Global Population Analysis: Insights from 1960-2022

A comprehensive data-driven project exploring global population dynamics and its socio-economic implications from 1960 to 2022.

Table of Contents

1. Introduction
2. Data Source Justification
3. Relevance, Scope, and Methodology
4. Technical Exploration
5. Conclusion

Introduction

This research delves into global population changes to understand their multifaceted aspects. It focuses on analyzing patterns of growth, examining influential factors such as GDP progression, age distribution, and age dependency ratios. The primary dataset used for this project is sourced from the World Bank Open Data portal.

Data Source Justification

The World Bank's "Population, total" dataset offers extensive insights into global population figures over time. Its relevance, origin, acquisition, and comparison with other datasets have been elaborated to ensure the authenticity and reliability of the data source.

Relevance, Scope, and Methodology

Population dynamics play a pivotal role in various global challenges. This project aims to identify top countries by population growth, investigate their patterns, and assess the socio-economic implications. The analytical data processing pipeline and evaluation methodologies are also outlined to offer clarity on the approach adopted.

Technical Exploration

An in-depth technical exploration of the dataset to comprehend its characteristics, structure, and potential issues. This section encompasses both data cleaning and exploratory analysis.

Conclusion

While the project has provided valuable insights into global demographic trends, it's a mere foundation for numerous possibilities in further research. The exploration emphasizes the significance of data analysis and visualization in understanding global socio-economic and demographic changes.

Dataset

The primary dataset for this project is available at World Bank Open Data portal.

Libraries Used

• Python
• Pandas
• Matplotlib
• Seaborn
• Jupyter Notebook

Authors

• Yassin Nawar - Initial work, analysis, and documentation.
• Goldsmith College - Academic supervision and project guidance.
• University of London - Institutional support and resources.

License

This project is licensed under the MIT License. While the analysis, interpretations, and code are original contributions by the authors, the raw data was sourced from the World Bank's open data platform.