Motivation of the application

Recently, happiness is considered to be the proper measure of social progress and the goal of public policy. According to World Happiness Report 2017, Norway is the happiest country in the world and Singapore is the happiest country in Asia. With the raw data given retrieved from Kaggle, the following interested questions would like to be approached:

How is country happiness score distributed globally?
How is happiness score measured?
What factors influence the residences’ happiness the most?
How does country happiness ranking change over the time?
Which countries are outperformed in 2015, 2016, and 2017, and in what aspect?

Review and critic on past works

Design framework

Visualization	Description
Map	World map with the package highchart shows users an intuitive distribution of happiness score across country. With yellow-blue gradient, scores from high to low can be recognized and compared straightforward.
Histogram	Histogram, an accurate graphical representation of the distribution of numerical data, is used to show the distribution of world happiness scores. With the histogram, users are able to understand how the happiness score of distributed, the mean and median of the overall world happiness score from 2015 to 2017.
Tableplot	A tableplot is used to explore the relationships between the variables for high-dimensional data. In this project, it allows users to discover countries’ happiness ranking changes patterns from 2015 to 2017 on a world or region scale. The data set is sorted according to happiness rank in 2015, each row representing corresponding country’s rankings of these three years. Outperformed countries can be observed from the tableplot obviously. Concave indicates the country ranks up in 2016 or 2017, compared with 2015, while convex means its rank dropped.
Regression Analysis	Regression analysis applies linear regression to model the relationship between the dependent variable (Happiness Score) and each independent variables (Economy, Family, Health, Freedom, Trust, and Generosity). It is able for users to understand which independent variable will influence the happiness score the most through the regression analysis. Moreover, users are able to easily find out outliers for each independent variable and determine whether those countries are outperformed or fallen behind.
Heatmap	Heatmap is a graphical representation of data where the individual values contained in a matrix are represented as colors. From the heatmap, users are able to understand which countries are more keen on Economy, which countries are more interested in Freedom, and so on. Countries are grouped into clusters based on their interests of each independent variable. In this project, Shiny heatmap, an advanced user-friendly heatmap is used to allow users to customize the heatmap as desired.