Jupyter Cookbook: Over 75 recipes to perform interactive computing across Python, R, Scala, Spark, JavaScript, and more

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

Who This Book Is For

This cookbook is for data science professionals, developers, technical data analysts, and programmers who want to execute technical coding, visualize output, and do scientific computing in one tool. Prior understanding of data science concepts will be helpful, but not mandatory, to use this book.

Table of Contents

1. Installation & Setting up the Environment
2. Adding an Engine
3. Accessing and Retrieving Data
4. Visualize your analytics
5. Working with Widgets
6. Jupyter dashboards
7. Sharing your code
8. Multiuser Jupyter
9. Interacting with Big Data
10. Jupyter Security
11. Jupyter Labs

充分利用流行的Jupyter筆記本的功能，輕鬆簡化您的數據科學任務，無需任何麻煩。

主要特點：
- 創建並共享包含實時代碼、文本和可視化的互動式文檔
- 將Python、R、Julia、Scala等流行的編程語言與Jupyter集成
- 使用創新的技巧開發小工具和互動式儀表板

書籍描述：
Jupyter近來在數據科學界引起了強烈的興趣，因為它使常見的數據處理和分析任務變得更加簡單。本書針對希望掌握與Jupyter相關的各種任務，以創建高效、易於共享的科學應用程序的數據科學專業人士。

本書首先介紹了在各種平台上安裝和運行Jupyter筆記本系統以及配置可與之一起使用的各種套件的技巧。然後，您將了解如何在Jupyter筆記本上實現不同的編程語言和框架，例如Python、R、Julia、JavaScript、Scala和Spark。本書包含直觀的技巧，用於構建互動式小工具以實時操作和可視化數據，共享代碼，創建多用戶環境和組織筆記本。然後，您將親自體驗Jupyter Labs、微服務和在Web上部署它們。

通過閱讀本書，您將提升對Jupyter的知識，並能夠執行與之相關的所有關鍵任務。

您將學到：
- 安裝Jupyter並配置Python、R、Scala等引擎
- 在Jupyter筆記本上訪問和檢索數據
- 為不同場景創建互動式可視化和儀表板
- 使用HTML、JavaScript、Docker等將動態代碼轉換和共享
- 使用各種Jupyter小工具創建自定義用戶數據交互
- 管理用戶身份驗證和文件權限
- 與大數據互動，進行數值計算和統計建模
- 熟悉Jupyter的下一代用戶界面-JupyterLab

本書適合對數據科學概念有一定了解的數據科學專業人士、開發人員、技術數據分析師和程序員，他們希望在一個工具中執行技術編碼、可視化輸出和進行科學計算。