https://github.com/invcble/report-automation---files
https://github.com/invcble/report-automation---files
Last synced: about 1 year ago
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- Host: GitHub
- URL: https://github.com/invcble/report-automation---files
- Owner: invcble
- Created: 2024-04-28T07:31:29.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2024-09-16T04:07:32.000Z (over 1 year ago)
- Last Synced: 2024-12-26T00:26:25.678Z (over 1 year ago)
- Language: Python
- Size: 6.89 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Leadership Development Assessments Automation
This project automates the reporting process for leadership development assessments used in corporate and executive education programs. The automation streamlines data handling, processing, and report generation, significantly improving efficiency and reliability.
## Table of Contents
- [Overview](#overview)
- [Features](#features)
- [Libraries Used](#libraries-used)
- [Contributing](#contributing)
## Overview
The project automates the creation of leadership development assessment reports, which were previously generated manually. The assessments include self and peer evaluations conducted via Qualtrics, with data processed through R scripts and reports generated in PDF format.
## Features
- **Data Extraction**: Automates the download and processing of survey data from Qualtrics.
- **Report Generation**: Creates PDF reports using PyPDF2, ReportLab, and other libraries.
- **Customization**: Allows for the inclusion of company logos and other custom elements in reports.
- **Integration**: Combines self and peer assessment data for comprehensive reports.
- **Efficiency**: Reduces manual effort and improves the speed and reliability of report generation.
## Libraries Used
The project leverages the following Python libraries:
- `PyPDF2`: For manipulating PDF files.
- `ReportLab`: For generating PDF documents.
- `PIL` (Pillow): For image processing.
- `Matplotlib`: For creating graphs and charts.
- `pandas`: For data manipulation and analysis.
- `numpy`: For numerical operations.
- `csv`: For reading and writing CSV files.
- `datetime`: For handling date and time operations.
## Contributing
Contributions are welcome! Please fork the repository and submit a pull request with your changes.