This helps to analyse if the socio-economic inequality lowered at South Africa or not.
# š Is Apartheid Really Over?
### A Data-Driven Analysis of Socio-Economic Inequality in South Africa
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## š
Historical Context
On this very day in **1992**, a referendum led by the white population in South Africa voted to dismantle apartheid laws. While apartheid officially ended, an important question remains:
> **Have social and economic conditions truly improved?**
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## š Dataset
- Link:
kaggle.com
- The raw file is at ghs-2022-person-v1.csv.zip. Unzip it to get the file.
š Note: Only the **2022 dataset** was used for this analysis.
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## āļø Tools Used
- Python (Pandas, NumPy, Matplotlib, Seaborn, Plotly)
- Jupyter Notebook
- GitHub (for project hosting)
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# š Key Insights
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## 1ļøā£ Income Inequality by Race
- **Whites earn the highest incomes**
- Followed by:
- Indian/Asian
- Coloured
- African/Black (lowest)
### š Question Raised:
Is this due to population imbalance?
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## 2ļøā£ Population & Employment Distribution
- African/Black population dominates both:
- Metro areas
- Non-metro areas
### Employment Share:
- African/Black ā **76.3%**
- White ā **11.1%**
- Coloured ā **9.1%**
- Indian/Asian ā **3.5%**
### š” Insight:
- African/Black population contributes most **numerically**
- However, **income per individual remains low**
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## 3ļøā£ Income Gap Within Provinces
- Whites earn more in **every province**
- African/Black population earns the least consistently
- Indian/Asian group shows relatively strong income levels
- Coloured population shows **high variability**
### š§ Conclusion:
> Inequality persists even within the same region
ā This indicates **structural inequality**, not just geographic differences
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## 4ļøā£ Spatial Inequality (Regional Income Gap)
### š Above National Average:
- Northern Cape ā **+19.2%**
- Western Cape ā **+16.4%**
- Free State ā **+13.7%**
- Gauteng ā **+11.0%**
### š Below Nationa ā¦