Data Study on Real Estate Sales in New York City

Posted on May 7, 2018
The skills the author demoed here can be learned through taking Data Science with Machine Learning bootcamp with NYC Data Science Academy.
The most recent version of this app is accessible onlineΒ here, while its source code may be found here.

Introduction

This app is a visualization tool for examining real estate sales in New York City, drawing on data published by the City of New York, availableΒ here.Β The data, which cover the years 2003-2015, include a range of variables, including price, size, category of building, location, and date of sale.

Data

The app plots sales from this data on a map to facilitate exploring the connections, in particular, between time, location and price. The following screenshot displays a number of its features:

Data Study on Real Estate Sales in New York City

A screenshot displaying some of the features of this app (click for a larger image)

Data Findings

As can be seen, the main panel of the app consists of a street map of New York City (sourced from theΒ Open Street MapΒ project), with dots plotted on it in varying sizes. Each of these dots represents a single property sale, with blue dots corresponding to residential properties and red ones to non-residential properties. (Note that "property" here is not synonymous with "building": many property sales are of single condominium units in large apartment buildings.)

The relative size of these dots is set by the second drop-down menu on the left-hand sidebar, labeled Weight by. By default, they are set to a constant size (relative to each other), which is a good format to give an overview of the overall volume and concentrations of sales. Alternatively, however, their sizes can be set to vary in proportion with some property of the sale.Β In the illustration above, for instance, they are scaled by price, with larger dots corresponding to greater prices. They can be scaled instead by square footage, or by price per square foot*.

App Instructions

Clicking on a particular dot brings up a pop-up bubble displaying salient data points about the sale it represents: address, date, price, and square footage. (Note that all of these data points are displayed when one clicks on a dot, regardless of whether they are reflected in the dots' scaling.) Clicking again will banish this bubble.

The map may be zoomed in or out via the + and - buttons in its top left corner. The area shown can be changed by clicking the map and dragging it as desired. The adjustable 'slider' beneath the map displays the range dates for which sales are plotted. By default, this range is set to thirty days, beginning with the date of the first sale in the loaded dataset, but it can be adjusted by moving the sliding buttons to the endpoints of the date range one is interested in.

Alternatively, one may click on the slider to the right or left of the selected range, which keeps the range at the existing size, while 'jumping' it to the point clicked. Finally, clicking the play button at the bottom right of the slider causes the selected range to automatically progress from left to right until it has reached the end of the dates available. While this is progressing, the button may be clicked again to pause it.

*All references to "square footage" here denoteΒ gross square footage, meaning total floor space of a property.

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