This project examines global shark attack incidents, focusing on understanding patterns and trends that could help us create a business plan for developing an anti-shark-attack product. Our goal was to identify key factors contributing to shark attacks to better understand high-risk conditions, locations, and activities.

The dataset includes records of shark attacks worldwide, with fields like:

• Country: Country where the attack occurred
• Activity: Activity of the victim at the time of the attack (e.g., surfing, swimming)
• Time: Approximate time of the attack
• Age and Gender: Gender of the victim

Data was sourced from publicly available shark attack records, providing information across various locations and activities.

To ensure data quality and reliability, we performed essential cleaning steps, including:

1. Removed columns that were empty or did not contain meaningful information.
2. Filled or removed null values in critical fields.
3. Kept records with verified attack data and removed duplicates.
4. Converted text to lowercase, removed whitespace, and formatted dates consistently.

Our analysis identified patterns in shark attacks based on:

• Location: High-risk countries.
• Time of Day: Peak times for shark encounters.
• Activity: Activities associated with a higher likelihood of shark attacks.
• Age and Gender: Most common age and gender of shark attack victims.

These insights helped in forming a business case for designing an anti-shark-attack product targeting high-risk activities and locations.

To explore this project: please run the Google Colab file to see data preprocessing, detailed data exploration, and visualization.

1. Run the jupyter notebook to see data preprocessing, detailed exploration, and visualization.
2. Read the 'Insights' file to see the conslusions upon which we constructed our business plan.
3. Presentation url: https://www.canva.com/design/DAGVEHPpPuQ/4NUs-LkI0RAXxqcbsyrXxQ

This project provides actionable insights into shark attack risks, supporting the development of targeted anti-shark-attack solutions. By understanding when and where attacks are most likely to occur, we can make informed recommendations to minimize sh

• Alvaro, Aurelie, Clara and Marc