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TheKingSegun/nigeria-inflation-dashboard

Domaine:

socioeconomic

Type de record:

project
Créateur:
The
Hôte:
Nigeria CPI & inflation analysis using NBS data | Python, Power BI, pandas # Nigeria Inflation Dashboard An end-to-end data analysis project tracking Nigeria's Consumer Price Index (CPI) and inflation trends using data from the **National Bureau of Statistics (NBS)**. ## Project Overview This project analyses Nigeria's inflation landscape — headline CPI, food inflation, core inflation, and urban vs. rural breakdowns — using Python for data processing and Power BI for interactive dashboards. ## Key Insights - Food inflation has consistently outpaced headline CPI by 3-6 percentage points - Urban centres (Lagos, Abuja) experience faster price transmission than rural zones - Energy price shocks (PMS deregulation, FX pass-through) show clear CPI lag effects - Naira depreciation correlates with a 45-60 day import-price transmission lag ## Tools & Technologies | Tool | Purpose | |------|---------| | Python (pandas, matplotlib, seaborn) | Data cleaning & EDA | | Power BI | Interactive dashboards | | Excel | Raw NBS data formatting | | Jupyter Notebook | Analysis pipeline | ## Project Structure ``` nigeria-inflation-dashboard/ ├── data/ │ ├── raw/ # Raw NBS CPI data (CSV) │ └── processed/ # Cleaned and transformed data ├── notebooks/ │ └── inflation_analysis.ipynb ├── dashboard/ │ └── screenshots/ # Dashboard PNG exports ├── src/ │ └── data_pipeline.py └── README.md ``` ## Data Sources - NBS Nigeria — CPI & Inflation Reports - CBN Statistical Bulletin - World Bank Open Data ## How to Run ```bash git clone github.com cd nigeria-inflation-dashboard pip install -r requirements.txt jupyter notebook notebooks/inflation_analysis.ipynb ``` ## About Built by **David** — Senior Data Analyst with expertise in Nigerian macroeconomic data and business analytics.