New York Housing Prices
We imagine that a firm is looking into the housing prices in New York to get an idea of which boroughs are growing fastest, and what that growth is projected to be. This project was completed by me end to end, from data collection to analysis.
Please check out my GitHub for the source code!
Data Collection
Data was fetched from the New York Department Of Finance's API, then saved as a csv for later use.
Data Cleaning
Data was cleaned and inspected so that there were no nans, invalid inputs, blanks, or variances in formatting.
Exploratory Data Analysis
The average sale price is given per neighborhood, but we wish to calculate which borough as a whole has the fastest growing average price of sold houses, so after averaging over all the neighborhoods in an borough, we plot the results, looking at both the changes in price, as well as the percent increase in sales prices.
The graphs tell us a few things, first, that all boroughs have an increasing average sale price in the long run, but also very interestingly, Manhattan is far more volatile, and during certain years, even has a negative change in average sale price. We wish to analyze the fastest-growing borough, and visually it appears to be Brooklyn, but for the sake of thoroughness, we will numerically print the average growth rate of all boroughs.
From this table, we can see that our suspicions were correct, although all boroughs sport a rather impressive growth rate!
With our eyes now set on Brooklyn, we will attempt to predict future prices. To do this we train a linear regression algorithm, then ask it to predict the price in 2024, which yields:
Our model tells us that if our theoretical company is looking to invest in properties, the best place to look first would be Brooklyn, and if they were holding properties and looking to sell next year, on average, they could expect prices to be about 6% higher next year.
