manqoba-SA/Educational-Data-Analysis-of-South-Africa

# Educational Data Analysis of South Africa This repository contains a Jupyter Notebook that explores a dataset of educational indicators for South Africa. The data includes a wide range of metrics that track various aspects of the education system over multiple years. ## Dataset Overview The dataset, named `education_zaf.csv`, is a comprehensive collection of education-related indicators from South Africa. It covers a plethora of variables ranging from enrollment rates and average years of schooling to government expenditure on education and literacy rates. ## Analysis Summary The Jupyter Notebook within this repository carries out the following analyses: - **Data Preprocessing**: Inspection of data types and handling of missing values. - **Descriptive Statistics**: Calculation of central tendency, dispersion, and distribution metrics for different educational indicators. - **Time Series Analysis**: Exploration of trends over time in educational attainment and government expenditure. - **Visualizations**: Line graphs and bar charts to illustrate the findings and trends within the data. ## Key Insights The analysis led to several key insights, including: - A decline in the population with no education, especially among young females. - Growth in higher educational attainment, with notable gender parity in recent years. - Increased government investment in education, as reflected by the GDP percentage. ## Repository Structure Save to grepper └── education_zaf.csv # Dataset file └── M_Ngubeni_220121897.ipynb # Jupyter Notebook with the complete analysis └── README.md ## Usage To run the Jupyter Notebook, ensure that you have Jupyter installed on your system, which is available as part of the Anaconda distribution or can be installed via pip. Then, navigate to the directory and open the `M_Ngubeni_220121897b` file. ## Acknowledgments - Data sourced from humdata.org.