🌍 Global GDP Intelligence: Predictive Analytics & Business Intelligence Dashboard

A full-stack economic intelligence system — integrating 7 World Bank macroeconomic datasets, building ML regression models to predict GDP, and delivering a 4-page interactive Power BI dashboard for global and country-level economic analysis.

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📊 Dashboard Preview

Page 1 — GDP Overview

• 🗺️ World map — GDP by country (filled choropleth)
• 📈 GDP trend lines — Top economies 2000–2024
• 🔢 KPI cards — Total global GDP, world population, country count
• 🎛️ Year range slicer — filter all visuals dynamically

Page 2 — Macroeconomic Indicators

• 📉 Exports vs Imports scatter chart
• 🏦 Top countries by FDI Inflows (bar chart)
• 📊 Inflation trends over time (line chart)
• 🌐 Country slicer for filtered analysis

Page 3 — Model Results

• 🎯 Feature importance ranking (Random Forest)
• 🔵 Actual vs Predicted GDP — Random Forest
• 🔴 Actual vs Predicted GDP — Decision Tree
• 📊 R² score comparison chart

Page 4 — Country Deep Dive

• 🔍 Country selector with full KPI panel
• 📈 GDP growth trajectory over time
• 📋 Detailed data table with all indicators

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🏗️ Architecture

7 World Bank Excel Files (GDP, Exports, Imports, FDI, Inflation, Population, Govt Expenditure)
    ↓
Python Pipeline (pandas) — Melt wide→long, merge on Country+Year, clean missing values
    ↓
EDA — Correlation heatmap, scatter plots, distribution analysis, top economy trends
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Feature Selection — Random Forest importance ranking
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ML Models — Decision Tree & Random Forest Regressor (80/20 split)
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Evaluation — MAE, RMSE, R² | Residual analysis
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Export — PowerBI_GDP_Main.xlsx + Predictions + Feature Importance
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Power BI Dashboard — 4 interactive pages

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📁 Dataset

• Source: World Bank Open Data
• Coverage: 180+ countries | 2000–2024
• Indicators integrated:

File	Indicator	Role
GDP.xls	GDP (current US$)	Target variable
Export.xls	Exports of goods & services	Feature
Imports.xls	Imports of goods & services	Feature
FDI inflows.xls	Foreign Direct Investment net inflows	Feature
Inflation.xls	Consumer Price Index	Feature
Population.xls	Total population	Feature
Goverment_Expenditure.xls	General government expenditure	Feature

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🤖 Machine Learning Results

Metric	Decision Tree	Random Forest
MAE	Higher	✅ Lower
RMSE	Higher	✅ Lower
R² Score	Good	✅ Better
Winner		✅ Random Forest

Key finding: Population and Government Expenditure rank as the top GDP predictors globally, with ensemble methods (Random Forest) significantly outperforming single-tree models by reducing variance across the high-dimensional cross-country dataset.

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🚀 How to Run

Python Pipeline

# Clone
git clone https://github.com/Derio001/exploratory-predictive-gdp-analysis.git
cd exploratory-predictive-gdp-analysis

# Install dependencies
pip install pandas numpy matplotlib seaborn scikit-learn openpyxl xlrd

# Run the notebook
jupyter notebook Project_Implementation.ipynb

Power BI Dashboard

1. Download Power BI Desktop (free)
2. Open powerbi_implementation.pbix
3. If prompted, re-link the data source to your local PowerBI_GDP_Main.xlsx

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📁 Project Structure

exploratory-predictive-gdp-analysis/
│
├── Project_Implementation.ipynb      # Full Python pipeline (78 cells)
├── powerbi_implementation.pbix       # 4-page Power BI dashboard
│
├── data/
│   ├── Global GDP and Macroeconomic Indicators Dataset/
│   │   ├── GDP.xls
│   │   ├── Export.xls
│   │   ├── Imports.xls
│   │   ├── FDI inflows.xls
│   │   ├── Inflation.xls
│   │   ├── Population.xls
│   │   └── Goverment_Expenditure.xls
│   │
│   ├── Integrated_GDP_Dataset.csv          # Cleaned unified dataset
│   ├── PowerBI_GDP_Main.xlsx               # Main Power BI data source
│   ├── PowerBI_Predictions.csv            # Actual vs predicted GDP
│   └── PowerBI_Feature_Importance.csv     # Feature rankings
│
└── README.md

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🔭 Future Work

• Add Sub-Saharan Africa focused lens (Chad, Niger, Mali, Sudan deep dive)
• Incorporate conflict/fragility index as a feature for Sahel economies
• Time-series forecasting (ARIMA / LSTM) for multi-year GDP projection
• Live World Bank API integration for automatic data refresh
• Streamlit web app version for browser-based access

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👤 Author

Mahamat Hanga Derio M.Tech Data Science — Christ University, Bangalore Chadian national | Building economic intelligence tools for Sub-Saharan Africa

📬 Open to collaboration with development banks, economic research institutions & policy organizations 🔗 GitHub | LRI Child Health Project →

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Part of a portfolio focused on data-driven economic and public health analysis for the Lake Chad Basin and Sub-Saharan Africa.