Difference between revisions of "ISSS608 2016-17 T1 Assign1 WEI Jingxian"
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There are ten variables in the dataset, including registration date, flat information, and flat price. The sample data has shown below. Noticed that the date variable Month is treated as string in Tableau, so we need to calculate a new variable, which is in date format in Tableau, so that we can use the variable to do further analysis. | There are ten variables in the dataset, including registration date, flat information, and flat price. The sample data has shown below. Noticed that the date variable Month is treated as string in Tableau, so we need to calculate a new variable, which is in date format in Tableau, so that we can use the variable to do further analysis. | ||
| − | [[File:Datapre.jpg|800px| | + | [[File:Datapre.jpg|800px|frameless|center]] |
| − | [[File:SupplyDis.jpg|400px| | + | [[File:SupplyDis.jpg|400px|frameless|center]] |
| − | [[File:TownSupply.jpg|400px| | + | [[File:TownSupply.jpg|400px|frameless|center]] |
| − | [[File:SupplyChange15.jpg|400px| | + | [[File:SupplyChange15.jpg|400px|frameless|center]] |
| − | [[File:FlatModel.jpg|800px| | + | [[File:FlatModel.jpg|800px|frameless|center]] |
| − | [[File:SvsP.jpg|400px| | + | [[File:SvsP.jpg|400px|frameless|center]] |
| − | [[File:PriceDis.jpg|400px| | + | [[File:PriceDis.jpg|400px|frameless|center]] |
| − | [[File:Price&area.jpg|400px| | + | [[File:Price&area.jpg|400px|frameless|center]] |
| − | [[File:PriceChange.jpg|400px| | + | [[File:PriceChange.jpg|400px|frameless|center]] |
| − | [[File:Supply.jpg|400px| | + | [[File:Supply.jpg|400px|frameless|center]] |
| − | [[File:SupplyChange.jpg|400px| | + | [[File:SupplyChange.jpg|400px|frameless|center]] |
== Tools Utilised == | == Tools Utilised == | ||
== Result == | == Result == | ||
Revision as of 13:17, 29 August 2016
Contents
Abstract
Problem and Motivation
Public housing is an icon of Singapore, and HDB flats are home to over 80% of Singapore's resident population. However, sometime it is not easy for resident to apply flats due to financial or other problems. The resale flat is a good choice for these resident. We purpose to provide a clear view of resale flats for residents who are interested in resale flats and help them in making decisions. The dataset we used is from HDB, resale-flat-price
There are two key variables have significant impacts on resident’s choice, including price and location. First of all, people always concern about price. Apart from price, people would also care about locations of flats.
- What are the shares of the resale public housing supply in 2015 (at least three observation),
- What are the distribution of the resale public housing prices in 2015 (at least three observation), and
- With reference to the findings, compare the patterns of the first-half of 2016 with the patterns of 2015.
Approaches
Data Preparation
There are ten variables in the dataset, including registration date, flat information, and flat price. The sample data has shown below. Noticed that the date variable Month is treated as string in Tableau, so we need to calculate a new variable, which is in date format in Tableau, so that we can use the variable to do further analysis.
