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Shanghai, as a city with a high demand for rental housing, rents and the factors affecting rents are a concern for many individuals. This paper analyzes Shanghai Lane house rental in 2021. Using data from Kaggle, key variables such as square meters, location, latitude and longitude, bedrooms, living rooms, bathrooms, lofts, outdoor spaces, and underfloor heating were examined to understand their impact on rents. Using multiple linear regression and stepwise regression methods, the study identified the important factors that influence rental prices. Correlation analysis and multiple regression models revealed a strong relationship between rent and variables such as square meters, bedrooms, living rooms, dining rooms and bathrooms. The R-square values of the models were 0.689 and 0.360, respectively, indicating that these variables collectively explain a significant portion of the variation in rents. It highlights the positive impact of neighborhoods, living-dining rooms, and outdoor spaces on rents, while lofts negatively affect rental prices. Providing valuable insights for policymakers, real estate professionals, and urban planners, this comprehensive analysis greatly contributes to the understanding of urban housing markets, especially in fast-growing cities such as Shanghai.
Jiayin Li (Fri,) studied this question.