emilycalvert/un_energy_data_eda

"Energy Statistics Analysis in Africa During COVID" is a data-driven project that explores the impact of the COVID-19 pandemic on energy consumption and production in African countries. Using advanced data analysis and visualization techniques, this project aims to provide insightful trends and implications for energy policy and management. # Energy Statistics Analysis in Africa During COVID ## Project Overview This project aims to analyze energy consumption and production trends in African countries during the COVID-19 pandemic. Utilizing data science and statistical analysis techniques, the study seeks to uncover how the pandemic has affected the energy sector across the continent. ## Key Objectives - **Data Exploration**: Investigate energy production and consumption data across various African countries. - **Trend Analysis**: Identify significant trends and changes in energy statistics during the pandemic period. - **Impact Assessment**: Assess the implications of these trends on energy policy and management in the context of COVID-19. ## Skills and Technologies Used - **Data Analysis and Visualization**: Employed Python libraries like Pandas, Seaborn, and Matplotlib for data manipulation and insightful visualizations. - **Statistical Methods**: Conducted trend analyses to understand the dynamic changes during the pandemic. - **Geospatial Analysis**: Utilized Folium for mapping and spatial trend identification. ## Potential Value Contribution - **Policy Making and Energy Management**: Provides crucial insights for governments and energy organizations to make informed decisions in energy management during crisis situations. - **Academic and Research Implications**: Serves as a valuable resource for academic research in understanding the socio-economic impacts of global health crises on key sectors like energy. - **Strategic Planning for Future Crises**: Assists in developing resilient energy policies and strategies to manage future global disruptions effectively. ## Repository Content - **Jupyter Notebook**: Contains the code, analysis, visualizations, and findings of the project. - **Data Files**: Includes the datasets used for the analysis. ## About the Author Emily Calvert is a data scientist with a passion for applying analytical skills to real-world problems. With expertise in machi …