phumz-ile/NDTA631-South-Africa-Transport-GHG-Food-Security

NDTA 631 Data Analysis and Visualisation – South Africa: Transport GHG Emissions and Food Security Analysis # South Africa: Transport GHG Emissions and Food Security Analysis ## NDTA 631 – Data Analysis and Visualisation ### Research Question What relationship exists between transport-sector greenhouse gas emissions and food security indicators in South Africa from 2002 to 2021? ## Datasets This project uses two datasets: 1. FAO Food Security dataset 2. WRI Climate Watch dataset ## Study Period 2002–2021 ## Project Overview This project analyses the relationship between transport-sector greenhouse gas emissions and selected food security indicators in South Africa. The analysis follows the required project stages: 1. Data preparation and cleaning 2. NumPy analysis 3. Data visualisation 4. Database creation and SQL analysis 5. Python and Excel analysis 6. Final report and conclusion ## Analysis The cleaned datasets were combined into a master dataset containing yearly observations from 2002 to 2021. The analysis includes data preparation, descriptive statistics, NumPy calculations, correlations, visualisations, database queries, and Excel analysis. ## How to Run the Notebook 1. Download or clone this repository. 2. Open `South_Africa_Climate_and_Food_Security_Analysis.ipynb` using Jupyter Notebook or JupyterLab. 3. Install the required Python libraries. 4. Run the notebook cells from top to bottom. ## Python Libraries The project uses Python libraries including: - pandas - NumPy - matplotlib - seaborn - sqlite3 - openpyxl ## Authors NDTA 631 Group Assignment