Global Happiness Analysis

Project Overview

Welcome to the World Happiness Index Data Analysis project repository. This project was developed as the final assignment for the Data 101 course and aims to analyze and visualize the World Happiness Report dataset. The report highlights the importance of happiness and well-being in governmental policies by evaluating various factors that contribute to happiness across different countries.

Authors

• Jasmine Tuiachieva
• Djeinabou Diallo

About the Dataset

The dataset used in this project is derived from the Gallup World Poll, specifically focusing on responses to the Cantril ladder question. This question asks respondents to rate their current lives on a scale from 0 (worst possible life) to 10 (best possible life). The dataset includes six key factors that influence happiness:

1. Economic production (GDP per capita)
2. Social support
3. Life expectancy
4. Freedom to make life choices
5. Absence of corruption
6. Generosity

Project Goals

The primary goal of this project is to analyze the World Happiness Report data and present key insights through comprehensive visualizations. By doing so, the project aims to:

• Identify the top and bottom countries based on their happiness scores.
• Examine the correlation between various factors and the overall happiness score.
• Highlight key determinants of happiness and their relative importance.

Key Findings

• Top 5 Happiest Countries: Finland, Denmark, Switzerland, Iceland, Netherlands.
• Bottom 5 Unhappiest Countries: Lesotho, Botswana, Rwanda, Zimbabwe, Afghanistan.
• Determinants of Happiness: GDP per capita, social support, and healthy life expectancy are the most influential factors.

Skills and Concepts Demonstrated

This project showcases a variety of skills and concepts in data analytics, including:

• Data Collection: Acquiring data from reliable sources (e.g., Kaggle).
• Data Cleaning: Processing raw data to ensure accuracy and consistency.
• Exploratory Data Analysis (EDA): Utilizing statistical techniques to uncover patterns and insights.
• Data Visualization: Creating visual representations of data to communicate findings effectively. Tools used include correlation matrices and funnel charts.
• Statistical Analysis: Understanding relationships between different variables using correlation analysis.

Files in the Repository

• Data & Charts Table.xlsx: Contains the data and charts used for analysis.
• LICENSE: MIT license for the project.
• README.md: This document, providing an overview of the project.
• World happiness Infographics Poster.pdf: The final poster presenting the key findings and visualizations.

How to Use This Repository

1. Explore the Data: Open the Data & Charts Table.xlsx file to view the data and charts.
2. View the Poster: Check out the World happiness Infographics Poster.pdf for a comprehensive summary of the findings.

References

• World Happiness Report Dataset
• World Happiness Report
• Gallup World Poll

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Thank you for visiting this repository. If you have any questions or feedback, feel free to contact the authors.