Real Estate Market Data Analysis: Correlation Between Housing Prices, Living Space, Building Age and Location

The real estate market plays a significant role in economic activity, with housing price fluctuations affected by a variety of factors. Understanding these factors is crucial for investors, developers, and policymakers. This study analyzes the relationship between housing prices and variables such as living space, age of construction, age of renovation, and geographic location using data visualization techniques. The results indicate a positive correlation between living area and housing prices, and show that the distribution of building and renovation ages highlights peak periods of construction and renovation activity. In addition, location has a significant impact on housing prices, which may be related to factors such as land prices, transportation convenience, etc. This study collects data and performs statistical analysis to present and interpret the data through data visualization techniques. The findings suggest that house prices are positively correlated with living area, the distribution of building and renovation ages follows a specific periodic pattern, and location has a significant impact on house prices. This study offers a new perspective on the dynamics of the real estate market and provides valuable insights for guiding investment decision and shaping policy.