We have recently been involved in buying Nova Scotia real estate and we’ve had to analyse the market to look for criteria we wanted. However we found the real estate broker websites in the Nova Scotia area generally did not have enough filtering criteria to narrow down the exact requirements we had.
Therefore we felt we need to write our own charting tool to quickly visualise and compare different properties attributes.
|Price||property asking price|
|Price Per Sq Ft||property price divided by livable internal living space (sq ft)|
|Living Space||internal living space (sq ft)|
|Land Size||external land that coming with the property (sq ft)|
|Miles from Centre||physical distance from|
|Walkscore||properiety walk score (taken from real estate broker website). 100 = very walkable and 0 = not|
|Transitscore||public transport score (taken from real estate broker website). 100 = very easy to get around and 0 = not|
|Bedrooms||number of bedrooms|
|Bathrooms||number of bathrooms|
|Days on Market||important in a buyers market with lots of inventory - can focus on longest sitting properties|
|Building Age||Age of building in years - dont want a maintanence headache for rental properties.|
You can access the live demo version of the Real Estate Market Visualisation tool or just look at the following screenshot:
So how do you use it ?
The tool instructions are relatively straightforward:
1. Select vertical and horizontal chart axis
2. Move mouse over chart and click on any blue data point to display quick property detail
3. Then click MLS link (beneath chart) to see property listing
4. Repeat from point 1 for different axis comparisons
The result plots one property attribute against the second property attribute and displays the graph. Each data point on the chart is a property.
Please note: although all the URL were originally working, over time the URL links to original listings are often no longer available on the real estate brokers website (for example if the house has been sold or taken off the market).
What did we have to do to build the tool ?
1) Define a specification of the property attributes we care about
We wrote an IT focused detailed specification to read the HTML for an individual property listing and define exactly which property attributes to extract into a spreadsheet format. We simply choose Comma Seperated Values (CSV) spreadsheet format as the output because it is very simple to read and edit.
2) Write a website reader to download all property attributes
Gave the above specification to an IT contractor on an outsourcing site. This work was ultimately outsourced on upwork.com but anything similar would be fine.
The contractors job is then to take a download snapshot of all housing listing from a target real estate website, saving all required fields into one CSV spreadsheet for the current download. The real estate website is currently Remax Canada at www.remax.ca. Currently no user login is required for the website. The delivery was a Python program (with specified .py modules) executed as a command line interface. The website features main listing (of all available houses) and individual detail listing (for each house), both of which will need to be scrapped to produce the CSV spreadsheet. We ended up calling this part the “house scrapper” CSV code.
3) Write a simple webpage to read the CSV spreadsheet and nicely visualise the data into a graph. You can easily review this code if you like by looking at the Real Estate Market Visualisation webpage, then right clicking on “View Source”.
How did it go?
Overall the tool implementation was a relatively cheap and quick success. The approximately cost was about $100 to hire the programmer who wrote the house scrapper that downloads the CSV data source. Then about 12 hours total effort of our own time to write the house scrapper spec (4 hours) and create/fully test the HTML webpage (8 hours) that uses the CSV data.
This is not exactly an out of the box solution for us, but it was worth it because it helped us visualise the market nicely in graphs. Ultimately we made a decision and bought a house from it, so it was definitely worth the relatively cheap money and effort put into it. This could be extended to other markets were other websites are not as good. However this might not be necessary in the US if websites such as Trulia and Zillow do everything you need.
However its good overview of how to roll your own Real Estate Market Visualisation tool, if you end up searching for real estate in a market that doesn’t have the full analysis tools you want.