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[null,"1.","Record Nr.",null,"UNINA9910820826103321"]
[null,null,"Autore",null,"Toomey Dan"]
[null,null,"Titolo",null,"Jupyter cookbook : over 75 recipes to perform interactive computing across Python, R, Scala, Spark, JavaScript, and more / / Dan Toomey"]
[null,null,"Pubbl/distr/stampa",null,"Birmingham ; ; Mumbai : , : Packt, , [2018]"]
[{"$nulls":4},"2018"]
[null,null,"Edizione",null,"[1st edition]"]
[null,null,"Descrizione fisica",null,"1 online resource (238 pages)"]
[null,null,"Disciplina",null,"005.434"]
[null,null,"Soggetti",null,"Command languages (Computer science)"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Sommario/riassunto","Leverage the power of the popular Jupyter notebooks to simplify your data science tasks without any hassle About This Book 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 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. 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 In Detail 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 "]
[{"$nulls":4},"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. Style and approach The recipes in this book are highly practical and very easy to follow, and include tips and tricks that will help you crack any problem that you might com..."]