - Provides summary statistics and categorized result sheets in the output file. - Includes troubleshooting guidance for column selection, large files, and dependencies.
Metadata
Slug operation
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is excel application?

Compare two columns in an Excel or CSV file to find differences, unique values, and common values. This skill should be used when the user wants to upload an... It is an AI Agent Skill for Claude Code / OpenClaw, with 47 downloads so far.

How do I install excel application?

Run "/install operation" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is excel application free?

Yes, excel application is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does excel application support?

excel application is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created excel application?

It is built and maintained by lqiuee (@lqiuee); the current version is v1.0.0.

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