Difference between revisions of "G4 Report"
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==R Packages Used== | ==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. [https://cran.r-project.org/web/packages/shiny/shiny.pdf Package ‘shiny’][https://cran.r-project.org/web/packages/shinydashboard/shinydashboard.pdf Package ‘shinydashboard’] | ||
| + | *For Interactive Plot: ggplot2, plotly and gghighlight [https://cran.r-project.org/web/packages/plotly/plotly.pdf Package ‘plotly’] [https://cran.r-project.org/web/packages/ggplot2/ggplot2.pdf Package ‘ggplot2’] [https://cran.r-project.org/web/packages/gghighlight/vignettes/gghighlight.html Package ‘gghighlight’] | ||
| + | |||
| + | *For Choropleth Mapping: tmap, sf and leaflet [https://cran.r-project.org/web/packages/tmap/vignettes/tmap-getstarted.html Package ‘tmap’][https://rstudio.github.io/leaflet/ Package ‘leaflet’] | ||
| + | |||
| + | *For HeatMap: heatmaply [https://cran.r-project.org/web/packages/heatmaply/heatmaply.pdf Package ‘heatmaply’] | ||
| + | |||
| + | *For Likert Scale: likert [https://rdrr.io/cran/likert/man/shinyLikert.html Package ‘likert’] | ||
| + | |||
| + | *For Correlation Matrix: corrplot [https://cran.r-project.org/web/packages/corrplot/vignettes/corrplot-intro.html Package ‘corrplot’] | ||
| + | |||
| + | *For data preparation: sqldf(for SQL operations in R),dplyr,stringr [https://cran.r-project.org/web/packages/sqldf/sqldf.pdf Package ‘sqldf’] [https://cran.r-project.org/web/packages/dplyr/dplyr.pdf Package ‘dplyr’] [https://cran.r-project.org/web/packages/stringr/stringr.pdf Package ‘stringr’] | ||
==Choice of Visualizations and Critics== | ==Choice of Visualizations and Critics== | ||
Revision as of 16:19, 25 April 2020
CHINA HAPPINESS SURVEY
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Contents
Project Motivation
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’
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
- visNetwork, an R package for interactive network visualization
- Association Rules and the Apriori Algorithm: A Tutorial,Annalyn Ng, Ministry of Defence of Singapore
- Association Rule Mining with R,Yanchang Zhao
- Market basket analysis,S. Bushmanov
- Market Basket Analysis Using R and Shiny, Maureen O'Donnell
- Shiny Application layout guide,JJ Allaire
- Zoomable plots in Shiny, RStudio, Inc.
- Introduction to visNetwork,B. Thieurmel - DataStorm
- Interactive arules with arulesViz and visNetwork,timelyportfolio
- Network visualization with R Workshop,Katya Ognyanova
- Selecting rows of data R Shiny
- Write Transactions or Associations to a File
- Event handler R Shiny
- Using Action Buttons R Shiny
- Create an object for storing reactive values R Shiny
