This repository contains a data analysis project on the United Nations High Commissioner for Refugees (UNHCR) refugee dataset. The aim of this project is to analyze the trends and patterns of the refugee crisis globally, focusing on key indicators such as refugee populations, countries of origin, and host countries.
To get started with this project, you will need to download the code and data from this repository. The analysis is conducted using Python programming language and a range of data analysis libraries such as Pandas, NumPy, and Matplotlib. The code is written in Jupyter Notebooks, which allow for a clear and interactive presentation of the analysis results.
The data source used in this project is the United Nations High Commissioner
The analysis in this project includes exploratory data analysis, statistical analysis, and data visualization. The aim is to provide insights into the refugee crisis, such as the countries with the highest refugee populations, the main causes of displacement, and the countries providing the most support to refugees.
The results of this project are presented in a clear and concise manner through interactive charts and graphs, as well as detailed explanations of the analysis process and findings. The code and data in this repository can be used by researchers, policymakers, and data enthusiasts who are interested in exploring and understanding the refugee crisis.
This project provides valuable information and tools to understand and explore the refugee crisis, using the UNHCR refugee dataset. By analyzing key indicators, this project presents insights into the global refugee crisis, which can inform policy decisions and aid in providing support to those in need.
Made with ❤️ by Janmay Joshi and Vansh Tandon