Book Image

Jupyter for Data Science

By : Dan Toomey
Book Image

Jupyter for Data Science

By: Dan Toomey

Overview of this book

Jupyter Notebook is a web-based 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.
Table of Contents (17 chapters)
Title Page
Credits
About the Author
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface

Plotting using Plotly


Plotly is an interesting mix. It is a subscription website that provides significant data analysis graphing functionality. You can use the free version of the software, but you still need to log in with credentials to use it. The graphics functions are available in a variety of languages from Node.js to Python and the like.

Further, the graphics generated are available in Plotly and in your local notebook. If you mark the graphic as public, then you can access it from the notebook, just like any other graphic over the internet. Similarly, as a web graphic, you can select from the display and save locally as needed.

In this example, we use the voting histogram again, but using Plotly's capabilities.

The script becomes the following:

import plotlyimport plotly.graph_objs as goimport plotly.plotly as pyimport pandas as pdimport numpy as np#once you set credentials they are stored in local space and referenced automatically#you need to subscribe to the site to get the credentials...