Difference between revisions of "Law403G3"
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=Motivation= | =Motivation= | ||
| − | There are a wide variety of property searching apps and website in the world, with a smart selection function for the user to filter their favor and find the ideal house. However, | + | Singapore becomes the world’s 5th most expensive place to rent a house, according to Nested.com (a UK based property website). By average, the rental is at $4.73 psf, which makes a monthly rent of $1,985 for an individual and $3,766 for a family. Given the current market condition, there are a lot of search, filter, and comparison work to do for every house seeker to find a suitable home with good price. |
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| + | There are a wide variety of property searching apps and website in the world, with a smart selection function for the user to filter their favor and find the ideal house. However, Currently most property portals only provide a mean to search and display a list of houses based on the filter criteria like price, house size, and bedrooms etc. It does not offer visualization summary in graphs for exploration of number of match-criteria houses in different districts, property distance to metro station or shopping malls and also comparisons for different houses types. | ||
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As data analyst, we are keen to provide a customized visualization tool that can reveal all the relationship among the property features--not only can select the ideal house for the client, but all also demonstrate the parameters' relationship. | As data analyst, we are keen to provide a customized visualization tool that can reveal all the relationship among the property features--not only can select the ideal house for the client, but all also demonstrate the parameters' relationship. | ||
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=Selection of Tools= | =Selection of Tools= | ||
Revision as of 17:30, 2 October 2017
| PROPOSAL | POSTER | APPLICATION | REPORT |
Motivation
Singapore becomes the world’s 5th most expensive place to rent a house, according to Nested.com (a UK based property website). By average, the rental is at $4.73 psf, which makes a monthly rent of $1,985 for an individual and $3,766 for a family. Given the current market condition, there are a lot of search, filter, and comparison work to do for every house seeker to find a suitable home with good price.
There are a wide variety of property searching apps and website in the world, with a smart selection function for the user to filter their favor and find the ideal house. However, Currently most property portals only provide a mean to search and display a list of houses based on the filter criteria like price, house size, and bedrooms etc. It does not offer visualization summary in graphs for exploration of number of match-criteria houses in different districts, property distance to metro station or shopping malls and also comparisons for different houses types.
As data analyst, we are keen to provide a customized visualization tool that can reveal all the relationship among the property features--not only can select the ideal house for the client, but all also demonstrate the parameters' relationship.
Selection of Tools
Since this course aims at pursuing the good command of R language, for the display part we will choose R to implement our visualization. To be more precise, we will use R Markdown and the other relevant package like ggplot2. At the data preparation step, we will take advantage of JMP Pro and Tableau as well.
Design Framework
The visualization tool contains 3 main part:
The first part is the main graph with lines linking all the parameter together (e.g. price, area, type etc.). In this part, it might seem very messy since we have thousands of record for the property, which means there are thousands of lines in this graph. Hence, we will provide the filter tool to let the customer select their favor to show their dream house.
The second part is a display area where show the details of selected or filtered information of properties.
The third part is a geographical chart demonstrating the nearest shopping malls, bus stops and MRT stations.
