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AbdurRahmanSalami/nigeria-economic-intelligence-dashboard

Domain:

socioeconomic

Record type:

software
Creator:
Abd
Host:
# πŸ‡³πŸ‡¬ Nigeria Economic Intelligence Dashboard An interactive data science dashboard for exploring Nigeria's macroeconomic performance, historical trends, economic relationships, and inflation forecasts. ## Live Demo 🌐 Launch the Nigeria Economic Intelligence Dashboard ## Project Overview This project combines data collection, data engineering, exploratory analysis, statistical modelling, time-series forecasting, and interactive visualisation in a Streamlit application. Historical Nigerian economic indicators are collected programmatically from the World Bank API, cleaned with Python, combined into a unified dataset, analysed, and presented through an interactive dashboard. ## Features - World Bank API data collection - Automated data-cleaning pipeline - Historical macroeconomic analysis - Interactive indicator charts - Custom year-range filtering - Latest economic indicator cards - Year-over-year changes - Executive economic summary - Correlation analysis - Interactive relationship explorer - Inflation forecasting - Forecast model comparison - 95% forecast confidence intervals - Downloadable datasets ## Economic Indicators The project includes: - Consumer price inflation - Official exchange rate - GDP growth - Unemployment rate - Oil rents (% of GDP) - Foreign reserves - Current account balance ## Data Sources Data is collected using the World Bank API for Nigeria (`NGA`). | Indicator | World Bank Code | |---|---| | Inflation | `FP.CPI.TOTL.ZG` | | Official exchange rate | `PA.NUS.FCRF` | | GDP growth | `NY.GDP.MKTP.KD.ZG` | | Unemployment | `SL.UEM.TOTL.ZS` | | Oil rents | `NY.GDP.PETR.RT.ZS` | | Total reserves | `FI.RES.TOTL.CD` | | Current account balance | `BN.CAB.XOKA.GD.ZS` | ## Data Pipeline World Bank API β†’ Raw JSON β†’ Python Cleaning β†’ Processed CSV β†’ Exploratory Analysis β†’ Forecasting β†’ Streamlit Dashboard Missing historical observations are retained rather than artificially filled. ## Inflation Forecasting The following models were evalua …