World Happiness Report Analysis

Dataset Overview

This project analyzes the World Happiness Report datasets to understand factors influencing happiness across countries. By examining data from 2015 and 2023, the goal is to identify decisive happiness factors, explore regional differences, and develop predictive models for happiness scores.

Data Files

The repository contains the following files:

1. World_Happiness_Report_Analysis.ipynb: A Jupyter Notebook with full analysis, including data preprocessing, exploratory data analysis (EDA), correlation analysis, and machine‑learning models.
2. 2015.csv: Dataset for the 2015 World Happiness Report, used for regional information gathering.
3. WHR2023.csv: Dataset for the 2023 World Happiness Report, serving as the primary analysis dataset.

Data Sources

The analysis uses datasets from Kaggle:

• World Happiness Report 2023
• World Happiness Report 2015

Project Objectives

1. Identify happiness drivers: Determine the most important variables influencing happiness scores, such as GDP, social support, and life expectancy.
2. Regional happiness analysis: Explore happiness differences across regions and identify regional trends.
3. Classification and Prediction: Develop machine‑learning models to classify and predict happiness scores based on key factors.

Analytical Methods

The analysis proceeds through the following steps:

1. Data preprocessing: Handle missing values, normalize data, and merge datasets for comprehensive analysis.
2. Exploratory Data Analysis (EDA): Visualize and examine data distribution, outliers, and regional trends.
3. Correlation analysis: Use statistical methods to identify relationships between happiness scores and various factors.
4. Machine‑learning models: Implement decision‑tree regression and linear regression to predict happiness scores.

Results Overview

• Key drivers: GDP, social support, and healthy life expectancy are the most influential factors for happiness scores.
• Regional analysis: Western Europe, North America, Australia, and New Zealand achieve the highest happiness scores, while Asia and Africa lag behind.
• Predictive model: The decision‑tree regression model explains approximately 83 % of the variance in happiness scores, demonstrating its effectiveness.