Across 4881 NYC Airbnb listings analysed (capped at $500/night), the median nightly price is $100. Manhattan commands the highest borough median at $140. Entire-home listings carry a median premium of $85 over private rooms, making room type the single largest price driver. OLS regression confirms these patterns persist after controlling for availability,

minimum nights, and review count simultaneously.

Manhattan leads all boroughs with a median nightly price of $140, while Bronx is the most affordable at $65 — a gap of $75. Manhattan's premium likely reflects both its central location and the concentration

of entire-home listings in high-demand neighbourhoods. Borough selection is the first major lever for guests managing their accommodation budget.

Entire home/apartment listings have a median nightly price of $155, versus $70 for private rooms — a premium of $85 per night. Shared room listings are the most affordable but show the narrowest spread,

suggesting a price ceiling imposed by guest willingness-to-pay for non-private accommodation. The long upper tails on entire-home and private-room boxes reflect premium boutique

listings skewing each distribution rightward.

Tribeca ranks as the priciest neighbourhood with a median nightly rate of $300. Premium neighbourhoods tend to cluster in Manhattan and parts of Brooklyn, reflecting

proximity to tourist attractions, dining, and transit. Guests and investors can use this ranking to benchmark specific listings against their

local micro-market median rather than the broader borough average.

Among numeric features, Host Listing Count shows the strongest correlation with

price (r = 0.094). Most predictors show weak to moderate pairwise correlations, suggesting limited

multicollinearity issues in the regression model. Reviews_per_month and number_of_reviews are positively correlated, as expected,

since both capture cumulative guest activity over time.

After controlling for all predictors simultaneously, 'Room Type: Shared room' has the largest independent effect on price ($-119.9 per unit). 4 predictors are associated with higher prices and 5 with lower prices in this model. Room type dummies typically dominate — an entire-home listing commands a substantial

premium over the private-room baseline even within the same borough. Coefficients should be interpreted as partial effects: the price change for a

one-unit increase in each predictor, holding all other variables constant.

Listing prices are not uniformly distributed across NYC geography — Manhattan listings

cluster at higher price points than outer borough listings at equivalent latitudes. Dot size encodes nightly price, making price hotspots immediately visible as

clusters of large dots in Midtown and Lower Manhattan. Brooklyn shows a wide spatial spread with pockets of premium pricing in

neighbourhoods like DUMBO and Williamsburg near the Manhattan border.

Staten Island has the highest average listing availability at 181.8 days per year. Higher availability in some boroughs may reflect a lower demand relative to supply,

professional hosts running multiple listings, or seasonal booking patterns. Cross-referencing availability with median price reveals whether scarcity (low

availability) correlates with premium pricing at the borough level.

This table provides a single-page market snapshot for each NYC borough. Median price, average availability, average review count, and total listing count

allow direct apples-to-apples comparison across the five boroughs. Listing Count reflects qualifying listings per borough after price-cap filtering.