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Python Web Scraping Cookbook

You're reading from   Python Web Scraping Cookbook Over 90 proven recipes to get you scraping with Python, microservices, Docker, and AWS

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Product type Paperback
Published in Feb 2018
Publisher Packt
ISBN-13 9781787285217
Length 364 pages
Edition 1st Edition
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Author (1):
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Michael Heydt Michael Heydt
Author Profile Icon Michael Heydt
Michael Heydt
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Table of Contents (13) Chapters Close

Preface 1. Getting Started with Scraping FREE CHAPTER 2. Data Acquisition and Extraction 3. Processing Data 4. Working with Images, Audio, and other Assets 5. Scraping - Code of Conduct 6. Scraping Challenges and Solutions 7. Text Wrangling and Analysis 8. Searching, Mining and Visualizing Data 9. Creating a Simple Data API 10. Creating Scraper Microservices with Docker 11. Making the Scraper as a Service Real 12. Other Books You May Enjoy

Visualizing contributor location frequency on Wikipedia

We can use the collected data to determine the frequency of edits of Wikipedia articles from countries around the world. This can be done by grouping the captured data by country and counting the number of edits related to each country. Then we will sort the data and create a bar chart to see the results.

How to do it

This is a very simple task to perform with pandas. The code of the example is in 08/03_visualize_wikipedia_edits.py.

  1. The code begins by importing pandas and matplotlib.pyplot:
>>> import pandas as pd
>>> import matplotlib.pyplot as plt
  1. The data file we created in the previous recipe is already in a format that can be read directly by...
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