thatomonde2-sketch/South_Africa_Unemployment_Project

Python analysis of South Africa unemployment data with visualisation and forecasting. # South Africa Unemployment Analysis Project ## Author Thato Mokgosi Bachelor of Economic Science with Econometrics ## Project Overview This project analyses unemployment trends in South Africa using macroeconomic data from the World Bank. The project demonstrates data collection, cleaning, analysis, visualisation, and forecasting using Python. The purpose is to showcase economic data analysis skills for a professional portfolio. ## Data Source World Bank World Development Indicators Indicator: Unemployment, total (percent of total labour force) ## Tools and Technologies Python pandas matplotlib requests statsmodels Visual Studio Code Microsoft Word ## Project Structure data/ - Raw data files code/ - Python scripts output/ - Graphs and Excel tables report/ - Project report document ## How to Run the Project 1. Install Python and required libraries. 2. Open Visual Studio Code. 3. Run the script using: python analysis.py 4. The script will download data, clean it, generate graphs, and export tables. ## Key Results The analysis shows long-term unemployment trends in South Africa and provides a forecast of future unemployment rates. The project demonstrates Python programming, economic analysis, and data visualisation skills.