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Python project proposal report for college students on the design and implementation of large-screen full-screen system for data visualization in Jinan, Shandong, food stores (Django framework)
1. Research background and significance
With the development of the economy and the improvement of people's living standards, the catering industry has gradually become an important economic industry. Jinan, Shandong Province, is a famous historical and cultural city in China. Its unique geographical location and rich history and culture have given birth to many gourmet shops with local characteristics. In order to better understand the distribution, operating conditions and market trends of Jinan gourmet stores, it is of great significance to design and implement a large-screen full-screen system for gourmet store data visualization based on Python and Django frameworks.
Through this system, key information such as the number, type, geographical location, and operating conditions of Jinan gourmet shops can be visually displayed, providing decision support and information services to government departments, catering companies, and consumers. At the same time, the system can also promote the dissemination and promotion of Jinan's food culture and enhance the visibility and competitiveness of Jinan's catering industry.
2. Research status at home and abroad
At present, certain results have been achieved in the field of data visualization at home and abroad, but there are still deficiencies in data visualization systems for specific regions and industries. Data visualization systems for the catering industry are mostly concentrated in large chain catering companies, while there are relatively few data visualization systems for local specialty food stores.
On the technical side, Python is a popular programming language with powerful capabilities in data analysis and visualization. As a mature web development framework, Django provides a wealth of functions and tools that can simplify the web development process and improve development efficiency. Therefore, it is feasible to design and implement a large-screen full-screen data visualization system for Jinan food stores based on Python and Django frameworks.
3. Research ideas and methods
This research will use a system design method, combined with the Python programming language and Django framework, to design and implement a large-screen full-screen data visualization system for Jinan gourmet stores. The specific research ideas include: four steps: demand analysis, system design, system implementation and system testing. Understand user needs and actual scenarios through demand analysis, and clarify the function and performance requirements of the system; design the overall architecture, functional modules and database structure of the system through system design; use the Python programming language and Django framework for system coding and development through system implementation; Conduct functional and performance testing of the implemented system through system testing to ensure the stability and availability of the system.
4. Research content and innovation points
Research content: The main contents of this research include collecting, processing, storing and displaying Jinan food store data; designing and implementing a feature-rich and highly interactive data visualization large-screen full-screen system; testing and evaluating the system.
Innovation point: The innovation point of this study is to design and implement a large-screen full-screen system for food store data visualization based on the Django framework for Jinan for the first time; using modular design to improve the maintainability and scalability of the system; through intuitive data display and Interaction design improves user experience and satisfaction.
5. Backend functional requirement analysis and front-end functional requirement analysis
Backend functional requirements analysis: The backend needs to realize the collection, cleaning, storage and management functions of Jinan gourmet store data. Specifically, you need to write a crawler program to crawl food store data from relevant websites, clean and process the data and store it in the database. At the same time, the backend also needs to provide a data interface for the front end to call.
Front-end functional requirements analysis: The front-end needs to realize the visual display and user interaction functions of Jinan food store data. Specifically, you need to use a chart library (such as ECharts) to display the data in the form of charts, including key indicators such as the number of food stores, type distribution, and geographical location. At the same time, the front end also needs to provide interactive functions such as filtering and search to facilitate users to conduct in-depth analysis and mining of data.
6. Research ideas, research methods, and feasibility
Research idea: This research will follow the basic process of software engineering, that is, the four stages of demand analysis, system design, system implementation and system testing for research and development. In each stage, corresponding research methods and tools will be used to work.
Research methods: This study will use literature review, case analysis, system design and other methods for research. Understand the current research status and development trends in related fields through literature review; understand actual needs and application scenarios through case analysis; realize the function and performance requirements of the system through system design.
Feasibility: This study is technically and economically feasible. The Django framework provides a wealth of functions and tools that can simplify the Web development process; the Python language is simple and easy to learn, reducing development difficulty and costs. At the same time, with the development of technology and the growth of the open source community, related development costs are gradually decreasing. In addition, the food store data visualization system has a wide range of application prospects and market demands, providing a good market environment and application prospects for the implementation of this study.
7. Research progress arrangement
This research plan is divided into the following stages: requirements analysis (1 month), system design (2 months), system implementation (3 months), system testing (1 month), and thesis writing (1 month) . The entire research plan is expected to take eight months to complete.
8. Thesis (design) writing outline
- Introduction: Explain the research background and significance, domestic and foreign research status, and research purpose and tasks.
- Requirements analysis: Conduct detailed requirements analysis on the back-end and front-end functions of the system.
- System design: Based on the requirements analysis results, design the overall architecture, functional modules and database structure of the system.
- System implementation: Describe the development environment, key technologies and implementation process of the system.
- System testing: Carry out functional and performance testing on the implemented system and display the test results.
- Conclusion and outlook: Summarize the research results and shortcomings, and propose future research directions and improvement measures.
- References: List references relevant to this study.
9. Main references
[References related to this research are listed here] such as Django framework tutorials, books and papers related to data visualization, etc. At the same time, you can refer to research literature and technical documents in the fields of computer science and data visualization to gain an in-depth understanding of the knowledge and technical background in related fields.
10. Expected results
Through the design and implementation of this study, the following results are expected to be achieved:
- System design and implementation : Successfully designed and implemented a large-screen full-screen system for Jinan food store data visualization based on Python and Django frameworks. The system can run stably and meet the basic needs of users.
- Data visualization effect : Through the system's data visualization function, users can intuitively understand key information such as the distribution, quantity, and type of Jinan food stores, improving the efficiency of data analysis and decision-making.
- User interactive experience : The system provides a friendly user interactive interface and rich interactive functions, such as filtering, searching, etc., to facilitate users to conduct in-depth analysis and mining of data, and improve user experience and satisfaction.
- Technical documents and reports : Write detailed technical documents and research reports to record key information such as system design ideas, implementation processes, test results, etc., to provide valuable reference for subsequent research and development.
11. Research value and application prospects
The large-screen full-screen system for data visualization of Jinan gourmet stores designed in this study has important research value and application prospects. Specifically:
- Research value : By designing and implementing such a system, the development and application of data visualization technology can be further promoted, and new data visualization methods and tools can be explored and practiced. At the same time, this system can provide practical experience and case references for research in related fields, and promote the development and progress of related disciplines.
- Application prospects : With the continuous development of tourism and people's pursuit of food, the demand for data visualization of local specialty food stores will continue to increase. The system can not only be applied to gourmet shops in Jinan, but can also be expanded to other cities and regions to provide decision support and information services to governments, enterprises and consumers. At the same time, the design concept and technical methods of this system can also be applied to the data visualization needs of other industries and fields, and it has broad application prospects and market potential.
12. Research risks and countermeasures
In the process of designing and implementing a large-screen full-screen system for data visualization in Jinan gourmet stores, you may encounter some risks and challenges. In order to deal with these risks and challenges, this study will take the following measures:
- Technical risks : Since the system involves complex programming and data processing technologies, you may encounter technical difficulties and implementation difficulties. To cope with this risk, the research team will continue to learn new technologies and methods, keep pace with the latest technology trends, and actively seek expert guidance and cooperation.
- Data acquisition and processing risks : Food store data collection and processing may encounter problems such as unstable data sources and inconsistent data formats. To ensure the accuracy and completeness of the data, the research team will establish a stable and reliable data collection mechanism, write efficient data cleaning and processing procedures, and conduct regular data quality inspections and verifications.
- Risk of change in user requirements : During the system development process, user requirements may change or be added. To deal with this risk, the research team will maintain close communication with users, promptly understand and respond to demand changes, adopt agile development methods, and flexibly adjust system design and development plans.
- Time and resource limitations risk : Due to limited time and resources, it may not be possible to complete all expected functions or achieve optimal results. In order to ensure the smooth progress of the project and the output of high-quality results, the research team will develop a reasonable project plan and timetable, and rationally allocate manpower and resources to ensure the priority realization of key functions and the satisfaction of core needs.
- Legal and compliance risks : When collecting and processing food store data, you need to comply with relevant laws, regulations and privacy policies. To ensure compliance, the research team will carefully study relevant laws, regulations and policy requirements, and adopt corresponding security measures and privacy protection measures during the system design and implementation process.
Through the implementation of the above countermeasures, this research will strive to reduce the impact of risks on project progress and results, and ensure the smooth progress and successful completion of the research. At the same time, the research team will maintain flexibility and adaptability, and promptly adjust research plans and programs according to actual conditions to ensure the smooth progress of the project and the output of high-quality results.