Tosenrium/nigeria-inflation-analysis

End-to-end data science project analyzing Nigeria's historical inflation trends using Python, Pandas, Matplotlib, Scikit-learn, and Jupyter Notebook. Turning Nigeria's historical inflation data into actionable economic insights using Python, data visualization, and exploratory data analysis. # nigeria-inflation- Turning raw economic data into actionable insights. This project analyzes Nigeria's inflation trends using Python, Pandas, and data visualization to uncover patterns, tell the story behind the numbers, and showcase practical data science skills through a real-world analytical workflow. --- ## 📖 Overview Nigeria has experienced significant fluctuations in inflation over the years, affecting purchasing power, investment decisions, and economic stability. This project explores historical inflation data for Nigeria using Python and modern data analysis techniques to identify patterns, trends, and insights that can support economic understanding and decision-making. The project demonstrates the complete data analysis workflow—from raw data preprocessing to visualization, interpretation, and documentation—following industry best practices. This repository serves as the first project in my Applied Data Science portfolio. --- # 🎯 Project Objectives - Analyze Nigeria's historical inflation trends. - Clean and prepare raw economic data. - Perform Exploratory Data Analysis (EDA). - Visualize inflation patterns over time. - Generate meaningful economic insights. - Export cleaned datasets for reuse. - Demonstrate a professional end-to-end data science workflow. --- # ⚙️ Requirements Before running this project, ensure you have: - Python 3.12+ - Jupyter Notebook - pip (Python package manager) ### Required Python Packages | Package | Version | |----------|---------| | ipykernel | 6.29.5 | | jupyter | 1.1.1 | | matplotlib | 3.11.1 | | numpy | 2.5.1 | | openpyxl | 3.1.5 | | pandas | 3.0.3* | | scikit-learn | 1.9.0 | | scipy | 1.18.0 | > **Note:** These package versions are those used during development. Newer compatible versions may also work. Install all dependencies using: ```bash pip install -r requir …