WPS Excel Spreadsheet Automation
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About this skill
Problem
Repetitive Excel / WPS spreadsheet work often involves more than single formulas: reading multiple workbooks, merging worksheets, and producing a reviewable report. Manually opening attendance files, sales files, and then formatting target values, actuals, and completion rates is slow and error-prone.
How It Works
The skill centers on Python-based spreadsheet processing, with WPS-compatible .xlsx output and data extraction from complex .xlsm files:
- Formatted report generation: uses openpyxl to create professionally formatted Excel files for financial reports, sales monthly reports, and data summaries. Color conventions can distinguish business meaning: blue for input items, black for calculated values, and green for cross-sheet references.
- Complex xlsm parsing: when openpyxl cannot open files with VBA macros, large financial models, or special structures, zipfile and xml.etree can extract data from the package without adding extra dependencies.
- Batch processing: reads multiple worksheets, merges data, and produces summary reports for attendance rollups, sales data cleanup, and HR batch tasks.
Boundaries and Notes
- It is a script-based spreadsheet-processing skill, not a GUI WPS automation tool; output may need review before use.
- Color rules are example conventions and should be adjusted to the business definition.
- For macro-heavy, protected, or unusually structured
.xlsmfiles, parsing may extract readable XML data without preserving macro behavior.
Use Cases
- Finance compiles targets, actuals, and completion rates from multiple worksheets into a color-coded xlsx report.
- Use zipfile and xml.etree to extract data from a macro-heavy xlsm model that openpyxl cannot open.
- HR merges worksheets from 20 attendance files into one monthly summary report.
- Sales generates a monthly report with performance, completion rate, ranking, and color-coded values.
Best For
- Financial analyst who needs multiple worksheets compiled into color-coded xlsx reports
- HR specialist who merges 20 attendance files into a monthly summary report each month
- Sales operations person who creates monthly reports with targets, actuals, and completion rates color-coded
- Data engineer who extracts data from macro-heavy xlsm files that openpyxl cannot open
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