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You're reading from  Beginning Data Science with Python and Jupyter

Product typeBook
Published inJun 2018
Reading LevelBeginner
Publisher
ISBN-139781789532029
Edition1st Edition
Languages
Python
Tools
PandasJupyter
Concepts
Data Analysis
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Author (1)
Alex Galea
Alex Galea
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Alex Galea

Alex Galea has been professionally practicing data analytics since graduating with a masters degree in physics from the University of Guelph, Canada. He developed a keen interest in Python while researching quantum gases as part of his graduate studies. Alex is currently doing web data analytics, where Python continues to play a key role in his work. He is a frequent blogger about data-centric projects that involve Python and Jupyter Notebooks.
Read more about Alex Galea

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Summary

In this lesson, we scraped web page tables and then used interactive visualizations to study the data.

We started by looking at how HTTP requests work, focusing on GET requests and their response status codes. Then, we went into the Jupyter Notebook and made HTTP requests with Python using the Requests library. We saw how Jupyter can be used to render HTML in the notebook, along with actual web pages that can be interacted with. After making requests, we saw how Beautiful Soup can be used to parse text from the HTML, and used this library to scrape tabular data.

After scraping two tables of data, we stored them in pandas DataFrames. The first table contained the central bank interest rates for each country and the second table contained the populations. We combined these into a single table that was then used to create interactive visualizations.

Finally, we used Bokeh to render interactive visualizations in Jupyter. We saw how to use the Bokeh API to create various customized plots...

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Beginning Data Science with Python and Jupyter
Published in: Jun 2018Publisher: ISBN-13: 9781789532029
© 2018 Packt Publishing Limited All Rights Reserved

Author (1)

author image
Alex Galea

Alex Galea has been professionally practicing data analytics since graduating with a masters degree in physics from the University of Guelph, Canada. He developed a keen interest in Python while researching quantum gases as part of his graduate studies. Alex is currently doing web data analytics, where Python continues to play a key role in his work. He is a frequent blogger about data-centric projects that involve Python and Jupyter Notebooks.
Read more about Alex Galea

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