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

Data scraping with a Python notebook


A common tool for data analysis is gathering the data from a public source such as a website. Python is adept at scraping websites for data. Here, we look at an example that loads stock price information from Google Finance data.

In particular, given a stock symbol, we want to retrieve the last year of price ranges for that symbol.

One of the pages on the Google Finance site will give the last years' worth of price data for a security company. For example, if we were interested in the price points for Advanced Micro Devices (AMD), we would enter the following URL:

https://www.google.com/finance/historical?q=NASDAQ:AMD

Here, NASDAQ is the stock exchange that carries the AMD security. On the resultant Google page, there is a table of data points of interest, as seen in the following partial screenshot.

Like many sites that you will be attempting to access, there is a lot of other information on the page as well, like headers and footers and ads, as you can see...