Analyzing Global Trends for Water Supply

Project Overview

This project focuses on analyzing global water supply data, specifically examining the total population supplied by the water supply industry. By leveraging historical data, we aim to extract meaningful insights and predict future trends to help stakeholders understand water accessibility and sustainability.

Data Source

• Source: Environment Statistics Database | United Nations Statistics Division
• Official Links:
  • Environment Statistics Database
  • United Nations Data

Project Objectives

• Analyze historical water supply data to identify trends across various countries.
• Visualize the data to communicate insights effectively to both technical and non-technical stakeholders.
• Implement predictive modeling to forecast future water supply scenarios.

Data Description

The dataset consists of the following columns:

• Country or Area: Name of the country or region.
• Year: The year of the recorded data.
• Value: Percentage of the population supplied by the water supply industry.
• Unit: Measurement unit, in this case, a percentage.

Key Analysis Steps

1. Data Cleaning: Addressing missing values and ensuring the dataset is ready for analysis.
2. Exploratory Data Analysis (EDA): Visualizing trends, distributions, and relationships within the data.
3. Feature Engineering: Creating relevant features that enhance the predictive modeling process.
4. Predictive Modeling: Using machine learning techniques to forecast water supply for upcoming years.
5. Stakeholder Summary: Presenting findings in an easy-to-understand format for non-technical audiences.

Summary of Insights

• Overall trends indicate improvements in water supply across many countries.
• Specific nations, such as Albania and Algeria, have shown notable progress over the years.
• Predictions suggest a positive trajectory in water supply accessibility in the coming years.

Visualization

We created several visualizations, including:

• Line charts for historical trends.
• Bar charts for feature importance in predictive models.
• Infographics summarizing key insights for stakeholders.

Conclusion

This project provides valuable insights into the global water supply situation and predicts future trends. By using data-driven analysis, we aim to contribute to the understanding and sustainability of water resources worldwide.

Acknowledgments

Special thanks to the United Nations for providing the data that enabled this analysis.

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