python Zhejiang Hangzhou shopping store data visualization large-screen full-screen system design and implementation (django framework)

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Python Zhejiang Hangzhou shopping store data visualization large-screen full-screen system design and implementation (Django framework) proposal report

1. Research background and significance

With the rapid development of e-commerce, the number and scale of shopping stores continue to expand. How to effectively display shopping store data and improve user experience and merchant benefits has become an important issue. This research aims to design a large-screen full-screen system for visualizing shopping store data in Zhejiang Hangzhou based on Python and Django frameworks. Through real-time monitoring and visual display of shopping store data, it can help merchants and consumers understand store operations and consumption trends more intuitively, and provide Provide the basis for formulating effective marketing strategies and improving shopping experience.

Specifically, the significance of this study is mainly reflected in the following aspects:

1. Improve merchant efficiency: Through real-time monitoring and visual display of store data, merchants can have a more comprehensive understanding of store operations, timely adjust product prices and inventory, formulate more effective marketing strategies, and increase sales and user satisfaction.
2. Improve user experience: By visually displaying shopping store data, users can more intuitively understand product information and consumption trends, improving shopping experience and satisfaction.
3. Promote the construction of smart cities: The large-screen full-screen shopping store data visualization system designed in this study can be used as an important part of smart city construction and provide strong support for urban management and commercial development.

2. Research status at home and abroad

At home and abroad, some cities and regions have established shopping store data visualization systems and achieved certain results. Abroad, some large retailers and supermarkets use large screens to display store data in real time to provide consumers with timely information. In China, some e-commerce platforms have also launched similar functions, but they are mainly concentrated on the web page, and the data visualization effect and user experience need to be improved.

3. Research ideas and methods

This research will be conducted using the following methods:

1. Requirements analysis: Conduct a detailed analysis and description of the functional requirements of the large-screen full-screen shopping store data visualization system, including back-end management functions and front-end display functions.
2. System design: Based on the requirements analysis results, design the overall architecture and functional modules of the system, including database design, back-end management system development, front-end page development, etc.
3. System implementation: Use Python and Django frameworks for system development to implement back-end management functions and front-end interaction functions.
4. Data visualization: Use appropriate data visualization technologies and tools, such as ECharts chart library, etc., to achieve visual display of shopping store data.
5. System testing and optimization: Conduct detailed testing and optimization of the system, including functional testing, performance testing, security testing, etc., and optimize and improve the system based on the test results.
6. System application and promotion: Apply the system to actual scenarios, collect user feedback, and continuously improve system functions and user experience.

4. Research content and innovation points

The main contents of this study include:

1. Design and implement a system that can monitor and visually display shopping store data in Hangzhou, Zhejiang in real time;
2. Realize the system's back-end management functions and front-end interactive functions to facilitate user use and management;
3. Conduct detailed testing and optimization of the system to ensure its stability and practicality;
4. Apply the system to actual scenarios, collect user feedback, and continuously improve system functions and user experience.

Innovation:

1. Use Python and Django frameworks for system development to improve development efficiency and code quality;
2. Design and implement a user-friendly front-end interactive interface to facilitate user use;
3. Implement backend management functions and support real-time updates and queries of data;
4. Display shopping store data in full screen on a large screen to improve the effect of data visualization;
5. Based on actual needs, design and implement some special functions, such as coupon issuance, membership management, etc.

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

Backend functional requirements analysis:

1. Product management: including functions such as adding, editing, and deleting products;
2. Order management: including order query, export, statistics and other functions;
3. User management: including user registration, login, rights management and other functions;
4. Data statistics and analysis: perform statistics and analysis on store data and generate reports and charts.

Front-end functional requirements analysis:

1. Real-time monitoring and display: real-time display of operational data of shopping stores in Hangzhou, Zhejiang;
2. Historical data query: supports querying historical data by time period;
3. Data visualization: display the changing trends of shopping store data through charts and other forms;
4. Interactive functions: Support users to operate and use the system, such as searching for products, placing orders, etc.

6. Research ideas, research methods, and feasibility analysis

Research idea: First, conduct a detailed analysis and description of the functional requirements of the large-screen full-screen shopping store data visualization system, and then conduct system design based on the requirements analysis results, including database design, functional module division, etc. Then use Python and Django frameworks for system development, including backend management system development and front-end page development. Finally, detailed testing and optimization of the system are conducted to ensure its stability and practicality. Specific methods include literature research method, case analysis method, empirical research method, etc. By reviewing relevant literature and cases, we understand the current research status and development trends in shopping store data visualization at home and abroad to provide reference for system design. At the same time, the system is tested and evaluated using empirical research methods to verify the feasibility and practicability of the system. In terms of feasibility, the technologies and tools used in this study have been extensively verified and applied, and have high feasibility and practicability. At the same time, this research has received support and funding from relevant companies and institutions, which provides guarantee for the smooth progress of the research.

7. Technical route and implementation plan

1. Technical route:

   • Back-end: Use the Python programming language and Django framework for back-end development, and use Django's ORM function to perform database operations to achieve data addition, deletion, modification and query;
   • Front-end: Use HTML, CSS and JavaScript for front-end page development, and combine with ECharts chart library to achieve visual display of data;
   • Data transmission: Use RESTful API to realize the interaction and transmission of front-end and back-end data to ensure the real-time and accuracy of data;
   • Data storage: MySQL database is used for data storage and management to ensure data security and reliability.

2. implementation plan:

   • Demand research and analysis: Conduct research and analysis on the actual needs of shopping stores in Hangzhou, Zhejiang, and clarify the functional requirements and performance requirements of the system;
   • System design: Based on the requirements analysis results, design the overall architecture, database structure and functional modules of the system;
   • System development: According to the system design, use Python and Django frameworks for back-end development, and use HTML, CSS and JavaScript for front-end development;
   • Data visualization implementation: Integrate ECharts chart library to realize visual display of shopping store data;
   • System testing: Conduct functional testing, performance testing and security testing on the system to ensure the stability and practicality of the system;
   • System deployment and application: Deploy the system into actual application environments, collect user feedback, and continuously improve system functions and user experience.

8. Research progress arrangement

This research plan is divided into the following stages:

1. The first stage (1-2 months): demand research and analysis to clarify the functional requirements and performance requirements of the system;
2. The second stage (2-3 months): system design, including the design of the overall architecture, database structure and functional modules;
3. The third stage (3-4 months): system development, including back-end development, front-end development and data visualization implementation;
4. The fourth stage (4-5 months): System testing and optimization, conduct detailed testing and optimization of the system to ensure its stability and practicality;
5. The fifth stage (5-6 months): System deployment and application, apply the system to actual scenarios, collect user feedback, and continuously improve system functions and user experience.

9. Thesis (design) writing outline

1. Introduction: Introducing the research background and significance, domestic and foreign research status, and research ideas and methods;
2. Requirements analysis: Conduct a detailed analysis and description of the functional requirements of the large-screen full-screen shopping store data visualization system;
3. System design: Based on the requirements analysis results, design the overall architecture, database structure and functional modules of the system;
4. System implementation: Detailed description of the system implementation process and technical route including back-end development, front-end development, data visualization implementation, etc.;
5. System testing and optimization: Detailed testing and optimization of the system including functional testing, performance testing, security testing, etc.;
6. System application and promotion: Apply the system to actual scenarios and collect user feedback to continuously improve system functions and user experience;
7. Conclusion and outlook: Summarize the main work and results of this study and look forward to future research directions and improvement measures.

10. Main references

[List relevant references here]

11. Summary and Outlook

This research aims to design a large-screen full-screen system for data visualization of shopping stores in Zhejiang Hangzhou based on Python and Django frameworks. Through real-time monitoring and visual display of shopping store data, it can help merchants and consumers understand store operations and consumption trends more intuitively and formulate effective strategies. Provide basis for marketing strategies and improving shopping experience. Through this research, we can provide strong support for the operation and development of shopping stores and help promote the development of smart business and smart city construction. In the future, we will continue to pay attention to the research and development trends of shopping store data visualization, continuously improve and optimize system functions, and improve user experience and merchant benefits.

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Proposal report: Design and implementation of python Zhejiang Hangzhou shopping store data visualization large-screen full-screen system (django framework)

1. Research background and significance

Nowadays, with the rapid development of the Internet, the e-commerce industry is developing rapidly. Visual analysis of shopping store data is of great significance to the e-commerce industry. Through visual analysis of shopping store data, information such as store sales and user purchasing behavior can be intuitively displayed, helping e-commerce companies understand market demand, optimize product recommendation strategies, and improve operating efficiency.

This article is dedicated to the design and implementation of a large-screen full-screen system for visualizing shopping store data in Zhejiang Hangzhou based on Python. It builds a backend management system through the Django framework to visually present shopping store data and provide users with intuitive analysis and decision-making support.

2. Research status at home and abroad

At present, there are some researches on python-based data visualization systems at home and abroad, such as Tableau, Power BI, etc. These systems can display data graphically, but there is a lack of relevant research on the visual analysis of shopping store data in Hangzhou, Zhejiang.

3. Research ideas and methods

This article will use the Django framework to build a backend management system to manage and visualize shopping store data. The specific research ideas and methods are as follows:

1. Determine system requirements: Analyze e-commerce companies' needs for shopping store data visualization, and clarify system functions and interface design requirements.
2. Data collection and processing: Obtain shopping store data through crawler technology, and clean and organize the data to make it suitable for visual analysis.
3. Backend system design: Use the Django framework to build a backend management system to realize data storage, management and query functions. Including user management, store data management, data analysis report generation and other functions.
4. Front-end interface design: Design an intuitive and easy-to-use visual interface, display shopping store data through charts, tables, etc., and provide interactive data analysis functions.
5. System testing and optimization: Functional testing and performance optimization of the system to ensure system stability and user experience.

4. Research internal customers and innovation points

The goal of this research is to implement a large-screen full-screen system for data visualization of shopping stores in Hangzhou, Zhejiang Province, with the following innovations:

1. Use the Django framework to build a backend management system to make the system scalable and easy to use.
2. Realize multi-dimensional visual display of shopping store data to help e-commerce companies deeply understand market demand and user behavior.
3. Provides interactive data analysis functions, allowing users to customize data filtering and analysis to achieve personalized data visualization needs.

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

Backend functional requirements include user management, store data management, data analysis report generation, etc. Front-end functional requirements include data visualization display, data filtering and analysis, etc.

6. Research ideas, research methods, and feasibility

The research idea of ​​this article is to build a back-end management system through the Django framework and cooperate with the front-end interface design to realize the visual display and analysis of shopping store data. Research methods include data collection and processing, system design and implementation, etc. This research method has high feasibility, and the Django framework has rich functions and community support, which can meet the needs of the system.

7. Research progress arrangement

1. Week 1: Determine system requirements, conduct literature research, and write a proposal report.
2. Week 2: Conduct data collection and processing, and prepare data sets.
3. Week 3: Build a Django framework background management system to implement data storage and management functions.
4. Week 4: Design the front-end interface to implement data visualization display function.
5. Week 5: Implement data filtering and analysis functions.
6. Week 6: System testing and optimization.
7. Week 7: Writing the paper.

8. Thesis (design) writing outline

1. Introduction 1.1 Research background and significance 1.2 Research status at home and abroad 1.3 Research objectives and content

2. Introduction to related technologies and tools 2.1 Introduction to django framework 2.2 Introduction to data visualization technology

3. System requirement analysis and design 3.1 Backend functional requirement analysis 3.2 Front-end functional requirement analysis 3.3 System design and implementation

4. System testing and optimization 4.1 Functional testing 4.2 Performance optimization

5. Result analysis and discussion 5.1 Data visualization analysis results 5.2 Analysis of the advantages and disadvantages of the system

6. Summary and Outlook 6.1 Summary of research work 6.2 Next research direction

9. Main references

1. Chan, K. C. C., & Chao, P. K. (2019). Data visualization for business analytics: The R Language, Excel, and Python. Springer.
2. Duggan, P., & Han, J. (2017). Python for Finance: Analyze Big Financial Data. John Wiley & Sons.
3. Jun, S. (2019). Django for Beginners: Build websites with Python and Django. Independently Published.

The above is a project report on the design and implementation of a large-screen full-screen system for data visualization of Zhejiang Hangzhou shopping stores in python (django framework), including research background and significance, domestic and foreign research status, research ideas and methods