In this project, we utilize the shark attack dataset and use Python to clean and explore the data, validate our hypotheses, and extract meaningful insights.
- Hypothesis 1: Shark attacks tend to happen in particular locations and during specific times of the year (seasons).
- Hypothesis 2: Certain activities and human factors, such as gender, may influence the occurrence of shark attacks.
- We confirmed that location (Country & State) and season are relevant when assessing the risk of shark attacks. Key Finding: Summer is the primary season for shark attacks across hemispheres.
- Examining top activities linked to increased shark attack risks was useful, but human factors such as gender showed minimal insights or correlations with activities.
