excel-data-import

What This Skill Does

The excel-data-import skill is a powerful, configuration-driven utility designed to automate the ingestion, transformation, and consolidation of spreadsheet data. Unlike simple copy-paste tasks, this tool handles complex data manipulation tasks through YAML-defined workflows. It enables users to map source headers to specific target templates, perform schema validation, clean data using built-in transformations, and even execute incremental updates. It is specifically engineered to handle the common pain points of spreadsheet management, such as multi-layer merged headers, inconsistent encodings in CSV files, and the need to process hundreds of files stored in a directory simultaneously. By centralizing logic in a YAML configuration file, users can ensure consistent, reproducible data pipelines that are easy to audit and version control.

Installation

To integrate this skill into your OpenClaw environment, execute the following command in your terminal:

clawhub install openclaw/skills/skills/aqbjqtd/excel-data-import

Additionally, ensure your system meets the requirements by installing the necessary Python dependencies: pip3 install openpyxl pyyaml If you anticipate working with older legacy Excel formats (.xls), please also install the optional library: pip3 install python-calamine.

Use Cases

• Corporate Reporting: Merging monthly sales data from dozens of departmental CSV exports into a single master tracking sheet.
• Master Data Management: Updating an existing 'Employee Directory' Excel file with new hire information while validating tax ID and phone number formats.
• Data Cleaning: Standardizing data entries—such as converting all names to 'Title Case' or stripping leading/trailing whitespace—during the ingestion process.
• Bulk Migration: Importing raw client feedback sheets into a standardized database-ready template using custom field mapping.

Example Prompts

1. "Import all CSV files located in the /downloads/march-report folder into our master template, mapping 'Name' to 'FullName' and 'ID' to 'EmployeeID'."
2. "Update the 'Inventory' excel file by importing this new manifest. Use the 'SKU' column as the key field and skip any rows where the price is missing or invalid."
3. "Merge these three different department schedules into one master file and auto-detect the header rows because they have complex merged cell labels."

Tips & Limitations

• Dry-Run Feature: Always execute with the --dry-run flag first to preview your mappings and validation results before modifying your production files.
• Validation Strictness: When using 'required' validators, ensure your source data has clean headers, or the script may skip records unexpectedly.
• Memory Usage: While the tool is optimized, processing extremely large files (e.g., millions of rows) might require significant system RAM. For massive datasets, consider splitting files into smaller chunks.
• Backup: The skill creates backups by default to prevent data loss. If disk space is an issue, you can disable this, though it is highly recommended to keep it enabled for production workflows.