Nelvinebi/Fish-Stock-Decline-Analysis

A data science project analyzing synthetic environmental and fishing activity data to model fish stock decline in the Niger Delta, using exploratory analysis, correlation mapping, and regression modeling to understand key drivers and support sustainable fisheries management. Fish Stock Decline Analysis 📌 About the Project This project analyzes factors contributing to fish stock decline in the Niger Delta using synthetic environmental and fishing activity data. It demonstrates how data science can be applied to understand ecological challenges and support sustainable fisheries management. 📊 Features Synthetic dataset with 150+ records Environmental indicators: Water Quality Index Fishing Effort (hours/week) Habitat Loss (%) Exploratory Data Analysis (EDA) with pair plots & correlation heatmaps Linear Regression Model to quantify factor influence on fish stock Data export to Excel (.xlsx) 🛠 Technologies Used Python 3 Pandas NumPy Matplotlib Seaborn Scikit-learn 📂 Project Structure bash Copy Edit . ├── fish_stock_decline_analysis.py # Main script ├── fish_stock_decline_synthetic.xlsx # Generated dataset └── README.md # Project documentation 🚀 How to Run Clone this repository or copy the code into a .py file. Install required packages: bash Copy Edit pip install pandas numpy matplotlib seaborn scikit-learn Run the script: bash Copy Edit python fish_stock_decline_analysis.py View the generated dataset (fish_stock_decline_synthetic.xlsx) and visualizations. 📈 Example Insights Higher fishing effort and habitat loss significantly reduce fish stock. Poor water quality negatively impacts fish populations. The model achieves a high R² value indicating strong predictive accuracy. 👤 Author Agbozu Ebingiye Nelvin 📧 Email: nelvinebingiye@gmail.com 💻 GitHub: github.com LinkedIn: *linkedin.com