housing-monitor

Name: housing-monitor
Availability: InStock
Author: Lumin

Analyze real estate market data and generate charts with Python and matplotlib.

Updated Mar 5, 2026

Search Tags:#charts #python #data-visualization #market-analysis #real-estate #shenzhen #rent-vs-price

Ready to run

npx skills add https://github.com/lumincui/skills --skill housing-monitor

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: housing-monitor
Source: https://github.com/lumincui/skills/tree/main/housing-monitor
Command: npx skills add https://github.com/lumincui/skills --skill housing-monitor

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires matplotlib, numpy, and includes scripts (resource) components.

What problem does it solve?

This Skill helps users monitor real estate markets by collecting data, visualizing trends, and forecasting, reducing manual charting and analysis effort.

Core Features & Use Cases

Automated Data Collection: Pulls data from official sources and trusted platforms to build a consistent market view.
Visualization & Analysis: Generates charts for price trends,成交量, rent, and rent-to-price metrics, with cross-source validation.
Use Case: Example: create Shenzhen market dashboards that compare second-hand and new-home prices, volumes, and rent yield to inform decisions.

Quick Start

Analyze Shenzhen real estate data and generate the latest-month charts using official sources.

Frequently Asked Questions about housing-monitor

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I generate real estate market analysis charts for Shenzhen using Python?▼

You can generate real estate market analysis charts by running Python scripts that use matplotlib to process collected data. The Skill automates data collection from official sources and outputs visualizations for price trends, volumes, and rent metrics.

What is rent-to-price analysis and how does it work for real estate markets?▼

Rent-to-price analysis compares rental income against property prices to evaluate market yield. This Skill calculates this metric alongside price trends and trading volumes, creating visual charts to help identify market forecasts and inform real estate decisions.

Can I use matplotlib and numpy to visualize real estate data for cities other than Shenzhen?▼

Yes, while the Skill is designed for Chinese markets notably Shenzhen, it is adaptable to other cities. It uses Python with matplotlib and numpy to process official data sources and generate visual charts and trend analyses for various real estate markets.

What's the best way to compare second-hand and new-home prices in real estate data visualization?▼

The best way to compare property prices is using automated data visualization that aggregates official sources. This Skill creates dashboards comparing second-hand and new-home prices, volumes, and rent yields with cross-source validation for reliable trend analysis.

Do I need to manually clean official real estate data before visualizing market trends?▼

No, manual data cleaning is not needed. This Skill automatically collects data from official sources and trusted platforms, validates the information across sources, and then processes it with Python to generate charts and reports with clear citations.