Learning Jupyter 5 : Explore Interactive Computing Using Python, Java, JavaScript, R, Julia, and JupyterLab, 2nd Edition

Create and share livecode, equations, visualizations, and explanatory text, in both a single document and a web browser with Jupyter Key Features Learn how to use Jupyter 5.x features such as cell tagging and attractive table styles Leverage big data tools and datasets with different Python packages Explore multiple-user Jupyter Notebook servers Book Description The Jupyter Notebook allows you to create and share documents that contain live code, equations, visualizations, and explanatory text. The Jupyter Notebook system is extensively used in domains such as data cleaning and transformation, numerical simulation, statistical modeling, and machine learning. Learning Jupyter 5 will help you get to grips with interactive computing using real-world examples. The book starts with a detailed overview of the Jupyter Notebook system and its installation in different environments. Next, you will learn to integrate the Jupyter system with different programming languages such as R, Python, Java, JavaScript, and Julia, and explore various versions and packages that are compatible with the Notebook system. Moving ahead, you will master interactive widgets and namespaces and work with Jupyter in a multi-user mode. By the end of this book, you will have used Jupyter with a big dataset and be able to apply all the functionalities you've explored throughout the book. You will also have learned all about the Jupyter Notebook and be able to start performing data transformation, numerical simulation, and data visualization. What you will learn Install and run the Jupyter Notebook system on your machine Implement programming languages such as R, Python, Julia, and JavaScript with the Jupyter Notebook Use interactive widgets to manipulate and visualize data in real time Start sharing your Notebook with colleagues Invite your colleagues to work with you on the same Notebook Organize your Notebook using Jupyter namespaces Access big data in Jupyter for dealing with large datasets using Spark Who this book is for Learning Jupyter 5 is for developers, data scientists, machine learning users, and anyone working on data analysis or data science projects across different teams. Data science professionals will also find this book useful for performing technical and scientific computing collaboratively. Downloading the example code for this book You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If ... Annotation Develop, deploy, and streamline your data science projects with the most popular end-to-end platform, AnacondaKey Features-Use Anaconda to find solutions for clustering, classification, and linear regression-Analyze your data efficiently with the most powerful data science stack-Use the Anaconda cloud to store, share, and discover projects and librariesBook DescriptionAnaconda is an open source platform that brings together the best tools for data science professionals with more than 100 popular packages supporting Python, Scala, and R languages. Hands-On Data Science with Anaconda gets you started with Anaconda and demonstrates how you can use it to perform data science operations in the real world. The book begins with setting up the environment for Anaconda platform in order to make it accessible for tools and frameworks such as Jupyter, pandas, matplotlib, Python, R, Julia, and more. You'll walk through package manager Conda, through which you can automatically manage all packages including cross-language dependencies, and work across Linux, macOS, and Windows. You'll explore all the essentials of data science and linear algebra to perform data science tasks using packages such as SciPy, contrastive, scikit-learn, Rattle, and Rmixmod. Once you're accustomed to all this, you'll start with operations in data science such as cleaning, sorting, and data classification. You'll move on to learning how to perform tasks such as clustering, regression, prediction, and building machine learning models and optimizing them. In addition to this, you'll learn how to visualize data using the packages available for Julia, Python, and R. What you will learnPerform cleaning, sorting, classification, clustering, regression, and dataset modeling using AnacondaUse the package manager conda and discover, install, and use functionally efficient and scalable packagesGet comfortable with heterogeneous data exploration using multiple languages within a projectPerform distributed computing and use Anaconda Accelerate to optimize computational powersDiscover and share packages, notebooks, and environments, and use shared project drives on Anaconda CloudTackle advanced data prediction problemsWho this book is forHands-On Data Science with Anaconda is for you if you are a developer who is looking for the best tools in the market to perform data science. It's also ideal for data analysts and data science professionals who want to improve the efficiency of their data science applications by using the best libraries in multiple languages. Basic programming knowledge with R or Python and introductory knowledge of linear algebra is expected 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. Create and share livecode, equations, visualizations, and explanatory text, in both a single document and a web browser with Jupyter Key Features Learn how to use Jupyter 5.x features such as cell tagging and attractive table styles Leverage big data tools and datasets with different Python packages Explore multiple-user Jupyter Notebook servers Book Description The Jupyter Notebook allows you to create and share documents that contain live code, equations, visualizations, and explanatory text. The Jupyter Notebook system is extensively used in domains such as data cleaning and transformation, numerical simulation, statistical modeling, and machine learning. Learning Jupyter 5 will help you get to grips with interactive computing using real-world examples. The book starts with a detailed overview of the Jupyter Notebook system and its installation in different environments. Next, you will learn to integrate the Jupyter system with... COM018000 - COMPUTERS / Data Processing,COM089000 - COMPUTERS / Data Visualization,COM062000 - COMPUTERS / Data Modeling and Design In this book, you will learn how to build interactive dashboards in a Jupyter notebook. Explore JupyterHub and various Jupyter widgets through which you can easily perform 3D data visualization, 3D plotting, and geospatial analytics. This book helps you understand BeakerX to create interactive tables and interact with spreadsheets. Hands-On Data Science with Anaconda gets you started with Anaconda and demonstrates how you can use it to perform data science operations in the real world. You will learn different ways to retrieve data from various sources and different visualization tools packages available in Python, R, and Julia.