Jupyter Cookbook

Leverage the power of the popular Jupyter notebooks to simplify your data science tasks without any hassleKey FeaturesCreate and share interactive documents with live code text and visualizationsIntegrate popular programming languages such as Python R Julia Scala with JupyterDevelop your widgets and interactive dashboards with these innovative recipesBook DescriptionJupyter 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 learnInstall Jupyter and configure engines for Python R Scala and moreAccess and retrieve data on Jupyter NotebooksCreate interactive visualizations and dashboards for different scenariosConvert and share your dynamic codes using HTML JavaScript Docker and moreCreate custom user data interactions using various Jupyter widgetsManage user authentication and file permissionsInteract with Big Data to perform numerical computing and statistical modelingGet familiar with Jupyters next-gen user interface - JupyterLabWho this book is forThis 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.