|
所在平台: Udemy |
课程主页: https://www.udemy.com/course/data-analysis-and-visualization-with-python-for-beginners/
课程评论：没有评论
课程名称：初学者的Python数据分析与可视化 概述：数据无处不在，越来越多的公司通过跟踪、分析数据，利用洞察力做出更好的决策。Python是一种流行的编程语言，广泛应用于网页开发、软件开发、数学计算、数据分析、数据可视化以及系统脚本等领域。 Python可以用来在服务器上创建web应用程序，也能与软件结合创建工作流程，连接数据库系统，读取和修改文件，处理大数据以及进行复杂数学计算。它不仅可用于快速原型开发，还适合生产级软件开发，尤其是在数据分析和可视化方面。 数据分析是分析和解释数据的过程，旨在发现推动更聪明、更有效业务决策的有价值洞察。数据分析工具用于从商业及其他类型的数据中提取有用信息，帮助简化数据分析过程。 数据可视化是信息和数据的图形表示，借助图表、图形和地图等视觉元素，数据可视化工具提供了一种易于理解趋势、异常值和模式的方式。 Jupyter Notebook是一个开源的web应用程序，允许用户创建并分享包含实时代码、公式、可视化和叙述文本的文档。其用途包括数据清洗与转换、数值模拟、统计建模、数据可视化、机器学习等。 该课程适合希望通过Python学习数据分析与可视化的初学者，通过实用的工具和方法，帮助学员掌握如何利用数据做出明智的商业决策。
Data is everywhere. That means more companies are tracking,analysing, and using the insights they find to make better decisions.Python is a popular programming language. It is used for:web development (server-side),software development,mathematics,Data AnalysisData VisualizationSystem scripting.What can Python do?Python can be used on a server to create web applications.Python can be used alongside software to create workflows.Python can connect to database systems. It can also read and modify files.Python can be used to handle big data and perform complex mathematics.Python can be used for rapid prototyping, or for production-ready software development.Python can be used for data analysis and visualization.Data analysis is the process of analysing, interpreting, data to discover valuable insights that drive smarter and more effective business decisions. Data analysis tools are used to extract useful information from business and other types of data, and help make the data analysis process easier.Data visualisation is the graphical representation of information and data. By using visual elements like charts, graphs and maps, data visualisation tools provide an accessible way to see and understand trends, outliers and patterns in data.The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modelling, data visualization, machine learning, and much more.
