Book description
Your onestop guide to building an efficient data science pipeline using Jupyter
About This Book
 Get the most out of your Jupyter notebook to complete the trickiest of tasks in Data Science
 Learn all the tasks in the data science pipeline  from data acquisition to visualization  and implement them using Jupyter
 Get ahead of the curve by mastering all the applications of Jupyter for data science with this unique and intuitive guide
Who This Book Is For
This book targets students and professionals who wish to master the use of Jupyter to perform a variety of data science tasks. Some programming experience with R or Python, and some basic understanding of Jupyter, is all you need to get started with this book.
What You Will Learn
 Understand why Jupyter notebooks are a perfect fit for your data science tasks
 Perform scientific computing and data analysis tasks with Jupyter
 Interpret and explore different kinds of data visually with charts, histograms, and more
 Extend SQL's capabilities with Jupyter notebooks
 Combine the power of R and Python 3 with Jupyter to create dynamic notebooks
 Create interactive dashboards and dynamic presentations
 Master the best coding practices and deploy your Jupyter notebooks efficiently
In Detail
Jupyter Notebook is a webbased environment that enables interactive computing in notebook documents. It allows you to create documents that contain live code, equations, and visualizations. This book is a comprehensive guide to getting started with data science using the popular Jupyter notebook.
If you are familiar with Jupyter notebook and want to learn how to use its capabilities to perform various data science tasks, this is the book for you! From data exploration to visualization, this book will take you through every step of the way in implementing an effective data science pipeline using Jupyter. You will also see how you can utilize Jupyter's features to share your documents and codes with your colleagues. The book also explains how Python 3, R, and Julia can be integrated with Jupyter for various data science tasks.
By the end of this book, you will comfortably leverage the power of Jupyter to perform various tasks in data science successfully.
Style and approach
This book is a perfect blend of concepts and practical examples, written in a way that is very easy to understand and implement. It follows a logical flow where you will be able to build on your understanding of the different Jupyter features with every chapter.
Publisher resources
Table of contents
 Preface

Jupyter and Data Science
 Jupyter concepts

A first look at the Jupyter user interface
 Detailing the Jupyter tabs
 What actions can I perform with Jupyter?
 What objects can Jupyter manipulate?
 Viewing the Jupyter project display
 How does it look when we execute scripts?
 Industry data science usage
 Real life examples
 Using Docker with Jupyter
 How to share notebooks with others
 How can you secure a notebook?
 Summary
 Working with Analytical Data on Jupyter
 Data Visualization and Prediction
 Data Mining and SQL Queries
 R with Jupyter
 Data Wrangling
 Jupyter Dashboards
 Statistical Modeling
 Machine Learning Using Jupyter
 Optimizing Jupyter Notebooks
Product information
 Title: Jupyter for Data Science
 Author(s):
 Release date: October 2017
 Publisher(s): Packt Publishing
 ISBN: 9781785880070
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