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Beginning Data Science with Python and Jupyter

You're reading from   Beginning Data Science with Python and Jupyter Use powerful industry-standard tools within Jupyter and the Python ecosystem to unlock new, actionable insights from your data

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Product type Paperback
Published in Jun 2018
Publisher
ISBN-13 9781789532029
Length 194 pages
Edition 1st Edition
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Author (1):
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Alex Galea Alex Galea
Author Profile Icon Alex Galea
Alex Galea
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Chapter 3. Web Scraping and Interactive Visualizations

So far in this book, we have focused on using Jupyter to build reproducible data analysis pipelines and predictive models. We'll continue to explore these topics in this lesson, but the main focus here is data acquisition. In particular, we will show you how data can be acquired from the web using HTTP requests. This will involve scraping web pages by requesting and parsing HTML. We will then wrap up this lesson by using interactive visualization techniques to explore the data we've collected.

The amount of data available online is huge and relatively easy to acquire. It's also continuously growing and becoming increasingly important. Part of this continual growth is the result of an ongoing global shift from newspapers, magazines, and TV to online content. With customized newsfeeds available all the time on cell phones, and live-news sources such as Facebook, Reddit, Twitter, and YouTube, it's difficult...

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