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Opening report
X X X X University/School/ School
Graduation thesis (design) proposal report
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PythonE-commerce data visualizationSystem design and implementation |
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| Basis for topic selection: 1. Research background and significance; 2. Current research (application and development) situation at home and abroad. 1: Research background and significance Research Background: With the rapid development of Internet technology, e-commerce (e-commerce) has become an important part of the global business field. E-commerce platforms have accumulated a large amount of user data, including user behavior, purchasing preferences, consumption habits, etc. These data are of high value to e-commerce platforms, merchants, and researchers because they can reveal consumer needs and behavior patterns and provide support for decision-making. However, raw data is often difficult to understand and apply directly, and data visualization technology needs to be used to transform it into intuitive graphics, images or animations. Data visualization can display large amounts of complex data in an intuitive and easy-to-understand way, helping analysts quickly and accurately discover patterns and trends in the data. Significance: Business decision support: Through the e-commerce data visualization system, merchants can understand key information such as sales, user behavior, and market trends in real time, providing data support for product pricing, inventory management, and marketing strategy formulation. User experience optimization: By analyzing users' browsing and purchasing behaviors, we can discover bottlenecks and problems in user experience, and then carry out targeted design optimization of websites or applications to improve user satisfaction and loyalty. Market research: E-commerce data visualization systems can reveal consumer needs and market trends, providing market researchers with valuable research tools to help them gain an in-depth understanding of the current market status and future development directions. Academic research: For the field of academic research, the e-commerce data visualization system can provide a rich research object and provide a practical application and verification platform for research in data management, data mining, artificial intelligence and other fields. Generally speaking, the research background of Python e-commerce data visualization system is based on the rapid development of e-commerce and the arrival of the big data era. Its research significance is to use data visualization technology to explore the potential value of e-commerce data and provide insights for business decision-making and user experience. Provide support and innovation in areas such as optimization, market research and academic research. 2: CountryResearch status at home and abroad The domestic and foreign research status of Python e-commerce data visualization system is very active and rich. The following is a brief overview of the current state of research in this area: In China, the rapid development of the e-commerce industry has promoted the research and application of Python e-commerce data visualization system. Many universities, research institutions and enterprises have invested resources in developing efficient and intelligent e-commerce data visualization systems. At present, domestic research focus mainly focuses on the following aspects: Data collection and preprocessing: Study how to obtain large amounts of diverse data from e-commerce platforms, and clean, integrate and preprocess these data to provide a reliable data basis for subsequent visual analysis. Visualization algorithms and technologies: Research various advanced visualization algorithms and technologies, such as Python-based visualization libraries (such as Matplotlib, Seaborn, etc.), interactive visualization tools, etc., to improve the effect of data visualization and user experience. Data analysis and mining: By using technologies such as machine learning and deep learning, we conduct in-depth analysis and mining of e-commerce data to discover associations, trends and patterns, and provide support for the operation and decision-making of e-commerce platforms. Current status of foreign research: Compared with domestic research, foreign research on Python e-commerce data visualization systems is also very active. Foreign researchers have conducted extensive and in-depth explorations in e-commerce data visualization and achieved a series of important results. Its research focus mainly includes: Large-scale data processing: For large-scale data generated by e-commerce platforms, study how to efficiently process and analyze data to meet real-time requirements. Visual interaction and user experience: Study how to improve the interactivity and user experience of data visualization so that analysts can conduct data exploration and insights more conveniently. Multi-dimensional data analysis: Through multi-dimensional analysis of e-commerce data, such as time series analysis, geographical distribution analysis, user group analysis, etc., the complex relationships and patterns in the data are revealed. In general, research on Python e-commerce data visualization systems at home and abroad has made significant progress, but it still faces many challenges and problems, such as data processing efficiency, improvement of visualization effects, and the development of intelligent analysis algorithms. In the future, with the continuous innovation of technology and the continued development of the e-commerce industry, the research and application prospects of the Python e-commerce data visualization system will be broader. 3: Research ideas and methods 3.1Research path Solve technical problems by borrowing development-related books from the library or searching for relevant topic videos on the Internet, searching the Internet, and seeking help from instructors. The specific steps are: (1) Conduct a demand analysis on the system to clarify administrator functions, front-end development functions, development framework models, etc.; (2) Conduct an outline design of the system, build the development process, and establish the system's architecture diagram, functional module diagram, etc.; (3) Design all functional modules for the system management background; (4) For the user front-end, design all functional modules; (5) Carry out software coding to realize various functions of the system; (6) Conduct various tests on the system; (7) Submit the system and write the paper. After selecting the project development model and back-end development framework, we set up the development environment and installed the corresponding development tools; then we designed the database, developed the back-end and interfaces, developed the complete project back-end and front-end, and completed the final work, testing, use. 3.2Research method In order to better improve the system, the following research methods are used: (1) Literature reading method Search and refer to thesis materials related to the topic through various literature search websites, school libraries and Baidu Encyclopedia, and then save the appropriate materials locally for use during development. (2) Comparative method: Through comparative analysis of the functions, related technologies, contents, etc. of relevant domestic and foreign subject systems, we can propose problems existing in the system and propose corresponding solutions. (3) Simulation method The simulation method is a description method that first creates a similar model based on the main characteristics of the prototype, and then indirectly studies the prototype through the model. We achieve the final effect of development by simulating the local computer as a server for local operations. 3.3Possibility 1. Technical feasibility It uses Windows 7 or 10 as the operating system, based on python3.8 version, uses PyCharm software as the development tool, and uses mysql for database storage; the background management system hardware environment is a PC. Users can use any computer with Internet access to set up and use a browser. Access the news management system. 2. Economic feasibility On the one hand, as long as there is a computer with Internet access, the system administrator can manage it anywhere and at any time, further improving work efficiency and saving manpower and material resources. As long as you can type, no high degree of education is required; on the other hand, The production cost of the system is low, and it can be developed using PyCharm developer tools on existing PCs. 3. Operational feasibility From a management point of view, as long as you have an ordinary computer, you can set up, enter, and modify website information. The operation is very convenient and highly feasible. 4. Feasibility of data sources Source: Taobao data. Taobao is already very popular and widely used. It is representative. 4: Preliminary system design plan 4.1主要设计技术 开发环境：python3.8+ 开发语言：Python 开发框架：Django框架 数据采集：selenium + Xpath 可视化模块：Echarts 开发工具：Pycharm 数据库：mysql8 数据库管理工具：navicat 其他开发语言：html + css +javascript 4.2研究内容 我们这里以我们打算实现的系统内容，分析如下，数据来源淘宝 大屏全屏可视化展示：
后台内容：
5：进度安排 2023.09.10—2023.10.15 查看大量的文献，收集课题有关资料，确定论文选题； 2023.10.16—2023.10.30 在老师的指导下，填写毕业论文任务书； 2023.10.31—2023.11.15 大量收集论文资料，理清论文思路，对论文思路进行完善。 2023.11.16—2023.12.22 完成开题报告答辩； 2023.12.23—2023.12.27 根据指导老师提出的建议再进行修改，完善系统功能设计 2023.12.28—2024.04.10 在查阅大量文献之后，运用多种研究方案，完成系统开发并基本完成论文初稿。 2024.04.01—2024.04.15 将初稿完善交由导师审阅，提出修改建议。 2024.04.16—2024.05.14 在导师指导下，对论文进行反复修改形成终稿，装订成册上交学院，同时为毕业论文答辩做准备工作 2024.05.15 进行毕业论文答辩 6：论文（设计）写作提纲 摘要 第1章 绪论 1.1 项目研究背景和意义 1.2 论文研究目的 1.3 系统主要功能 第2章 系统相关技术 2.1 开发概要 2.2 开发技术 2.2.1 Python介绍 2.2.2 Django框架 2.3 MYSQL 数据库 2.4 其他网页技术 2.5.1 什么是HTML 2.5.2 什么是 CSS 2.5.3 JavaScript 2.6 本章小结 第3章 系统分析 3.1 系统概要 3.2 数据库和图形 3.2.1 数据ER原型图 3.1.2 实体图 3.1.3 数据库表 3.3 前端需求分析 3.4 后台需求分析 3.5 本章小结 第4章 系统设计与实现 4.1 前端实现 4.2 后台实现 4.3 本章小结 第5章 总结与展望 5.1 总结 5.2 展望 参考文献 致谢 7：参考文献 [1]麻清应，马权. Web前端框架开发技术[M].重庆大学电子音像出版社，2020. 08. [2]李云.基于网站制作的Web前端开发技术与优化[J].电子技术与软件工程,2021(22): 50-52. [3]黑马程序员.HTMLHSS+JavaScript网页制作案例教程(第2版)[M].北京:人民邮电出版社，2021. [4]王千林.基于B/S架构固定资产管理系统设计与实现[J].电脑知识与技术.2020(07) [5]代飞，艾迪. Web前端开发项目案例教程[M],北京理工大学出版社，2020. 08. [6]郑智方. MySQL的重要性以及步入云的应用实例[J].计算机产品与流通，2020(01):151. [7]陈漫红.数据库原理与应用教程SQL Server 2012[M],北京理工大学出版社，2021. 01. [8]李曼. MySQL数据库系统中文乱码问题及解决方案[J].电子技术与软件程,2021(12):176-177. [9]王征，李晓波 著. Python从入门到精通[M], 中国铁道出版社，2020-01-01 [10]胡阳. Django企业开发实战[M], 人民邮电出版社，2021. 06. [11]李宁，python从菜鸟到高手[M]. 北京：清华大学出版社，2018. 219~315 [12]关东升，看漫画学python[M]. 北京：电子工业出版社，2020. 36~78 [13]王英英，MySQ 8 快速入门[M]. 北京：清华大学出版社，2020. 200~256 [14]慕课教育研发中心，HTML+CSS3+JavaScript从入门到项目实践[M]. 北京：清华大学出版社，2019. 11~40 [15]黄永祥，精通Django 3 web开发[M]. 北京：清华大学出版社，2020. 50~148 [16]胡阳，Django 企业开发实战[M]. 北京：人民邮电出版社，2019. 108~210 |
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| 指导教师意见： 意见从以下几个方面展开：
3、对研究思路、方法的评价。4、是否同意开题。（指导意见打印，签名指导教师务必手写） 指导教师签名： 年 月 日 |
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