Guernsey Data Workflow
A full proof-of-concept automated data workflow, extracting live weather, flight, and sailing data for Guernsey, transforming and analyzing it with Python, and generating daily reports in multiple formats using Pandoc and Bash.
This was made for the course Linux for Data Scientists (2024–2025) at HoGent.
This project contains a full data workflow for analyzing and reporting datasets related to the weather, boat- and plane arrivals in Guernsey.
The workflow extracts, processes and visualizes this data daily in reports in multiple formats (Markdown, HTML, PDF, and Word) as well as keeps a backup of every PDF before overwriting the reports the next day.
The workflow integrates the following components:
- Data extraction: Bash scripts using curl and jq fetch weather, flight, and sailing data from weatherapi.com and data.gg.
- Transformation: Raw JSON data is parsed and merged into a timestamped combined.csv file.
- Analysis: A Python script (analyze_data.py) performs statistical summaries and visualizations using Pandas and Matplotlib.
- Reporting: Reports are automatically generated in Markdown and converted into multiple formats using Pandoc, with old reports backed up.
- Automation: A single orchestrating script (run_workflow.sh) executes all steps, designed for scheduling with cron.
This project demonstrates a complete end-to-end data pipeline, from live data ingestion to automated daily report generation,
and serves as a reusable template for real-world data monitoring tasks.
For more details and instructions how to run this project, see the README.md file included in the download.
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