277 lines
4.6 KiB
Markdown
277 lines
4.6 KiB
Markdown
# <div align="center">AvalCal – Automatic Evaluation & Presentation Generator</div>
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---
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## <div align="center">Overview</div>
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AvalCal is a Python-based automation tool designed to process student evaluation spreadsheets and automatically generate formatted PowerPoint presentations with performance summaries and student imagery.
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The system was developed to simplify the preparation of evaluation reports and visual presentations by automating:
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- Excel data processing
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- Evaluation classification
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- Student ranking
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- PowerPoint slide editing
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- Automatic image insertion
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- Presentation generation
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The application combines spreadsheet manipulation with automated PowerPoint editing to accelerate academic and institutional reporting workflows. :contentReference[oaicite:0]{index=0}
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---
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# <div align="center">Main Features</div>
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## Automatic Excel Processing
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- Import `.xlsx` evaluation files
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- Automatic data cleanup
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- Column normalization
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- Quantitative score processing
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- Qualitative classification analysis
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---
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## Student Classification
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The system automatically categorizes students into:
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- MUITO BOM
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- SUFICIENTE
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- MEDIOCRE
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- MAU
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---
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## PowerPoint Automation
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- Automatic PowerPoint generation
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- Dynamic text replacement
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- Student number insertion
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- Automatic photograph placement
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- Slide customization
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---
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## Image Integration
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- Automatic student image loading
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- Dynamic image positioning
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- PowerPoint image rendering
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---
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# <div align="center">Technologies Used</div>
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| Technology | Purpose |
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|:---:|:---:|
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| Python | Main programming language |
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| Pandas | Excel data processing |
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| python-pptx | PowerPoint automation |
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| Tkinter | File selection interface |
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| OpenPyXL | Excel compatibility |
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| OS Library | File management |
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---
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# <div align="center">Project Structure</div>
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```txt
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.
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├── AvalCal.ipynb
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├── Apresentação Comportamentos.pptx
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├── Fotos/*
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├── README.md
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*Not commited
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```
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---
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# <div align="center">Requirements</div>
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## Python Version
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```txt
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Python 3.10+
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```
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---
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# <div align="center">Required Libraries</div>
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Install dependencies:
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```bash
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pip install pandas python-pptx openpyxl
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```
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---
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# <div align="center">Running the Application</div>
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Execute the notebook:
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```bash
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jupyter notebook
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```
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Open:
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```txt
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AvalCal.ipynb
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```
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---
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# <div align="center">Input Files</div>
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## Excel File
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The application expects an evaluation spreadsheet in:
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```txt
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.xlsx
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```
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format.
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The Excel file is selected dynamically through a file dialog interface.
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---
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## PowerPoint Template
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Required template:
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```txt
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Apresentação Comportamentos.pptx
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```
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This presentation is automatically modified by the system.
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---
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## Student Photographs
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Student images must be placed inside:
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```txt
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/Fotos
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```
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directory.
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---
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# <div align="center">Main Functionalities</div>
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## Excel Cleaning & Transformation
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The notebook automatically:
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- Merges rows
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- Renames columns
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- Removes unnecessary fields
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- Formats scores
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- Calculates final values
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- Cleans missing values
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---
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## Quantitative & Qualitative Analysis
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The system processes:
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- Quantitative grades
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- Qualitative classifications
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- Attendance/suspension indicators
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- Behavioral metrics
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---
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## Automatic Presentation Population
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The PowerPoint template is dynamically updated with:
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- Student numbers
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- Performance rankings
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- Student photographs
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- Evaluation highlights
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---
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# <div align="center">Generated Output</div>
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The system generates:
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- Automated PowerPoint presentations
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- Structured evaluation summaries
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- Visual student performance reports
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---
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# <div align="center">Workflow</div>
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```txt
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Excel Input
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↓
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Data Cleaning
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↓
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Classification Processing
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↓
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Student Ranking
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↓
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PowerPoint Population
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↓
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Final Presentation Export
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```
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---
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# <div align="center">User Interface</div>
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The application includes:
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- File picker dialog
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- Automated processing workflow
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- Dynamic PowerPoint editing
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- Automatic image handling
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---
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# <div align="center">Intended Use Cases</div>
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- Academic evaluations
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- Military training assessments
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- Student performance analysis
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- Behavioral reporting
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- Institutional presentations
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- Automated evaluation dashboards
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---
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# <div align="center">Future Improvements</div>
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- GUI application version
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- PDF export
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- Automatic charts
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- Multi-template support
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- AI-based evaluation insights
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- Database integration
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- Web dashboard version
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---
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# <div align="center">Disclaimer</div>
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This project was developed for academic and institutional automation purposes.
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Users remain responsible for validating all generated evaluation data before official usage.
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---
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# <div align="center">Author</div>
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José Garcia
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Data Scientist
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PhD Researcher – Digitalization Engineering |