Blogger introduction : Author of the books "Getting Started with Vue.js and Mall Development" and "WeChat Mini Program Mall Development", CSDN blog expert, online education expert, CSDN diamond lecturer; Focus on graduation project education and guidance for college students.
All projects are equipped with basic knowledge video courses from entry to mastering, free of charge
The projects are equipped with corresponding development documents, proposal reports, task books, PPT, and papers. Templates, etc.The project has recorded release and functional operation demonstration videos; the interface and functions of the project can be customized, and installation and operation are included! ! !
Contact information can be found at the end of the article
| PythonShanxi Taiyuan second-hand housing crawler data Visual analysis large-screen full-screen system Opening report |
X X X X University/School/ School
Graduation thesis (design) proposal report
| student name |
Affiliation college |
student ID |
|||||
| professional class |
|||||||
| Thesis (design) title |
PythonShanxi Taiyuan second-hand housing crawler data visual analysis large-screen full-screen systemDesign and implementation |
||||||
| Instructor’s name (professional title) |
Date of opening the topic |
||||||
| 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 The research background and significance of the large-screen full-screen system for visual analysis of second-hand housing crawler data in Taiyuan, Shanxi using Python are as follows: Research Background: The rise of the real estate market in Taiyuan, Shanxi: With the development of the economy and the acceleration of urbanization, the real estate market in Taiyuan, Shanxi has gradually prospered, especially the second-hand housing market. This has attracted a large number of investors, home buyers and intermediaries to the market. Challenges and opportunities in the information age: In the information age, a large amount of housing information is gathered on online platforms. How to efficiently obtain, process and analyze this data has become an important issue faced by market participants. Popularization and application of Python technology: Python, as a powerful programming language, has received widespread attention for its simplicity, readability and rich library support. Combining Python's crawler technology and data visualization tools provides the possibility to process and analyze second-hand housing data. significance: Market insights and decision support: Using Python crawler technology to obtain second-hand housing data in Taiyuan, Shanxi, and combined with data visualization analysis, market participants can have a deeper understanding of market dynamics, price trends, and supply and demand relationships, thereby providing scientific basis for investment decisions. Improve market transparency: The real-time data display of the large-screen full-screen system can enhance market transparency, reduce information asymmetry, and help maintain market fairness and integrity. Technological innovation and industrial upgrading: This research will further promote the application and innovation of Python crawler technology, data visualization technology, etc. in the second-hand housing market in Taiyuan, Shanxi, and help improve the informatization level and competitiveness of the entire industry. Policy formulation and market supervision: Government departments can better supervise and guide the healthy development of the second-hand housing market in Taiyuan, Shanxi, based on the real-time data analysis results provided by the system, and formulate policies that are more in line with market demand. In summary, the research on the Python Shanxi Taiyuan second-hand housing crawler data visual analysis large-screen full-screen system has important practical significance and long-term value, and is expected to bring a more efficient, transparent and fair trading environment to the second-hand housing market in Taiyuan, Shanxi. At the same time, it also provides valuable reference for the application expansion of Python technology and data visualization in more regional real estate markets. 2: CountryResearch status at home and abroad The domestic and foreign research status of large-screen full-screen system for visual analysis of second-hand housing crawler data in Taiyuan, Shanxi using Python is as follows: Research state in China: In recent years, China has made important progress in Python crawler technology and data visualization analysis. For the second-hand housing market in Taiyuan, Shanxi, some research teams and companies have begun to try to use Python to build a second-hand housing crawler system. These systems use Python's crawler library and data processing capabilities to crawl housing information from major real estate websites, clean and integrate it. At the same time, they use data visualization libraries and tools to perform chart display and statistical analysis on the crawled housing data to help users understand the market situation and housing characteristics more intuitively. However, in domestic research, the comprehensive research on the large-screen full-screen system for visual analysis of second-hand housing crawler data in Taiyuan, Shanxi is still in its infancy, and further in-depth exploration and practice are still needed. Current status of foreign research: In contrast, foreign research in the field of Python crawler technology and data visualization is more extensive and in-depth. Some advanced data analysis and visualization tools are constantly being developed and widely used in all walks of life. In the field of real estate, foreign research teams and companies have successfully applied Python technology to the capture, processing and analysis of second-hand housing data. They pay attention to the quality and timeliness of data, and achieve efficient acquisition and accurate analysis of housing data by continuously optimizing crawler algorithms and visualization technology. In addition, foreign research also focuses on integrating cutting-edge technologies such as big data and artificial intelligence with the second-hand housing market to provide market participants with more accurate and comprehensive decision-making support. To sum up, the Python Shanxi Taiyuan second-hand housing crawler data visual analysis large-screen full-screen system has received attention and research both at home and abroad. However, due to differences in market environments and technological development levels at home and abroad, domestic research in this field needs to be further deepened and improved. Therefore, combined with the current research status at home and abroad, it is of great practical significance and potential value to carry out research on a large-screen full-screen system for visual analysis of crawler data for second-hand housing in Taiyuan, Shanxi using Python. 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 来源知名房产网站数据，数据已经很普及了，使用也很广，有代表性 4：系统初步设计方案 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：requests + parsel + 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 |
|||||||
| 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 |
|||||||
参考来源：http://www.hzyaoyi.com/