KAMBALENGUNUNU/Bigdata-foodinsecurity-africa

# 🌍Food Insecurity Analysis in African Countries 🌍 **INSY 8413: Introduction to Big Data Analytics - Capstone Project** **Academic Year: 2024-2025, Semester III** **Student:** Daniel Kambale Ngununu **Instructor:** Eric Maniraguha > **Dataset Source**: FAO Food Security Indicators --- ## 📋 Project Overview This capstone project analyzes food insecurity patterns across African countries using the FAOSTAT dataset. The analysis employs comprehensive data preprocessing, multiple machine learning models, and innovative approaches to identify vulnerable populations and regions, providing actionable insights for food security interventions. ### 🎯 Problem Statement **"Can we identify patterns and predict food insecurity levels across African countries using historical FAOSTAT data to inform targeted intervention strategies?"** ### 🏭 Sector Focus - **Primary:** Agriculture & Health - **Secondary:** Government & Policy --- ## 📊 Dataset Information - **Dataset Title:** FAOSTAT Food Security Indicators - **Source:** FAO Statistical Database - **File:** `FAOSTAT_data_en_8-2-2025.csv` - **Dimensions:** 306 rows × 12 columns (after cleaning) - **Data Structure:** Structured (CSV) - **Key Indicators:** - Prevalence of undernourishment - Prevalence of severe food insecurity - Prevalence of moderate or severe food insecurity - Number of people undernourished ### 📈 Data Characteristics - **Time Period:** 2021-2023 - **Geographic Coverage:** African countries - **Missing Values:** Minimal (2 values in target variable) - **Outliers:** 0 detected (post-cleaning) --- ## 🛠️ Technical Implementation ### 🔧 Technologies Used - **Python 3.13** - **Libraries:** pandas, numpy, scikit-learn, matplotlib, seaborn, scipy - **Environment:** Jupyter Notebook / VS Code - **Version Control:** Git/GitHub ### 📁 Project Structure ``` BigData-FoodInsecurity-Africa/ │ ├── data/ │ └── FAOSTAT_data_en_8-2-2025.csv │ ├── notebook/ │ └── food_insecurity_africa_analysis.py │ ├── images/ │ └── …