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The Applied Data Science Workshop

You're reading from The Applied Data Science Workshop Get started with the applications of data science and techniques to explore and assess data effectively

Product type Paperback

Published in Jul 2020

Publisher Packt

ISBN-13 9781800202504

Length 352 pages

Edition 2nd Edition

Languages

Python

Tools

Jupyter

Concepts

Data Science

Author (1):

Alex Galea

View More author details

Table of Contents (8) Chapters

Preface

Installing Libraries

1. Introduction to Jupyter Notebooks

2. Data Exploration with Jupyter FREE CHAPTER

3. Preparing Data for Predictive Modeling

4. Training Classification Models

5. Model Validation and Optimization

6. Web Scraping with Jupyter Notebooks

Appendix

Summary

In this chapter, we worked through the process of pulling tables from Wikipedia using web scraping techniques, cleaning up the resulting data with pandas, and producing a final analysis.

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. In order to learn about web scraping, we saw how BeautifulSoup can be used to parse text from the HTML, and used this library to scrape tabular data from Wikipedia.

After pulling two tables of data, we processed them for analysis with pandas. The first table contained the central bank interest rates for each country, while the second table contained the populations. We combined these into a single table that was then used for the final analysis, which involved...

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Authors (1)

Galea

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.

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