Sunny Singapore

PROPOSAL

POSTER

APPLICATION

RESEARCH PAPER

Introduction

As the jewel of Southeast Asia, Singapore is a chart topper for many global, accredited rankings. However, these prominent awards narrowly focused on the nation’s economic development, technological infrastructure and overall prosperity. In fact, much less emphasis was placed on Singapore’s real and present problems – a struggling middle class, isolated social class and undefined first-world poverty. This passion project seeks to unearth the realities by designing an intuitive application that provides straightforward visualisations of key trends and statistics of Singapore.

Problem and Motivation

Despite Singapore has its own statistical government office and multiple websites such as SingStat or data.gov.sg, most of the data you can find are in the format of an Excel spreadsheet, which is very hard to understand and draw insight for the general public. Hence, we are motivated to come up with a more user-friendly visualized tool that allows everyone to instantly identify the pattern and insight about Singapore socioeconomic situation

Objectives

In this project, we are creating a visualisation dashboard that is able to discover different aspects of Singapore:

• Economic situation and demographic of different planning areas
• The income inequality and wealth distribution
• The life standard of Singapore residents through:
  • Highest qualification achieved
  • Marital status
  • Choice of transportation
  • Accommodation situation

Datasets

These are the datasets we plan to use:

Dataset	Rationale
Map of Planing Areas in Singapore	A dataset containing SHP files of the administrative boundaries of Singapore Used as a reference to digitize Singapore planning areas https://data.gov.sg/dataset/master-plan-2014-planning-area-boundary-no-sea?resource_id=c8185fd3-3c78-48c8-94bc-a957699b4e92
Population distribution in Singapore by age, sex and planning areas	A dataset containing the total number of citizen by age and sex at each planning area in Singapore Used to visualize the demographic at each planning area https://data.gov.sg/dataset/singapore-residents-by-planning-area-subzone-age-group-and-sex
Resident households in Singapore by household size and planning areas	A dataset containing the total number of households in each planning area by household size Used to visualize the population demographic and living standard in Singapore https://data.gov.sg/dataset/resident-households-by-planning-area-and-household-size-2015
Population in Singapore by sex, economy status and planning areas	A dataset containing the total number of people by economic status and sex at each planning area Used to visualize the population demographic and living standard in Singapore https://data.gov.sg/dataset/resident-population-aged-15-years-and-over-by-planning-area-economic-status-and-sex-2015
Population in Singapore by sex, marital status and planning areas	A dataset containing the total number of people by marital status and sex at each planning area Used to visualize the population demographic and living standard in Singapore https://data.gov.sg/dataset/resident-population-aged-15-years-and-over-by-planning-area-marital-status-and-sex-2015
Working residents in Singapore by industry and planning areas	A dataset containing the total number of people working in each industry at each each planning area Used to visualize the population demographic https://data.gov.sg/dataset/resident-working-persons-aged-15-years-and-over-by-planning-area-and-industry-2015
Working residents in Singapore by monthly income and planning areas	A dataset containing the total number of people within each income range at each planning area Used to visualize the population wealth distribution https://data.gov.sg/dataset/resident-working-persons-aged-15-years-over-by-planning-area-gross-monthly-income-from-work-2015
Working residents in Singapore by occupation and planning areas	A dataset containing the total number of people working in some occupation group at each planning area Used to visualize the population socioeconomic situation https://data.gov.sg/dataset/resident-working-persons-aged-15-years-and-over-by-planning-area-and-occupation-2015
Highest qualification achieved by Singapore resident by planning area	A dataset containing the total number of people at each different qualification level at each planning area Used to visualize the population socioeconomic situation https://data.gov.sg/dataset/resident-population-aged-15-years-and-over-by-planning-area-and-highest-qualification-attained-2015
Resident Households by Planning Area and Type of Dwelling	A dataset containing the total number of people at each type of dwelling at each planning area Used to visualize the population socioeconomic situation https://data.gov.sg/dataset/resident-households-by-planning-area-n-type-of-dwelling-2015
Resident Working Persons by Planning Area and Usual Mode of Transport to Work	A dataset containing the total number of people with different transportation choice at each planning area Used to visualize the population socioeconomic situation https://data.gov.sg/dataset/resident-working-persons-aged-15-yrs-n-over-by-planning-area-n-usual-mode-of-transport-to-work-2015

Proposed Storyboard

#1: Introduction page

To provide background story, problem and motivation of this project

#2: Economic Overview

• Economic Health
  • Economic Status of different planning areas
  • Breakdown of economic status at each planning area by genders
  • Dependency ratio of different planning areas
• Economic Sector
  • Distribution of working resident in different industries
  • Distribution of working resident in different sectors of the service industry
  • Breakdown of different industries employment by planning areas
  • Breakdown of different sectors employment in the service industry by planning area
  • Distribution of working resident in different occupation groups
  • Breakdown of different occupation group by planning area

#3: Socioeconomic Overview

• Income Statistics
  • Wealth distribution each different planning area at different income range
  • Breakdown of monthly income at each planning areas
• Education Statistics
  • Highest qualification achieved by residents at each planning areas

#4: Quality of life Overview

• Housing distribution
  • Type of dwelling at different planning areas
  • Breakdown of housing type at each planning area
  • Distribution of different household size around Singapore
  • Percentage of each household size at different planning areas
• Transport Trends
  • Breakdown of transportation choice at each planning area
• Relationship
  • Breakdown of marital situation by genders and planning areas

Background Survey of Related Works

There are multiple visualizations around the world with the goal to uncover the poverty situation in different countries. Although there are not a lot of visualizations about the situation in Singapore, we were able to found a few visualizations about the US to draw inspiration from:

• Median Age of US Counties in 2018 (https://www.census.gov/library/visualizations/2019/comm/median-age.html)
• List of popular graph/ visualizations (https://datavizproject.com/)
• Visualizing Singapore (https://www.vslashr.com/2013/10/visualizing-singapore/)
• Visualization on data.gov.sg (https://data.gov.sg/)
• Singapore: Distribution by age and gender (https://viz.sg/viz/map_age_gender/)
• Singapore Demographic Visualization(https://rstudio-pubs-static.s3.amazonaws.com/281811_58c03b274d7946f99f43c616726fa243.html)

Tools and Libraries

• Microsoft Excel
• R Markdown
• R Shiny
• Google Drive

Foreseen Technical Challenges

We encountered the following technical challenges throughout the course of the project and how we overcame them.

Technical problem	Solution
Do not know how to create pie chart/ box plot using ggplot	Search on google how to make the plot Create the basic plot using R markdown to check Visualize the improvement we want to make for each graph Search on Google on how to do that Test on the graph using R markdown before applied to R Shiny
Do not know how to use reactive function to create reactive dataframe	Find multiple examples on Google find out the logic and how different people do it Write down how we want to the code to behave based on that logic Modify the code accordingly
Do not know how to design the User Interface on R shiny	Visualize what we want the app to look like Search on Google on how to make it work Test with different versions/ iterations until we are all satisfy with the look
Do not know how to deploy the app	Try to follow the instruction on shinyapp.io Ask our classmates whether they got the same problem and how to deal with it Create a new app and copy all the code/ data/ picture over

Data Analysis and Transformation

Most of the datasets need to followed the same data preparation steps

• Rename the columns so that it makes more sense
• Remove redundant columns
• Remove aggregated rows/ columns
• Filter/ Create additional attributed (if needed)
• Capitalize the planning areas name and join with the Singapore map (for map visualization)
• Aggregated the data based on chosen categories
• Find the percentage
• Spread/ Gather the dataset depend on the choice of visualization
• Create a reactive datasets (if needed)

All of these steps are developed and tested in R markdown before being used in R Shiny

Proposed Visualizations and Storyboard

• Chrolopleth map with filter to see the distribution of different attributes over Singapore
• Stacked percent barchart to show the percentage of each attributes at each planning area
• Pie chart to show the proportion of different attributes at each planning area
• Boxplot to show the distribution of residents
• Data table of each dataset in case the user want to find out more
• Statistic Summary by R to provide addtional insight about each dataset

Project Timeline

Week 8: Complete detailed project proposal and gather datasets supervised by Alexia
Week 9: Clean datasets supervised by Chau
Week 10: Create data visualisation & consult on quality of work supervised by Chau And Parth
Week 11: Finalise storyboard teamwork with help of professor!
Week 12: Get ready for deadlines whoop! Beautify the dashboard supervised by Alexia and Chau
Week 13: Finalize the user guide supervised by Parth
Week 14: Finalize the research paper and proposal supervised by Alexia and Parth

References

• https://shiny.rstudio.com/tutorial/
• https://shiny.rstudio.com/tutorial/written-tutorial/lesson2/
• http://t-redactyl.io/blog/2016/01/creating-plots-in-r-using-ggplot2-part-4-stacked-bar-plots.html
• https://plot.ly/r/pie-charts/
• http://www.sthda.com/english/wiki/ggplot2-pie-chart-quick-start-guide-r-software-and-data-visualization
• https://geocompr.robinlovelace.net/adv-map.html
• https://shiny.rstudio.com/articles/html-tags.html
• https://stackoverflow.com/questions/15282580/how-to-generate-a-number-of-most-distinctive-colors-in-r
• https://stackoverflow.com/questions/14718203/removing-particular-character-in-a-column-in-r
• https://stackoverflow.com/questions/36325154/how-to-choose-variable-to-display-in-tooltip-when-using-ggplotly
• https://stackoverflow.com/questions/16184188/ggplot-facet-piechart-placing-text-in-the-middle-of-pie-chart-slices/22804400#22804400
• https://stackoverflow.com/questions/21996887/embedding-image-in-shiny-app
• https://shiny.rstudio.com/tutorial/written-tutorial/lesson6/
• http://www.sthda.com/english/wiki/ggplot2-box-plot-quick-start-guide-r-software-and-data-visualization

Comments

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