NYC Real Estate Market Visualization
Did you ever wonder where the most popular neighborhoods are in New York City? Or which neighborhoods are the most expensive? Perhaps you’re curious about the types of properties people are buying and their median price? I had these questions in mind when I set out visualize the NYC real estate market
About the data source
The data is found from the NYC Department of Finance Rolling Sales Data.
NYC Department of Finance Rolling Sales Data contains sales records dating back to 2003 that are updated monthly. For this particular project, I used sales records from the time period of March 2017 to February 2018. The variables I focused on were Boroughs, Neighborhoods, Building Types, Sales Prices and Sales Date. I also cleaned out all the zero sales prices due to transfer of ownership. In addition, I cleaned out tax class 3 and tax class 4 properties that are mostly made up of office buildings, gas stations, factories, etc.
For detailed coding and data cleaning process. See my GitHub repository by following this link:
Now that we have our data set with residential property sales for the past 12 month, let us discover what it looks like!
Exploring the Shiny App
Here is the link to my Shiny App. Feel free to explore for yourself in any neighborhood or building types that interests you:
Mapping out the entire year worth of transactions amount by neighborhood reveals the answer to our first question.
- The most popular neighborhood in Manhattan is the Upper East side!
Close to 5000 properties were sold during the past 12 months, which is 5 times more than Midtown, the location in second place with a transaction amount of 1015. That indicates that the Upper East Side is the most sought after in Manhattan by far. This can be due to a number of the neighborhood features, including several reasons from fancy restaurants, shopping experiences on Madison Avenue, and the proximity to many cultural museums and beautiful Central Park.
But what kind of apartments are buyers trying to buy? Let's take a look at the pie chart for sales breakdown by building types:
- 80% of the sales are for elevator apartment coops and elevator apartment condos.
For frame of reference, elevator apartments buildings are the majority of buildings types in Manhattan
When is the peak season for NYC real estate market? The bar graph will give you a trend analysis through out the year. We can see that
- Most of the sales happen during the summer.
This makes sense since summer time is the best time for most buyers to go out and explore options without the worry of the cold or possibly the commitment to their children’s school activities.
What about price?
- Flatiron/SoHo/Tribeca turned out to be the most expensive neighborhood.
Possible reasons for for that are its proximity to the action, Madison Square Park, and 5th Ave, and many office buildings. While SoHo is located at the lower side of Manhattan, filled with cute boutiques, high-end shopping and restaurants. Tribeca is slowly turning from its old industrial buildings to residential lofts that are located alongside the Hudson River with many trendy boutiques and restaurants.
Why the change? Take a look at the pie chart we find our answer.
- Luxury rental buildings are driving the median sales price up for these neighborhoods to accommodate the buyers interested in living the New York Dream.
Now we have take a closer look into the New York City real estate market. What is happening in the other 4 boroughs? I created a heat map for the transactions for all 5 boroughs. The size of the bubbles are according to the sales price.
We can see that--not surprisingly--most of the high sale price transaction still took place in Manhattan, especially around Central Park and downtown. But some neighborhoods in other boroughs are on the rise. As in Williamsburg in Brooklyn and Long Island City/Flushing in Queens. Large sales are also taking place in Bronx.
You can check all the detail records and filter by boroughs and sales price range on the data table on the third tab.
There is still so much that can be done with this data set and a lot more to find. In the future, I will like to enhance the apps to explore additional aspect including:
- Adding more metrics into the sales price like the per square footage price for better comparison among building types and neighborhoods.
- Including sales record dated 3 years back to better understanding the price trends, for example, YoY, MoM, QoQ comparison.
- Applying machine learning to predict future sales price and spot good investment opportunity.