Difference between revisions of "FLATearthers proposal"
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<div style="background: #C2CAD0; padding: 20px; line-height: 0.3em; letter-spacing:0.1em; font-size:150%; font-weight:bold; text-align: center; margin-left: 5em; margin-right: 5em;"><font color=#000 face="Verdana">PROJECT MOTIVATION</font></div> | <div style="background: #C2CAD0; padding: 20px; line-height: 0.3em; letter-spacing:0.1em; font-size:150%; font-weight:bold; text-align: center; margin-left: 5em; margin-right: 5em;"><font color=#000 face="Verdana">PROJECT MOTIVATION</font></div> | ||
<div style= "text-align: left; margin-left: 10em; margin-right: 10em; font-size: 15px"><font color=#000 face="Verdana"> | <div style= "text-align: left; margin-left: 10em; margin-right: 10em; font-size: 15px"><font color=#000 face="Verdana"> | ||
− | + | As Singapore government ramps up efforts to collect and share data sets to the public, various kinds of information are readily available. There are however, no readily available tools that could allow analysts who are well-versed in real estate, but do not have the coding know-how to perform analysis. Thus, our group hopes to bridge the gap and provide these analysts with a friendly user interface and experience. | |
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<div style="background: #C2CAD0; padding: 20px; line-height: 0.3em; letter-spacing:0.1em; font-size:150%; font-weight:bold; text-align: center; margin-left: 5em; margin-right: 5em;"><font color=#000 face="Verdana">PROJECT DESCRIPTION</font></div> | <div style="background: #C2CAD0; padding: 20px; line-height: 0.3em; letter-spacing:0.1em; font-size:150%; font-weight:bold; text-align: center; margin-left: 5em; margin-right: 5em;"><font color=#000 face="Verdana">PROJECT DESCRIPTION</font></div> | ||
<div style= "text-align: left; margin-left: 10em; margin-right: 10em; font-size: 15px"><font color=#000 face="Verdana"> | <div style= "text-align: left; margin-left: 10em; margin-right: 10em; font-size: 15px"><font color=#000 face="Verdana"> | ||
− | Our project aims to find out how external and internal factors may affect resale housing prices. External factors are, though not limited to, | + | Our project aims to find out how external and internal factors may affect resale housing prices, specifically for HDB resale flats. External factors are, though not limited to, shopping malls, hawker centers, MRTs and LRTs, supermarkets, primary schools, pre-schools and eldercare services. Internal factors are, though not limited to, remaining lease, floor area, storey, flat type and model. |
− | We will be using | + | We will be using 2 different models: |
− | # | + | # Multiple linear regression |
− | # Geographically weighted regression | + | # Geographically weighted regression |
− | + | ||
+ | to compare and explain how the factors stated above may, affect resale housing prices. | ||
</div> | </div> | ||
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|-style="font-size: 100%; | |-style="font-size: 100%; | ||
! <b>Data Set</b> | ! <b>Data Set</b> | ||
− | ! <b> | + | ! <b>Source</b> |
− | ! <b> | + | ! <b>Data Type/Method</b> |
+ | |-style="font-size: 100%; | ||
+ | | 2014 Master Plan Planning Subzone | ||
+ | | [https://data.gov.sg/dataset/resale-flat-prices?resource_id=1b702208-44bf-4829-b620-4615ee19b57c data.gov.sg] | ||
+ | | SHP | ||
|-style="font-size: 100%; | |-style="font-size: 100%; | ||
− | | [https://data.gov.sg/dataset/resale-flat-prices?resource_id=1b702208-44bf-4829-b620-4615ee19b57c | + | | Resale flat prices |
+ | | [https://data.gov.sg/dataset/resale-flat-prices?resource_id=1b702208-44bf-4829-b620-4615ee19b57c data.gov.sg] | ||
| CSV | | CSV | ||
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|-style="font-size: 100%; | |-style="font-size: 100%; | ||
− | | [https://en.wikipedia.org/wiki/List_of_shopping_malls_in_Singapore | + | | Singapore Shopping malls |
− | | | + | | [https://en.wikipedia.org/wiki/List_of_shopping_malls_in_Singapore Wikipedia] |
− | + | | Text to SHP | |
|-style="font-size: 100%; | |-style="font-size: 100%; | ||
− | | [https:// | + | | Singapore Hawker Centers |
− | + | | Hawker Centres <br> | |
− | | | + | # [https://data.gov.sg/dataset/hawker-centres?resource_id=c2e33097-4f46-4ef5-91db-64eef290ca85 data.gov.sg] <br><br> |
+ | Others <br> | ||
+ | # [http://www.kopitiam.biz/search-results/?keywords&zone=allzone&FC=yes&search=Search Kopitiam] | ||
+ | # [https://www.koufu.com.sg/our-brands/food-halls/koufu Koufu] | ||
+ | # [https://foodrepublic.com.sg/food-republic-outlets/ Food republic] | ||
+ | | KML | ||
|-style="font-size: 100%; | |-style="font-size: 100%; | ||
− | | | + | | MRT / LRT Stations |
− | | | + | | [https://www.mytransport.sg/content/mytransport/home/dataMall/static-data.html LTA Datamall] |
− | | | + | | SHP |
− | |||
− | |||
|-style="font-size: 100%; | |-style="font-size: 100%; | ||
− | | [https:// | + | | Supermarkets |
− | | | + | | [https://en.wikipedia.org/wiki/List_of_shopping_malls_in_Singapore Wikipedia] |
− | + | | Text to SHP | |
− | |||
− | |||
|-style="font-size: 100%; | |-style="font-size: 100%; | ||
− | | [ | + | | Primary Schools |
− | + | | [https://data.gov.sg/dataset/school-directory-and-information Primary Schools] | |
− | | | + | | CSV |
− | |||
− | |||
|-style="font-size: 100%; | |-style="font-size: 100%; | ||
− | | [https:// | + | | Premium Primary Schools |
− | | | + | | [https://elite.com.sg/primary-schools Premium Primary Schools] |
− | + | | Text to SHP | |
|-style="font-size: 100%; | |-style="font-size: 100%; | ||
− | | [https:// | + | | Premium Pre-schools |
− | | | + | | [https://skoolopedia.com/preschool-singapore-infographic/ Pre-Schools] |
− | + | | Text to SHP | |
|} | |} | ||
</div> | </div> |
Latest revision as of 00:02, 15 April 2019
As Singapore government ramps up efforts to collect and share data sets to the public, various kinds of information are readily available. There are however, no readily available tools that could allow analysts who are well-versed in real estate, but do not have the coding know-how to perform analysis. Thus, our group hopes to bridge the gap and provide these analysts with a friendly user interface and experience.
Our project aims to find out how external and internal factors may affect resale housing prices, specifically for HDB resale flats. External factors are, though not limited to, shopping malls, hawker centers, MRTs and LRTs, supermarkets, primary schools, pre-schools and eldercare services. Internal factors are, though not limited to, remaining lease, floor area, storey, flat type and model.
We will be using 2 different models:
- Multiple linear regression
- Geographically weighted regression
to compare and explain how the factors stated above may, affect resale housing prices.
Data Set | Source | Data Type/Method |
---|---|---|
2014 Master Plan Planning Subzone | data.gov.sg | SHP |
Resale flat prices | data.gov.sg | CSV |
Singapore Shopping malls | Wikipedia | Text to SHP |
Singapore Hawker Centers | Hawker Centres Others |
KML |
MRT / LRT Stations | LTA Datamall | SHP |
Supermarkets | Wikipedia | Text to SHP |
Primary Schools | Primary Schools | CSV |
Premium Primary Schools | Premium Primary Schools | Text to SHP |
Premium Pre-schools | Pre-Schools | Text to SHP |
Key Challenges | Mitigation |
---|---|
Unfamiliarity with R and packages required for project |
|
Unfamiliarity with proper approach to use for project |
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Limitations of OneMap API to handle large amount of data |
|