Group04 research paper

CHINA HAPPINESS SURVEY

Proposal

Poster

Application

Report

Abstract

Happiness is a very important topic all around the world nowadays, especially in China, the country which is becoming more and more focus on people’s happiness because of the development. Happiness can be influenced by a lot of factors, such as health, education and income. Also, happiness can show different features in different regions. Our objective is to get the most important factors to happiness in China. Therefore, we will use several types of graphs such as likert scale, bubble plot and mapping to analyze the result of a survey on Chinese people’s happiness in 2015 and consider different provinces in China.

Project Motivation

Our objective is to see the influence of different factors on happiness and get the most important factors. In order to get the factors, we will use several types of graphs, including exploratory data analysis, multivariate matrix analysis, likert scale, bubble plot, choropleth mapping and cluster analysis to analyze the happiness survey result in China in 2015 and show the results by different provinces. We will consider the happiness score given by the respondents themselves as the main target and choose several factors which we think have large influence on happiness to see the importance of them. Besides, when choosing the question results which can represent factors, we will choose subjective questions first, because they can directly show the real feelings of people.

R Packages Used

• For Interactive Application: R Shiny and Shiny Dashboard

Shiny is an R Studio package for developing interactive charts, data visualizations and applications to be hosted on the web using the R programming language. It enables developer to make an interactive application which allow user to understand a certain model or do some data explorations. In this case, we could visualize the underlying rules beyond given datasets which show a clear picture of how those items correlate with each other. Package ‘shiny’Package ‘shinydashboard’

• For Interactive Plot: ggplot2, plotly and gghighlight Package ‘plotly’ Package ‘ggplot2’ Package ‘gghighlight’

• For Choropleth Mapping: tmap, sf and leaflet Package ‘tmap’Package ‘leaflet’

• For HeatMap: heatmaply Package ‘heatmaply’

• For Likert Scale: likert Package ‘likert’

• For Correlation Matrix: corrplot Package ‘corrplot’

• For data preparation: sqldf(for SQL operations in R),dplyr,stringr Package ‘sqldf’ Package ‘dplyr’ Package ‘stringr’

Use Cases

1.Bashboard

2.Exploratory Data Analysis

3.Multivariate Matrix Analysis

4.Likert & Bubble Plot

5.Choropleth Mapping

6.Cluster Analysis

References

• World Happiness Report 2020
• Shiny Application layout guide,JJ Allaire
• Event handler R Shiny
• Build your first web app dashboard using Shiny and R
• Enterprise-ready dashboards
• ggplot2 Reference and Examples (Part 2) - Colours
• Hands-On Exercise 8: Diverging Stacked Bar Chart, Dr. Kam Tin Seong
• Hands-on Exercise 8: Heatmap Visualisation with R, Dr. Kam Tin Seong
• Hands-On Exercise 8: Visualising Correlation Matrix, Dr. Kam Tin Seong
• Hands-on Exercise 10: Choropleth Mapping with R, Dr. Kam Tin Seong
• Hands-on Exercise 10: Mapping Geospatial Point Data with R, Dr. Kam Tin Seong