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Revision as of 15:21, 26 April 2020
CHINA HAPPINESS SURVEY
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Contents
Project Motivation
Association Rule Mining is Powerful
Room for Improvement of Current Packages
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’
Data Cleaning and Preparation
Choice of Visualizations and Critics
Application Design in Details
Use Cases
1.Bashboard
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2.Exploratory Data Analysis
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3.Multivariate Matrix Analysis
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4.Likert & Bubble Plot
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5.Choropleth Mapping
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6.Cluster Analysis
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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
