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所在平台: Udemy |
课程主页: https://www.udemy.com/course/master-streamlit-build-interactive-data-apps-with-python/
课程评论：没有评论
课程名称：掌握Streamlit：使用Python构建交互式数据应用 课程概述： 本课程适合数据科学家、分析师、工程师或研究人员，特别是那些使用Python进行工作的专业人士。如果你希望以更引人入胜和互动的方式分享数据见解，而不必学习复杂的网页开发框架，那么这门课就是为你准备的！Streamlit是一种革命性的开源Python库，它使得构建美观、互动的数据科学和机器学习网页应用变得非常简单。通过Streamlit，你可以在几分钟内将数据脚本转化为可分享的网页应用，仅需使用Python，无需HTML、CSS或JavaScript。 本课程将引导你从Streamlit的基础知识开始，逐步构建和部署复杂的互动数据仪表板和工具。你将学习到： - **入门**：设置开发环境并创建你的第一个Streamlit应用。 - **显示数据**：使用Streamlit的内置函数及流行库（如Matplotlib和Plotly）处理文本、表格和各种类型的图表（折线图、柱状图、区域图等）。 - **增加互动性**：利用Streamlit强大的小部件（按钮、滑块、选择框、文本输入等）创建响应该用户输入的动态应用程序。 - **控制布局**：使用列、标签、展开器和容器组织应用程序，以确保用户界面的整洁和直观。 - **处理数据**：从CSV文件、JSON文件以及外部API加载数据。 - **持久化状态**：使用cookies在会话间存储用户偏好和数据。 - **部署应用**：通过Streamlit Sharing和其他云部署选项与世界分享你的创作。 - **超越基础**：通过使用React构建自定义组件，扩展Streamlit的功能，为创建独特而强大的数据应用程序开辟无限可能。 本课程强调实践学习，提供大量的示例、实际练习和技能挑战来巩固所学概念。到课程结束时，你将能够自信地构建和部署自己的交互式数据应用，改变你处理和传达数据的方式。无论你是经验丰富的数据专业人士还是刚刚开始入门，这门课都会帮助你轻松创建引人注目的数据驱动网页应用。如果你是Python的新手，也不用担心！课程附录中包含了完整的Python入门介绍，帮助每个人迅速掌握Python编程。 期待在课程中见到你！
Are you a data scientist, analyst, engineer, or researcher who works with Python? Do you want to share your data insights in a more engaging and interactive way, without having to learn complex web development frameworks? Then this course is for you!Streamlit is a revolutionary open-source Python library that makes it incredibly easy to build beautiful, interactive web applications for data science and machine learning. With Streamlit, you can turn your data scripts into shareable web apps in minutes, using only Python. No need for HTML, CSS, or JavaScript!This comprehensive course will guide you from the very basics of Streamlit to building and deploying sophisticated, interactive data dashboards and tools. You'll learn how to:Get Started: Set up your development environment and create your first Streamlit app.Display Data: Work with text, tables, and a wide variety of charts (line charts, bar charts, area charts, and more) using Streamlit's built-in functions and popular libraries like Matplotlib and Plotly.Add Interactivity: Use Streamlit's powerful widgets (buttons, sliders, selectboxes, text inputs, etc.) to create dynamic applications that respond to user input.Control Layout: Organize your apps with columns, tabs, expanders, and containers for a clean and intuitive user interface.Work with Data: Load data from CSV files, JSON files, and even external APIs.Persist State: Store user preferences and data across sessions using cookies.Deploy Your Apps: Share your creations with the world using Streamlit Sharing and other cloud deployment options.Go Beyond the Basics: Learn how to extend the capabilities of Streamlit by building custom components using React, opening up endless possibilities for creating unique and powerful data applications.This course emphasizes hands-on learning, with numerous examples, practical exercises, and skill challenges to reinforce the concepts. By the end, you'll be able to confidently build and deploy your own interactive data apps with Streamlit, transforming the way you work with and communicate data. Whether you're a seasoned data professional or just starting your journey, this course will empower you to create compelling data-driven web applications with ease. And if you're new to Python, don't fret! There is a full-length introduction to Python included as an Appendix which is included to get anyone up and running writing pythonic code in no time.See you inside!
