Research And Implementation Of The 21st CUBA Player Data Visualization Based On Python

With the rapid development of science and technology,data plays an increasingly important role in this information age.The use of computer data analysis,data visualization has been widely used in all walks of life.In sports,people are more comfortable with the graphical presentation of data than digital ones.Vivid data charts can intuitively display the value of data,facilitate people’s understanding of data,and are an effective way to explore and understand the connotation and significance of data.In the basketball sports,the visual analysis of player data plays an important role in giving play to the players’ abilities,improving the team’s offensive efficiency,and helping coaches to better understand the characteristics of the players’ games.However,at this stage,a lot of research and analysis on the visualization of CUBA player data are only for a certain aspect of the player data.Most of the charts used are simple static charts,and the types of charts are relatively single,and the interactivity of the graphics is not Strong,if you want to change players for visual analysis,you need to re-import player data for analysis,which is time-consuming and costly.Therefore,this article proposes a visual analysis system that starts from the players themselves and analyzes their performance during the season in order to help users analyze the players’ abilities.By writing a program,it is used to generate visual charts and visually analyze player data.Realize player visualization chart analysis program.Combining research methods such as literature data method,logical analysis method,case analysis method,mathematical statistics method,structured software development method,etc.,by crawling the game data of all men’s basketball players in the 21 st CUBA Basketball League,and storing the data in local files,then using Python programming language and Pyecharts third-party visualization library programming to realize the visualization of players’ technical statistics function.The final written program achieves the purpose of inputting the names of CUBA athletes,and the program can generate visual charts corresponding to various technical statistical data of the athletes,so that a large number of CUBA athletes’ game data can be displayed in the form of intuitive,efficient and fast visual charts.Improve the efficiency of visual data analysis of CUBA athletes,help coaches to better analyze and understand the technical advantages and characteristics of CUBA athletes,conduct more targeted training in training,and arrange for coaches in competitions.The selection of athletes provides a reference,and provides new ideas for the visual design of CUBA athlete competition data.At the same time,this visualization case is only a preliminary exploration of the application of Python language and visualization technology in the CUBA league.For the more possibilities of CUBA athlete game data and computer application technology,the diversity of data visualization chart styles still needs continuous research and exploration..In the future,there is a lot of room for development in the use of advanced artificial intelligence,machine learning and other technologies in the analysis of CUBA athlete competition data,which requires continuous research.