Graduation project application of large-screen full-screen visualization system for second-hand housing data set in Chengdu, Sichuan

 Blogger Introduction : Teacher Huang Juhua, author of the books "Getting Started with Vue.js and Mall Development" and "WeChat Mini Program Mall Development", CSDN blog expert, online education expert, CSDN Diamond Lecturer; focuses on graduation project education and guidance for college students.
All projects are equipped with basic knowledge video courses from entry to mastering, free of charge
The projects are equipped with corresponding development documents, proposal reports, task books, PPT, and papers. Templates, etc.

The project has recorded release and functional operation demonstration videos; the interface and functions of the project can be customized, and installation and operation are included! ! !

If you need to contact me, you can check Teacher Huang Juhua on the CSDN website
You can get the contact information at the end of the article

Graduation project application of large-screen full-screen visualization system for second-hand housing data set in Chengdu, Sichuan

I. Introduction

With the advent of the big data era, data visualization has become an important basis for decision-making. This graduation project aims to display and analyze the second-hand housing data set in Chengdu, Sichuan through a visual large-screen full-screen system to help users more intuitively understand the current situation and trends of the Chengdu second-hand housing market, thereby providing a basis for relevant decisions.

2. Data sources and cleaning

The data used in this design comes from the second-hand housing transaction data set in Chengdu, Sichuan obtained from public channels. In the data cleaning stage, we use data preprocessing technologies, such as deduplication, missing value processing, outlier processing, etc., to ensure the accuracy and completeness of the data.

3. Visual large-screen design

The large visual screen adopts a full-screen design to adapt to different display scenarios. The large-screen layout adopts a modular design, allowing users to adjust it according to different needs. The color matching is mainly fresh and elegant, which can not only highlight key data, but also maintain the harmony and unity of the overall visual effect.

4. Visual content display

1. Second-hand house price distribution: The map shows the average price of second-hand houses in various regions of Chengdu. The darker the color, the higher the price. Users can click on an area on the map to view detailed housing information in that area.
2. Popular property recommendation: Based on the attention of the property, transaction volume and other indicators, popular properties are displayed in the form of lists or cards to help users quickly understand the market's popular property information. At the same time, a filtering function is provided so that users can filter out qualified properties according to their own needs.
3. Second-hand house transaction trends: Display the historical data and forecast data of Chengdu’s second-hand house transaction volume through a line chart to help users understand the market transaction trends. At the same time, heat maps are used to display the trading activity in each region to help users gain a deeper understanding of market dynamics.
4. Property feature analysis: Display the keywords, unit type, area, decoration and other characteristics of the property through word clouds, bar charts and other forms to help users understand the property information more comprehensively. Users can view specific property information by clicking on elements in the chart.
5. Regional comparative analysis: By comparing housing prices, transaction volume and other indicators in different regions, the differences and connections between regions are displayed in the form of charts to help users gain a deeper understanding of market dynamics and regional characteristics. Provides area selection function, users can select the area they are concerned about for comparative analysis.
6. Supply and demand relationship analysis: Display the supply and demand relationship of second-hand houses through scatter plots, radar charts and other forms to help users understand the supply and demand balance in the market and provide a basis for investment decisions. At the same time, the supply and demand forecasting function is provided, and users can predict future supply and demand based on historical data.
7. Market hotspot tracking: By analyzing search engine keywords and social media discussion heat, market hotspots and concerns are displayed in the form of heat maps or word clouds to help users capture market changes in a timely manner.
8. Portrait of the home-buying crowd: By analyzing the age, gender, occupation and other characteristics of the home-buying crowd, the portrait of the home-buying crowd is displayed in a chart to help users more accurately grasp the needs of the target customer group. Provides customer group analysis function, users can formulate corresponding marketing strategies based on different customer group characteristics.
9. Policy impact analysis: By analyzing the impact of policies on the second-hand housing market, policy effects and policy trends are displayed in charts to help users better grasp market trends and policy opportunities.
10. Risk assessment and early warning: Display the risk level and early warning information of the second-hand housing market through risk matrix diagrams, heat maps and other forms to help users identify and avoid potential risks. Provides a risk reminder function. When abnormal conditions occur in the market, the system will automatically prompt users.

5. Interaction design and implementation

In order to ensure the smoothness and convenience of the user experience, we have carried out the following interactive design for the large visual screen:

1. Support full-screen switching: Users can switch the large screen to full-screen mode by clicking the full-screen button for a more immersive visual experience.
2. Supports data filtering: Users can filter and sort data through filter conditions to find interesting data and information more quickly.
3. Support dynamic updates: The system can regularly obtain the latest data from the data source and update it to ensure that users can obtain the latest market information at any time.
4. Supports multi-device adaptation: The system can adaptively adjust according to the screen size and resolution of the device to ensure good visual effects on different devices.
5. Support data export: users can export the data of interest to Excel or PDF format for saving and sharing.
6. Intelligent recommendation function: The system can intelligently recommend relevant housing information and analysis results based on the user's browsing history and preferences to improve the pertinence of information acquisition.
7. Multi-user collaboration: Support multiple users to view and operate the large visual screen online at the same time to achieve team collaboration and information sharing.
8. Provide help documentation: Provide users with detailed operating instructions and FAQs to help users better use the system.
9. Support voice interaction: users can operate the system and query data through voice commands to improve ease of use.
10. Provide data visualization customization function: users can customize the chart type, color, font, etc. of data visualization to meet individual needs.

6. Conclusion and outlook

This graduation project displays the visual results of the second-hand housing data set in Chengdu, Sichuan through a large-screen full-screen visualization system to help users intuitively understand the current situation and trends of the market and provide strong support for relevant decisions. In the future, the performance and interactive experience of the system can be further optimized to improve the real-time and accuracy of data to meet the needs of more users. At the same time, you can consider introducing more data analysis methods and machine learning algorithms to conduct more in-depth analysis and mining of data to discover more market rules and trends and provide users with smarter and more personalized services.

---

As a graduate, you can design a visual large-screen full-screen system based on the second-hand housing data set in Chengdu, Sichuan. This application can help people better understand the trends and dynamics of the second-hand housing transaction market in Chengdu. Here are some design suggestions:

1. Data source: You can obtain relevant data on second-hand housing transactions in Chengdu from different websites or institutions, such as house price, area, transaction time, etc. Ensure data authenticity and reliability.

2. Data visualization: You can use different visualization tools and techniques, such as line charts, bar charts, heat maps, etc., to display data visually. At the same time, you can also add dynamic effects and interactive functions, allowing users to freely switch between different views and time periods.

3. Map display: Combining Chengdu's map with second-hand housing transaction data can better display housing prices, supply and demand in different regions, etc. You can use map visualization tools, such as Amap, Baidu Map, etc., to display data on the map.

4. User settings: You can add user settings, such as allowing users to set different filtering conditions and sorting methods based on their needs and interests. This can improve the user experience and better meet the needs of different users.

5. Data reporting: You can add data reporting functions, such as allowing users to generate different data reports and analysis results, which can better help users understand the trends and dynamics of the second-hand housing market in Chengdu, and can also help industry insiders make more accurate decisions. predictions and decisions.

In short, a large-screen full-screen system for visualizing second-hand housing data in Chengdu can not only help people better understand the market situation, but also provide powerful decision-making support for related industries, which has great application value.