Design and implementation of python crawler Yunnan Kunming hotel data visualization large-screen full-screen system (django framework)

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University student Python project report on the design and implementation of a large-screen full-screen system for data visualization in Kunming, Yunnan (Django framework)

1. Research background and significance

With the rapid development of tourism, the hotel industry is an important part of the tourism industry, and its operational data is of great significance for improving hotel service quality, optimizing resource allocation, and formulating market strategies. As a famous tourist city in China, the hotel industry in Kunming, Yunnan Province is developing rapidly, but the utilization and analysis of hotel data are currently insufficient. Therefore, this research aims to use Python's Django framework to design and implement a large-screen full-screen data visualization system for hotels in Kunming, Yunnan. Through this system, the hotel's operational data can be visually displayed, providing decision support for hotel managers and related departments, and also helping to improve the hotel's service quality and market competitiveness.

2. Research status at home and abroad

At present, there have been extensive research and applications in the field of data visualization at home and abroad, but there are relatively few studies on hotel data visualization in specific regions (such as Kunming, Yunnan). Most of the existing hotel data visualization systems focus on macro-level data analysis and lack detailed research on specific hotels and customers. In addition, existing systems also have certain limitations in data display and user interaction. Therefore, this research will design and implement a more refined, user-friendly large-screen full-screen system for data visualization based on the actual needs of hotels in Kunming, Yunnan.

3. Research ideas and methods

This research will adopt the following ideas and methods:

1. Data collection: Obtain relevant data of Kunming hotels in Yunnan through crawler technology or API interface.
2. Data cleaning: Preprocessing of data, including deduplication, missing value filling, etc.
3. Data analysis: Use statistical methods to analyze the collected data.
4. Data visualization: Use the Django framework combined with front-end technologies (such as HTML, CSS, JavaScript, etc.) to implement a large-screen full-screen data visualization system.
5. System testing and optimization: Test the system and optimize it based on the test results.

4. Research content and innovation points

The main contents of this study include:

1. Backend function requirements analysis: Conduct a detailed analysis of the backend functions required by the system, such as data storage, data processing, etc.
2. Front-end functional requirements analysis: Conduct a detailed analysis of the front-end functions required by the system, such as data display, interaction design, etc.
3. System design and implementation: Based on Django framework and front-end technology, design and implement a large-screen full-screen data visualization system.

The innovative points of this study are:

1. For the first time, a large-screen full-screen data visualization system was designed for a hotel in Kunming, Yunnan.
2. Use Python's Django framework to implement system development to ensure system stability and scalability.
3. The system design is simple and intuitive, allowing users to quickly obtain hotel operation information.
4. Provides rich interactive functions to enable users to conduct data analysis and decision-making more conveniently.

5. Backend functional requirement analysis and front-end functional requirement analysis

Backend functional requirements analysis:

1. Data storage: Establish a database model to store various hotel-related data.
2. Data processing: Clean, transform and aggregate the collected data to meet the needs of front-end display.
3. Data analysis: Provide basic statistical analysis functions, such as hotel occupancy rate statistics, customer behavior analysis, etc.
4. Data export: Supports exporting analysis results in the form of charts or reports to facilitate further analysis and decision-making by users.

Front-end functional requirements analysis:

1. Data display: Display various hotel-related data through visual means such as charts and maps.
2. Interaction design: Provide a friendly user interface and interaction design to facilitate users to operate and view data.
3. Multi-screen adaptation: Ensure that the system can display and run properly on screens of different sizes and resolutions.
4. Real-time update: Supports real-time update and dynamic display of data to ensure that users can obtain the latest hotel operation information in a timely manner.

6. Research ideas, research methods, and feasibility

This study will adopt a research method that combines theory and practice, first conducting theoretical analysis and system design, and then conducting system development and testing. It is technically and economically feasible. As mature development languages ​​and frameworks, Python and Django have abundant resources and extensive developer community support. In addition, with the development of the hotel industry and the popularization of data visualization technology, related enterprises and departments have an increasing demand for such systems. Therefore, this research has high economic and social value.

7. Research progress arrangement

1. The first stage (1-2 months): Collect relevant data from hotels in Kunming, Yunnan, and conduct data cleaning and analysis.
2. The second stage (2-3 months): Design and implement the back-end and front-end functions of the large-screen full-screen data visualization system.
3. The third stage (1 month): Test and optimize the system to ensure the stability and reliability of the system.
4. The fourth stage (1 month): writing the thesis and preparing for the defense.

8. Thesis (design) writing outline

1. Introduction: Explain the research background and significance, domestic and foreign research status, and research purpose and tasks.
2. Research methods and theoretical basis: Introduce the methodology and related theories used in the research.
3. Data collection and processing: Describe the sources of data, the collection process, and processing methods.
4. System design and implementation: Describe in detail the back-end function design and front-end function design of the system, as well as the implementation process.
5. System testing and optimization: Test the system and analyze the test results, and make optimization suggestions.
6. Conclusion and outlook: Summarize the research results and point out the limitations of the research and future research directions.
7. References: List relevant literature cited in the paper.
8. Appendix: Contains system source code, test reports and other additional materials.

9. Main References
[References related to this study are listed here]

10. Expected results

This research is expected to achieve the following results:

1. Completed a large-screen full-screen data visualization system for hotels in Kunming, Yunnan, which can intuitively display the hotel's operational data and customer behavior.
2. Provide a detailed system design and implementation report, including backend function design, front-end function design, system testing and optimization, etc.
3. Publish a high-quality academic paper describing the research background, methods, results and conclusions of this study.
4. Provide decision support for hotel managers and related departments to improve the hotel's service quality and market competitiveness.

11. Research budget

This research funding budget mainly includes the following aspects:

1. Data collection and processing fees: fees for purchasing relevant data sets or API interfaces.
2. System development and testing costs: costs for purchasing infrastructure such as servers and domain names, as well as other costs that may be incurred during the development and testing process.
3. Academic paper publication fees: used to pay for academic paper publication fees, review fees, etc.
4. Other expenses: including attending academic conferences, purchasing relevant books, etc.

12. Research team composition and division of labor

This research team consists of the following members:

1. Supervisor: Responsible for guiding the entire research process and providing academic support and advice.
2. Project Leader: Responsible for the planning, organization and coordination of the entire project.
3. Back-end developer: Responsible for the development and maintenance of the system's back-end functions.
4. Front-end developer: Responsible for the development and maintenance of the front-end functions of the system.
5. Data Analyst: Responsible for data collection, cleaning and analysis.
6. Test Engineer: Responsible for system testing and optimization.

Each member will work together to complete this research based on their respective professional backgrounds and skills.

13. Risk assessment and countermeasures

The risks this research may face include technical risks, data risks, market risks, etc. To address these risks, we will take the following measures:

1. Technical risks: Choose mature development languages ​​and frameworks to ensure the stability and reliability of the technology; conduct regular technical training and exchanges to improve the team's technical level.
2. Data risk: Ensure the legality and accuracy of data sources; back up and encrypt data to prevent data leakage and damage.
3. Market risk: Pay close attention to market dynamics and policy changes, adjust system functions and design in a timely manner; actively promote system applications and expand user groups and market share.

14. Conclusion and outlook

This research aims to use Python's Django framework to design a data visualization large-screen full-screen system for hotels in Kunming, Yunnan. The system will provide hotel managers and relevant departments with intuitive data support, helping to better understand the hotel's operations and customer behavior. Through this research, we hope to promote the application and development of data visualization technology in the hotel industry and provide more refined data support for relevant enterprises and departments. In the future, we will continue to pay attention to market dynamics and technology development trends, constantly improve and optimize system functions and designs, and provide users with better services and experiences. At the same time, we also hope that this study can provide certain reference and reference value for hotel data visualization research in other regions.