fatimaujunwa/South-African-Unemployment-Classification--Challenge-

Domaine:

socioeconomic

Type de record:

dataset

Créateur:

fat

Hôte:

# South African Youth Employment Prediction Challenge This project involves predicting the employment status of youth in the South African labour market one year after the baseline survey. The data spans four rounds of surveys conducted at 6-month intervals, containing numerical, categorical, and free-form text responses. Demographic information such as age, school level, and results is also provided. ## Challenge Overview Data Source: Four rounds of a survey of youth in the South African labour market, conducted at 6-month intervals. Features: Numerical, categorical, and free-form text responses, along with additional demographic information. Objective: Predict whether a person is employed at the follow-up survey based on their baseline data. Training Set: One row per individual, including baseline information and the target outcome (employed or not) one year later. Test Set: Baseline data without the target outcome. ## Exploratory Data Analysis The analysis was structured into several key sections, each aimed at exploring different aspects of the dataset to derive meaningful insights and identify potential trends or disparities. ### Geographic and Provincial Diversity Objective: To examine regional differences in academic achievements across different geographic regions and provinces. Approach: Grouped the dataset by geographic regions and provinces, calculating average academic scores (Matric, Degree, Diploma) for each group. Findings: Significant disparities were observed in academic achievements across different regions and provinces, suggesting regional inequalities that may need to be addressed through targeted educational policies and interventions. ### Academic Categories Objective: To investigate the differentiation in academic subjects across different groups. Approach: Focused on academic variables such as Matric, Degree, and Diploma, assessing their distribution and performance across various categories. Findings: The analysis revealed variances in a …

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