Comprehensive Python analysis of Nigeria's macroeconomic data (2002-2024). This project explores the resilience of physical cash vs. eNaira adoption, the impact of the 2023 Naira redesign, and international payment trends using Central Bank of Nigeria (CBN) datasets. Features data cleaning, time-series growth analysis, and visualizations.
# Nigeria Macroeconomic Analysis (2002 - 2024)
An end-to-end data analysis project investigating Nigeria's monetary trends, focusing on the relationship between physical currency circulation, eNaira adoption, and international debt obligations.
## Key Insights
- **The 2023 Cash Crunch:** Statistical visualization of the Naira Redesign policy's impact on money supply.
- **Physical Cash Resilience:** Analysis of the V-shaped recovery in 2024, where cash reached a record ₦4.14 Trillion.
- **Digital vs. Physical:** Comparison of eNaira integration levels against traditional currency.
- **Outflow Intensity:** A derived metric comparing international debt/remittances to domestic liquidity.
## Tech Stack
- **Language:** Python 3.x
- **Libraries:** Pandas (Data Wrangling), Matplotlib/Seaborn (Visualization)
- **Data Source:** Central Bank of Nigeria (CBN)
## Project Structure
- `analysis_notebook.ipynb`: The main Jupyter Notebook containing the code and logic.
- `datasets/`: Original and cleaned CSV files.
- `visualizations/`: Exported high-resolution charts for reporting.
## How to Run
1. Clone the repo: `git clone
github.com`
2. Install dependencies: `pip install -r requirements.txt`
3. Open `analysis_notebook.ipynb` in Jupyter or VS Code.
## Conclusion
Despite the push for a "Cashless Nigeria," the data suggests physical cash remains the dominant pillar of the economy. This project highlights the sensitivity of the Nigerian market to central bank policy shifts.