Data Analytics project analyzing Egypt agriculture using FAOSTAT data with Power BI and Python
# π± Egypt Agriculture Analytics - FAOSTAT
## π Project Overview
This project analyzes **25 years of agricultural data in Egypt** using FAOSTAT datasets, focusing on:
* πΎ Crop production & yield
* π§ Rainfall & temperature impact
* π CO2 emissions
* π± Fertilizer usage
* π₯ Population growth
* π§βπΎ Arable land
The goal is to provide **data-driven insights for sustainable agriculture and food security**.
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## π― Objectives
* Analyze agricultural trends in Egypt
* Measure efficiency of water and fertilizer usage
* Study climate impact on crop production
* Evaluate sustainability indicators
* Support decision-making using data
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## π Tools & Technologies
* Power BI (Dashboard & Data Modeling)
* Python (Data Analysis & Prediction)
* Pandas, Scikit-learn
* FAOSTAT Dataset
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## π Dashboard Features
* KPI Tracking (Yield, Efficiency, Growth)
* Climate Impact Analysis
* Crop Performance Comparison
* Sustainability Metrics
* Food Security Indicators
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## π€ AI Component
A simple **Smart Agriculture Chatbot** was developed to:
* Recommend irrigation decisions
* Suggest suitable crops
* Predict crop yield
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## π Project Structure
```
data/ β dataset files
powerbi/ β Power BI dashboard
python/ β analysis & ML scripts
report/ β final report
images/ β dashboard screenshots
```
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## πΈ Dashboard Preview
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## π Key Insights
* Agricultural productivity is strongly influenced by rainfall and temperature
* Fertilizer efficiency varies across crops
* CO2 emissions are increasing alongside production
* Population growth creates pressure on food supply
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## π Future Improvements
* Real-time data integration
* Advanced machine learning models
* Deployment as web application
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## π¨βπ» Author
Graduation Project - Data Analytics Track
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