"B站用户行为分析系统：基于Python的数据分析与可视化"

In recent years, with the continuous development of Internet technology, the number of Internet users has been growing rapidly, and the amount of online data has also increased exponentially. This data can provide high commercial value for Internet enterprises. Through data analysis, Internet enterprises can better understand user needs and make business decisions based on those needs. By accurately positioning, they can create value for the entire enterprise. This project focuses on using Python technology to design a data analysis system using Bilibili data as the data source. Through big data analysis, the system visualizes data of Bilibili UP main accounts. In the data visualization, the system can analyze the video types and tags that UP mains prefer to publish, as well as their fan base and likes in forms of bar graphs. Additionally, the design of the system also includes analyzing user preferences in watching videos, such as interactive, sharing, and trending type videos. Through this analysis, charts displaying fan rankings, play rankings, and other data metrics are provided for businesses in need. This system provides valuable data support for enterprises and effective data analysis references for UP mains and users' viewing behaviors. Key words: big data, data analysis, Bilibili, video type analysis.