Analysis of water access patterns and disparities across South Africa using data analysis and visualization techniques.
# Water Access Analysis in South Africa
## Project Overview
This project explores water access patterns and disparities across South Africa using data analysis, exploratory data analysis (EDA), predictive modeling, and visualization techniques.
## Objectives
* Clean and prepare water access datasets
* Perform exploratory data analysis (EDA)
* Develop predictive models
* Visualize key findings and trends
* Support data-driven insights into water accessibility challenges
## Project Structure
* `01_data_cleaning.ipynb` – Data cleaning and preprocessing
* `02_eda.ipynb` – Exploratory data analysis and visualizations
* `03_model.ipynb` – Predictive modeling and evaluation
* `README.md` – Project documentation
* `Screenshots/` – Visual outputs and dashboard screenshots
## Tools and Technologies
* Python
* Pandas
* NumPy
* Matplotlib
* Scikit-learn
* Jupyter Notebook
## Key Skills Demonstrated
* Data Cleaning
* Exploratory Data Analysis
* Data Visualization
* Machine Learning
* Problem Solving
## Author
**Trustworth Bakamela**
Aspiring Data Analyst | Data Science NQF 5 Student
LinkedIn:
linkedin.com