Sunny Singapore
Contents
Introduction
Singapore is a leading economy in its region, but an astonishing number of its citizens fall below the first-world poverty line.
First-world poverty is a new concept to many, as it represents a group of citizens who are earning less than sufficient to cover the cost of living of their country of residence. For the fifth consecutive year, Singapore has held to its number one position as the most expensive city to live in. Although welfare is extensive in Singapore, it is definitely not exhaustive. Thus, this has become our main source of motivation for this project.
We seek to develop a tool that is easy use, analyse and to act on because we strongly believe that helping our communities should not be limited to the efforts of the government. We aim to design a platform where users can recognise the less-privileged areas and understand intuitively the type of support required. As such, any citizen, committees or even organisations can utilise this resource to lend a helping hand immediately and effectively.
Problem and Motivation
To build a dashboard that allows for:
- Profiling of neighbourhoods in Singapore by attributes: income, job specification, transportation, housing and qualifications
- Other sub-attributes to provide for analytical context: age, race/religion, expenditure, marital status, political views
- Infographic on First-World Poverty
- General guidelines on the support type for various helpgroups
Objectives
This project aims to provide insights into the following:
- Income data by geography
- Socioeconomic status by income
- Support types categorised by socioeconomic situation
- Scalable system to incorporate future data
Background Survey of Related Works
to be updated
Proposed Storyboard
#1: Home Page
To provide background story, define Singapore's first-world poverty and navigation to other pages
#2: Geographical overview
Income by geography - highlight the areas that are below Singapore's poverty line
#3: Socioeconomic Overview
Compare the areas where this group of people have fallen behind the average
#4: Support type
Proposed support suggestions for these groups of people
Tools and Libraries
- Microsoft Excel
- R Studio
- Tableau
- Google Drive
Datasets
These are the datasets we plan to use:
| Dataset | Rationale |
|---|---|
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Foreseen Technical Challenges
We encountered the following technical challenges throughout the course of the project. We have indicated our proposed solutions, and the outcomes of the solutions.
| Key Technical Challenges | Reason | Proposed Solution |
|---|---|---|
|
We will be retrieving our datasets from singstat.gov.sg and data.gov.sg. These two platforms provide an exhaustive list but only have data for the recent decades. |
NA | |
|
Unfamiliar with tools that are required to for data visualisation. |
NA |
Project Timeline
Week 8: Complete detailed project proposal and gather datasets supervised by Alexia
Week 9: Clean datasets supervised by Pham
Week 10: Create data visualisation & consult on quality of work supervised by Parth
Week 11: Finalise storyboard teamwork with help of professor!
Week 12: Get ready for deadlines whoop!
References
- Tableau: https://www.tableau.com/learn/training
- R Shiny: https://shiny.rstudio.com/tutorial/
Comments
Feel free to leave comments / suggestions!
