Visualization of Real Estate Price Trends

This project analyzes and visualizes price trends of used real estate in major areas of Tokyo, Chiba, Kanagawa, Saitama, Osaka, and Aichi, categorized by floor plan and age.

We utilized the "Real Estate Information Library" from the Ministry of Land, Infrastructure, Transport and Tourism as our data source to create a dashboard that allows users to intuitively understand price fluctuations and market trends in each region.

By visualizing trend data using Python, we clearly illustrate patterns and movements in the real estate market.

View Trend Data

Background and Objectives

In recent years, the real estate market in urban areas has experienced significant fluctuations. Particularly in the Tokyo metropolitan area, an increasing number of individuals and companies are considering real estate purchases and investments. However, since real estate price trends vary by location, floor plan, and building age, obtaining useful information as a concrete basis for decision-making can be challenging.

This project aims to achieve the following objectives by clearly showing historical price fluctuations of used real estate in each region:

• Understanding Market Trends:
• Visualize price trends by area, floor plan, and age to understand market movements and price fluctuation patterns.
• Supporting Decision-Making:
• Provide data-driven insights to those considering real estate purchases or investments to support their decision-making process.

Analysis Content and Functions

• Price Analysis by Area:
• Analyze trends in used real estate prices based on regional characteristics across Tokyo, Chiba, Kanagawa, Saitama, Osaka, and Aichi.
• Comparison by Floor Plan:
• Compare price trends across different floor plans (1K, 1LDK, 2DK, 3LDK, etc.) to clarify changes in property value and market demand.
• Age-Based Analysis:
• Display real estate price trends by building age to visualize long-term market movements and historical fluctuation patterns.
• Interactive Dashboard:
• Provide a dashboard where users can view detailed price information and graphs in real-time by selecting specific areas, floor plans, and building ages.
• Visualization Using Python:
• Leverage Python's data analysis library Pandas and graphing library Matplotlib to clearly display price trends and patterns through intuitive graphs and charts.

Data Source

The data used in this project comes from the "Real Estate Information Library" provided by the Ministry of Land, Infrastructure, Transport and Tourism. We conduct accurate market analysis based on this highly reliable official data.

Future Prospects

• Data Expansion:
• We plan to incorporate the latest market data and additional area/property information to enable more detailed analysis. We also aim to implement automatic updates by integrating with the API of the Ministry's "Real Estate Information Library."
• Predictive Analytics:
• We intend to develop functionality that predicts future real estate prices based on historical trends, incorporating machine learning models to provide valuable insights for investment decisions.