Yohannes022/ethiopian-agro-weather-intelligence

🌍 Ethiopian Agro-Weather Intelligence System 📌 Overview The Ethiopian Agro-Weather Intelligence System is a data-driven project that analyzes multi-year weather data across strategically selected Ethiopian cities to understand climate patterns and their impact on agriculture and resource planning. This project integrates data engineering (ETL), exploratory data analysis, time-series analysis, and geospatial visualization to produce actionable insights relevant to agriculture, policy-making, and environmental monitoring. 🎯 Objectives - Analyze temperature and rainfall trends across diverse Ethiopian regions - Identify seasonal weather patterns (rainy vs dry periods) - Compare climatic differences based on geography and elevation - Assess agricultural suitability and drought risk - Provide data-driven insights for farming and resource planning 🌐 Data Sources - Weather data collected from the Open-Meteo API - Time range: 2020 – 2025 - Data includes: - Temperature (min, max, average) - Rainfall (precipitation) 🧠 Project Approach This project follows a structured ETL (Extract → Transform → Load) pipeline implemented in Jupyter notebooks: 🔄 1. Extract - Retrieved real-time and historical weather data using API calls 🔄 2. Transform - Cleaned missing and inconsistent values - Converted date formats for time-series analysis - Engineered key features: - `temp_avg` (average temperature) - `is_rainy` (rain indicator) 🔄 3. Load - Stored raw and processed datasets in structured directories for reproducibility 🌍 Strategic City Selection Cities were selected based on agro-climatic diversity to enable meaningful comparison: - Addis Ababa – Moderate climate, urban baseline - Bahir Dar – High rainfall, strong agricultural potential - Hawassa – Warm climate, agro-industry hub - Mekelle – Semi-arid, drought-prone region - Dire Dawa – Hot and dry, extreme low rainfall 💡 Why This Matters Th …