Donmichael63/Africa-s_Climate_Analysis

Analysis of GHG emissions and temperature change in Africa (1980–2030) # GHG Emissions and Temperature Change in Africa: Fixed Scenario Analysis (1980–2030) ## Project Overview This project analyzes greenhouse gas (GHG) emissions and their impact on temperature change in African countries (1980–2023), using a comprehensive global dataset from Our World in Data. As part of my data science skill-building journey, I cleaned this massive dataset (\~50,000 rows, 70+ columns) in Excel to focus on Africa, demonstrating data wrangling, EDA, visualization, and predictive modeling. The scope is limited to Africa to showcase my skills for an internship application while addressing climate change, emphasizing `land_use_change_co2` (e.g., deforestation) as a key GHG driver, identified through Power BI visualizations. Dynamic scenario analysis correctly predicts warming for emission increases (±10%, ±20%) and cooling for reductions. **Key Insight**: `land_use_change_co2` dominates GHG emissions in Africa, and `temperature_change_from_ghg` shows the highest warming impact. Increasing emissions by 10% or 20% leads to warming, while reductions yield cooling effects. ## Dataset - **Source**: `owid-co2-data.csv`, a global dataset with emissions and temperature data. - **Data Cleaning**: - **Excel**: - Filtered for 54 African countries using `iso_code`. - Restricted to 1980–2023. - Selected 14 columns: `country`, `year`, `co2`, `land_use_change_co2`, `temperature_change_from_ghg`, etc. - Imputed missing values with medians or removed rows with >50% gaps. - Exported to `africa_co2_data_filtered.csv` (\~2,376 rows). - **Python**: Applied interpolation (<20% missing) or median imputation. - **Key Columns**: - `land_use_change_co2`, `co2`: Emissions (million tonnes CO2e). - `temperature_change_from_ghg`: Temperature change (°C). - `co2_per_capita`: Tonnes per person. ## Key Results ### 1. Cleaned Dataset - **Output**: `africa_co2_data_filtered.csv`. - **Details**: A robust dataset cleaned in Excel, ready for analysis. Small `temperature_change_f …