Abstract

Abstract: The concept of measuring happiness was introduced to the world by the government of Bhutan as Gross National Happiness which later was adapted by UN in the form of happiness index that measures the happiness and well-being of the population of the country. This project aims to analyze the happiness index and its relationship with various factors by making use of different attributes related to happiness of people. Features like ladder score, GDP per capita, life expectancy score etc. are used to analyze the happiness. The results have been presented by using pie charts, graphs and tables. The algorithms and tools like multiple regression and Naive Bayes have been used to measure the extent of dependence of the factors on happiness index. The Happiness Index is framed to set various parameters on grounds of which a country could be ranked in a list of 156 countries. India’s rank has come down the list in the year 2019 to be ranked at the 140th position. This clearly indicates India’s deteriorating position down the years. This project elaborates the concept of Happiness Index as a measure and analyses various reasons for India to lose its position in the World Happiness Report. Keywords: Data Science,Multiple Linear Regression Algorithm , Naive bayes Classifier .