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Kharendwenegota/sa-unemployment-analysis

Domain:

socioeconomic

Record type:

project
Creator:
Kha
Host:
Data Analysis project focused on the issues of unemployment in South Africa, it's causes and potential solutions and suggestions on how to minimize it. # South Africa Unemployment Analysis An end-to-end data analysis project exploring unemployment trends in South Africa (1991-2025), with a focus on youth unemployment, education disparities, and economic shock recovery — using Python, SQL Server, Power BI, and Tableau. ## 🔍 Key Findings - **Youth unemployment consistently runs ~2x the national rate**, and the gap has widened over time — from ~20 points in the early 1990s to 27-31 points in the 2020s. - **Education is the strongest predictor of unemployment risk** in this dataset: advanced-education unemployment (12-15%) sits far below basic education (~34-41%) — but the gap has never closed structurally, only narrowed temporarily before widening again. - **Unemployment lags behind GDP shocks by roughly a year.** The 2020 COVID GDP collapse (-6.2%) didn't produce its worst unemployment impact until 2021 — even as GDP was already recovering. - **Neither the 2008 financial crisis nor COVID saw a real recovery within 5 years** — both show a sharp spike followed by a plateau at a new, higher baseline. - **Inflation shows no meaningful relationship with unemployment** (correlation: -0.27), challenging assumptions about "stagflation" driving SA's unemployment crisis. ## 🛠️ Tools Used | Tool | Purpose | |---|---| | Python (pandas, sklearn) | Data cleaning, merging, trend projection | | SQL Server | Data storage, analytical queries (window functions, CASE logic) | | Power BI | Interactive dashboard, KPI overview | | Tableau Public | Narrative-driven visual storytelling | | Excel | Initial data inspection | ## 📈 Data Sources - World Bank Open Data — SA unemployment, youth unemployment, GDP growth, inflation, education-tier unemployment (SL.UEM.* indicators) ## 📊 Dashboards ### Power BI Interactive dashboard covering youth vs. national unemployment, the GDP-unemployment lag effect, education-tier comparison, and key stats (peak unemployment, current rate, …

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