Data Analysis on New York Housing Prices

Predict housing prices in New York City. Given a dataset containing multiple property features (such as house size, location, number of bedrooms) and historical selling prices, you need to build a predictive model to accurately estimate future property prices. Functions to implement: Analyze the given dataset to identify key factors influencing housing prices. Train a predictive model using an appropriate machine learning algorithm. Estimate the housing prices based on new input data. Test Cases: The data format is as follows: { "features": [ {"size": 850, "location": "Manhattan", "bedrooms": 1}, {"size": 700, "location": "Brooklyn", "bedrooms": 2} ], "prices": [1500000, 1000000] } Provide features for prediction, output the predicted price. Example Input {"features": [{"size": 850, "location": "Manhattan", "bedrooms": 1}], "prices": [1500000]}