Jupyter Cookbook

丛 书 名：[]

版本说明：1

作     者：Dan Toomey 

I S B N：(纸本) 9781788839440 

出 版 社：Packt Publishing  Limited 

出 版 年：2018年

页      数：229页

主 题 词：Jupyter Jupyter Notebook Jupyter Python Interactive Computing Interactive Computing Web Application Jupyter installation Jupyter configuration Jupyter R Jupyter visualization 

学科分类：0810[工学-信息与通信工程] 0711[理学-系统科学] 07[理学] 081203[工学-计算机应用技术] 08[工学] 080401[工学-精密仪器及机械] 0804[工学-仪器科学与技术] 080402[工学-测试计量技术及仪器] 0835[工学-软件工程] 081002[工学-信号与信息处理] 071102[理学-系统分析与集成] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

摘      要：Leverage the power of the popular Jupyter notebooks to simplify your data science tasks without any hassle Key Features Create and share interactive documents with live code, text and visualizations Integrate popular programming languages such as Python, R, Julia, Scala with Jupyter Develop your widgets and interactive dashboards with these innovative recipes Book Description Jupyter has garnered a strong interest in the data science community of late, as it makes common data processing and analysis tasks much simpler. This book is for data science professionals who want to master various tasks related to Jupyter to create efficient, easy-to-share, scientific applications. The book starts with recipes on installing and running the Jupyter Notebook system on various platforms and configuring the various packages that can be used with it. You will then see how you can implement different programming languages and frameworks, such as Python, R, Julia, JavaScript, Scala, and Spark on your Jupyter Notebook. This book contains intuitive recipes on building interactive widgets to manipulate and visualize data in real time, sharing your code, creating a multi-user environment, and organizing your notebook. You will then get hands-on experience with Jupyter Labs, microservices, and deploying them on the web. By the end of this book, you will have taken your knowledge of Jupyter to the next level to perform all key tasks associated with it. What you will learn Install Jupyter and configure engines for Python, R, Scala and more Access and retrieve data on Jupyter Notebooks Create interactive visualizations and dashboards for different scenarios Convert and share your dynamic codes using HTML, JavaScript, Docker, and more Create custom user data interactions using various Jupyter widgets Manage user authentication and file permissions Interact with Big Data to perform numerical computing and statistical modeling Get familiar with Jupyter s next-gen user interface - JupyterLab W