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Weifang City Property Transaction Data
Data Science and Analytics
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About
This collection provides a detailed snapshot of the secondhand residential property market within Weifang City, China. It is designed to facilitate in-depth analysis of regional real estate trends, feature correlations, and pricing dynamics. The dataset captures essential metrics such as total price, unit price per square metre, floor level, and specific property attributes like layout and decoration status, making it highly valuable for predictive modelling and statistical studies related to urban housing economics.
Columns
The dataset includes 16 features detailing various aspects of the properties:
- id: A numerical identifier for each listing.
- title: A brief introduction or summary of the property listing.
- total_price: The overall price of the second-hand house, measured in units of 10,000 Chinese yuan.
- unit_price: The price per square metre in yuan.
- square: The area of the house, measured in square metres.
- size: The layout description of the house or apartment (e.g., number of bedrooms, halls, kitchens, and bathrooms).
- floor: The storey level of the property.
- direction: The orientation of the housing unit (e.g., South, North).
- type: The specific house type (e.g., slab building, slab-tower combination).
- district: The region or administrative area within Weifang City.
- nearby: Information regarding the nearby neighbourhood or street.
- community: The name of the housing community or complex.
- decoration: The status of the interior decoration (e.g., fine decoration, simple decoration).
- elevator: A binary indicator specifying whether an elevator is available.
- elevatorNum: The proportion or ratio of elevator households (e.g., one elevator for two households).
- ownership: The classification of ownership (e.g., commercial housing).
Distribution
The data file contains sample information extracted via Python web scraping methods. The collection comprises 18,339 sample data records, encompassing 16 distinct characteristics for each property. The data reflects a single capture date, providing metrics from the early part of 2023. The file is approximately 4.44 MB.
Usage
Ideal applications for this data include:
- Data cleaning and preparation exercises.
- Statistical data analysis and visualisation of market trends.
- Machine learning models, particularly for predicting the relationship between house price and area.
- Investigating correlations between various property characteristics.
- Analysing housing distribution across different districts within Weifang.
Coverage
The geographic scope is limited to Weifang City, China. The temporal coverage is a static snapshot, with all data sourced as of 15 February 2023. The dataset focuses exclusively on second-hand residential properties listed on the Lianjia platform.
License
Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)
Who Can Use It
Intended users include:
- Data Scientists and Machine Learning Engineers: For building and testing regression models to predict property values based on features like size and location.
- Urban Planners and Real Estate Analysts: To study pricing structures, regional market distribution, and feature preferences (like decoration status or elevator availability).
- Students and Educators: For educational purposes, specifically in data analysis, visualisation, and introductory data preparation projects.
Dataset Name Suggestions
- Weifang Secondhand Housing Market Metrics (2023)
- Weifang City Property Transaction Data
- China Real Estate Features and Pricing
- Lianjia Weifang Secondhand House Data
Attributes
Original Data Source: Weifang City Property Transaction Data
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