Design and implementation of large-screen full-screen system for data visualization of shopping stores in Chengdu, Sichuan using python (django framework)

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Opening report

Design and implementation of large-screen full-screen system for data visualization of shopping stores in Chengdu, Sichuan (Django framework)

1. Research background and significance

With the rapid development of e-commerce and offline retail, Chengdu, Sichuan, as the economic center of the southwest region, has a large number of shopping stores and the transaction data generated is also growing. For store managers and government regulators, it has become crucial to intuitively grasp market trends, analyze consumer behavior, optimize product layout, and adjust business strategies. Therefore, designing and implementing a large-screen full-screen shopping store data visualization system based on the Django framework will not only help improve the efficiency of business decision-making, but also provide data support for the formulation of relevant policies.

2. Research status at home and abroad

At present, there has been a lot of research and practice in data visualization at home and abroad. Business intelligence tools such as Tableau and Power BI provide a wealth of visualization components. However, customized large-screen data visualization systems for specific regions or industries are still rare. Especially in terms of development combined with the Django framework, there is still a lot of research space.

3. Research ideas and methods

This research will adopt the following ideas and methods:

1. Research and analysis: Collect operating data of shopping stores in Chengdu, Sichuan, and analyze data characteristics and visualization needs.
2. Technology selection: Choose the Django framework as the back-end development technology, and combine the front-end visualization libraries (such as ECharts, Highcharts, etc.) for system design.
3. System design: Design database structure, front-end and back-end interactive interfaces and visual interface layout.
4. System implementation: Write code to implement background data processing and front-end data display functions.
5. Testing and Optimization: Conduct system testing and optimize system performance and user experience based on feedback.

4. Research content and innovation points

1. Research content: collection and organization of shopping store operating data, system architecture design under the Django framework, front-end and back-end interaction mechanism design, visual interface design and implementation, system testing and optimization.
2. Innovation points: Design a customized data visualization interface based on regional characteristics and industry characteristics; use the flexibility of the Django framework to achieve efficient data processing and display; provide a full-screen display function to enhance the impact and intuitiveness of data presentation.

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

1. Backend functional requirements: data cleaning and integration, data analysis and mining, data storage and query, permission management and security control.
2. Front-end functional requirements: user login and permission verification, data visualization display, interactive operation and response, interface layout and beautification.

6. Research ideas, research methods, and feasibility

This study adopts research ideas and methods of research analysis, technology selection, system design, system implementation and test optimization, which is feasible. The maturity and stability of the Django framework and its rich visual library resources provide strong support for the design and implementation of the system. At the same time, combined with the actual situation in Chengdu, Sichuan, the customized data visualization interface will be more practical and targeted.

7. Research progress arrangement

1. The first stage (1-2 months): Complete research analysis and technology selection.
2. The second stage (3-4 months): Complete system design and development work.
3. The third stage (5-6 months): Complete system testing and optimization work, and write relevant papers or reports.

8. Thesis (design) writing outline

1. Introduction: Explain the research background and significance, and introduce the current research status at home and abroad.
2. Demand analysis: Analyze the needs and challenges of shopping store data visualization.
3. Technology selection and design: Select the Django framework and front-end visualization library to design the system architecture.
4. System implementation: Describe in detail the implementation process of back-end data processing and front-end data display.
5. System testing and optimization: Introduce system testing methods and results, and discuss performance optimization strategies.
6. Case analysis and application: Taking the Chengdu area of ​​Sichuan as an example to demonstrate the practical application effect of the system.
7. Conclusion and outlook: Summarize the research results and shortcomings, and propose future improvement directions and application prospects.

9. Main references
(main references are listed here)

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Proposal report: Design and implementation of large-screen full-screen system for data visualization of shopping stores in Chengdu, Sichuan using Python (Django framework)

1. Research Background and Significance With the development of the times and the advancement of technology, data visualization is increasingly used in various fields. It can transform huge data into intuitive and easy-to-understand charts and graphs. The visualization of shopping store data can not only help merchants better understand their own operating conditions and market trends, but also provide decision-making basis for government departments and promote the development of urban economy. Therefore, designing a fully functional and user-friendly large-screen full-screen shopping store data visualization system has important research significance and practical value.

2. Research status at home and abroad At present, there have been some studies on data visualization at home and abroad. Some large domestic e-commerce platforms and data analysis companies have developed some commercial data visualization products, but most of these products are closed source and users do not have customization and scalability. There are also some open source data visualization tools and frameworks abroad, such as D3.js, Tableau, etc. However, in practical applications, these tools often require high technical threshold and programming capabilities. To sum up, there is still a lack of an open source shopping store data visualization large-screen full-screen system based on the Django framework.

3. Research ideas and methods This research will use the Django framework as the back-end implementation of the project and use the Python programming language for development. In terms of front-end, the data visualization interface is constructed through front-end technologies such as HTML, CSS and JavaScript. Specific research methods include: requirements analysis, system design, function development, interface implementation, testing and optimization, etc. The core functions of the system include data collection, storage and display, as well as user login, permission management, etc.

4. Studying internal customers and innovation points The intrinsic motivation of this study is to fill the gap in the field of large-screen full-screen system for data visualization in shopping stores, and to provide shopping store operators with an efficient and customizable data visualization solution. The innovation of the system lies in the use of the Django framework for development, which is open source, modular and extensible, making it convenient for users to carry out secondary development and customization.

5. Backend functional requirements analysis and front-end functional requirements analysis Backend functional requirements include data collection and import, data storage and management, user login and permission management, data visualization and display, etc. Front-end functional requirements include chart display, data filtering and sorting, multi-dimensional data comparison, etc.

6. Research ideas, research methods, and feasibility The idea of ​​this research is to develop the system based on the Django framework, use the Python programming language for back-end development, and use front-end technology to build a data visualization interface. This method is more feasible because the Django framework has good development efficiency and stability, and the Python language is also very suitable for data processing and data visualization tasks.

7. Research schedule The schedule of this study is as follows: the first week is for project establishment and proposal report writing, the second week is for demand analysis and system design, the third to eighth weeks are for function development and interface implementation, and the ninth to tenth weeks are Carry out testing and optimization, and carry out thesis (design) writing and delivery of the final system from the eleventh to the twelfth week.

8. Thesis (design) writing outline (1) Introduction (2) Review of related work (3) System design and implementation (4) System function and interface display (5) System testing and optimization (6) Summary and outlook

9. main reference

• J. Heer and M. Bostock, "Crowdsourcing graphical perception: using Mechanical Turk to assess visualization design," in Proceedings of the 28th international conference on Human factors in computing systems, ACM, 2010.
• N. Elmqvist, et al., "Fluid interaction for information visualization," in IEEE transactions on visualization and computer graphics, vol. 14, no. 5, pp. 877-884, 2008.
• M. Tory and T. Möller, "Human factors in visualization research," in IEEE transactions on visualization and computer graphics, vol. 10, no. 1, pp. 72-84, 2004.