A Python-based tool that analyzes work order data to support governance reporting.
This system handles data classification, chart and slide generation, and structured output for stakeholder visibility.

• Modular workflow design for scalability and maintainability
• Excel chart creation via xlsxwriter
• Automated PowerPoint slide generation
• Customizable classification logic with edge case handling
• wxPython GUI for user interaction
• Unit-tested components for high reliability
• Markdown tree output to document directory structure

work_order_analysis/ ├── config/ # YAML and config files ├── data/ # Input datasets ├── gui/ # wxPython GUI components ├── outputs/ # Generated files (Excel, PowerPoint, reports) ├── scripts/ # Core logic modules │ ├── classifier.py # Classifies work orders by status and type │ ├── data_loader.py # Loads and normalizes raw work order data │ ├── summary_generator.py # Generates summary tables and breakdowns │ ├── analysis_runner.py # Runs analysis and prints/exports summaries │ ├── slide_generator.py # Creates and updates PowerPoint slides │ ├── slide_updater.py # Updates charts in PowerPoint presentations │ ├── chart_builder.py # Builds and exports charts for reporting │ └── charts/ │ ├── pm_missed_chart.py # Generates PM missed charts │ └── group_missed_chart.py # Generates group missed charts ├── tests/ # Unit tests validating functionality │ ├── test_classifier.py # Tests classification logic │ ├── test_data_loader.py # Tests data loading logic │ └── test_summary_generator.py # Tests summary generation logic ├── main.py # Entry point for launching GUI and CLI processing ├── directory_tree.md # Auto-generated directory documentation └── README.md # Project documentation

• Purpose: Classifies work orders by status, dates, and type.
• Requirements: DataFrame with columns like 'status', 'target_date', 'actual_finish'.
• Output: Adds 'wo_class' column for reporting and analysis.

• Purpose: Loads raw work order data, normalizes columns, converts dates.
• Requirements: Excel or CSV input file, COLUMN_MAP config.
• Output: Cleaned DataFrame with normalized columns and 'report_month'.

• Purpose: Generates summary tables and breakdowns for monthly, group, and governance metrics.
• Requirements: Classified DataFrame.
• Output: Summary DataFrames, Excel exports, late work order lists.

• Purpose: Runs analysis from cleaned data, prints and exports summary metrics.
• Requirements: 'cleaned_work_orders.csv' with required columns.
• Output: Console output, optional file export.

• Purpose: Generates and updates PowerPoint slides for governance reporting.
• Requirements: DataFrames with summary/group/monthly data, PowerPoint template.
• Output: Updated presentation saved to outputs.

• Purpose: Updates PowerPoint charts with new data.
• Requirements: Presentation object, chart data, chart names.
• Output: Updated charts in PowerPoint file.

• Purpose: Builds and exports charts for reporting (Excel and PowerPoint).
• Requirements: DataFrame with monthly metrics.
• Output: Excel chart, PowerPoint slide.

• Purpose: Generates PM missed charts by month.
• Requirements: Dict with 'months', 'due', 'complete', 'missed'.
• Output: Chart image file.

• Purpose: Generates group missed charts (count and percent).
• Requirements: Dict with 'groups', 'missed', 'missed_percent'.
• Output: Chart image file.

• Purpose: wxPython GUI for user interaction, file selection, and report generation.
• Requirements: wxPython, input file, core scripts.
• Output: Interactive analysis, exports to Excel/PowerPoint.

• Purpose: Entry point for CLI and GUI workflows.
• Requirements: Input file, all core modules.
• Output: CLI: console and file output; GUI: dashboard and export options.

• Purpose: Unit tests for classifier, data loader, and summary generator.
• Requirements: Sample data, relevant modules.
• Output: Pass/fail results for each test case.

python -m venv .venv
.\.venv\Scripts\activate  # On Windows
pip install -r requirements.txt

python main.py

• GUI will launch for user input, file selection, and report generation.

python main.py path\to\your\input_file.csv

pytest tests/

• Includes unit tests for classifier logic, data flows, and output integrity.

• Classifications link to governance tags
• Slide decks generated with key metrics and summaries
• Clean handoff for stakeholder review using PowerPoint templates

• CI/CD for automated testing and deployment
• HTML dashboard output option
• Tag releases for milestone tracking

This project was built with a focus on modularity, maintainability, and usability—empowering technical and non-technical stakeholders to rely on meaningful insights from work order data.

Future Enhancements

• Add CI/CD pipeline for automated validation
• Integrate dashboard summary in HTML
• Tag versions for traceable governance milestones