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gAIety

🌍 World Happiness Report (2020-2024) - Streamlit Web App

This project explores the World Happiness Report (2020-2024) and predicts Healthy Life Expectancy using machine learning. It also includes a Streamlit web app that displays happiness insights, predictions, and jokes for entertainment.

📊 Dataset Information

The dataset is sourced from Kaggle:
World Happiness Report 2020-2024

It consists of data from 2020 to 2024, covering multiple countries, with features representing different happiness indicators.

Dataset Columns & Description

Column Name Description
Country name Name of the country
Happiness Rank Rank of the country based on happiness score
Happiness Score Overall happiness score (0-10)
Upperwhisker Upper confidence interval for happiness score
Lowerwhisker Lower confidence interval for happiness score
Economy (GDP per Capita) GDP per capita (economic indicator)
Social Support Extent of social support in the country
Healthy Life Expectancy Average healthy life expectancy (Target Variable)
Freedom to make life choices Perception of freedom in making life decisions
Generosity Measure of generosity in society
Perceptions of Corruption Perception of government corruption
Year Year of the data

📂 Data Preparation & Exploration

  1. Load all five CSV files (2020-2024) into Pandas.
  2. Explore the datasets to check for missing values, column names, and data consistency.
  3. Standardize column names if they differ across years.

🛠 Data Cleaning & Preprocessing

  1. Handle missing values (drop, impute, or interpolate as needed).
  2. Convert categorical data into numerical (e.g., encoding Country name).
  3. Normalize numerical values for better model performance.

📊 Exploratory Data Analysis (EDA)

Visualize trends over the years

  1. box plots
  2. histograms
  3. pair plot
  4. skewness graph to see if the distribution is balanced

🎯 Machine Learning Model

1️⃣ Model Used: Random Forest Regressor, Linear Regression A Random Forest Regression model was trained to predict Healthy Life Expectancy using all other features.

2️⃣ Model Performance

  1. Mean Squared Error (MSE): 0.0109 for Random Forest Regressor and 0.0178 for Linear Regression
  2. The low error indicates the model performs well in predicting Healthy Life Expectancy based on the given features.
  3. r2 error is alos found

Feature Importance Ranking is caluclated

🎨 Streamlit Web App

Features of the App

  1. Home Page - Displays famous happiness quotes from philanthropists.
  2. Predictions Page - Allows users to select a country and predict Healthy Life Expectancy.
  3. Jokes Page - Displays a random joke to entertain users.

📌 Future Improvements

  1. More interactive visualizations (e.g., box plots, scatter plots).
  2. Experiment with different ML models for comparison.
  3. Cluster analysis to group countries based on happiness scores.

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