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Practical Data Wrangling

You're reading from   Practical Data Wrangling Expert techniques for transforming your raw data into a valuable source for analytics

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Product type Paperback
Published in Nov 2017
Publisher Packt
ISBN-13 9781787286139
Length 204 pages
Edition 1st Edition
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Author (1):
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 Visochek Visochek
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Visochek
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Table of Contents (16) Chapters Close

Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
1. Programming with Data FREE CHAPTER 2. Introduction to Programming in Python 3. Reading, Exploring, and Modifying Data - Part I 4. Reading, Exploring, and Modifying Data - Part II 5. Manipulating Text Data - An Introduction to Regular Expressions 6. Cleaning Numerical Data - An Introduction to R and RStudio 7. Simplifying Data Manipulation with dplyr 8. Getting Data from the Web 9. Working with Large Datasets

Chapter 8. Getting Data from the Web

It is convenient to contain and distribute small amounts of data using static files. Files work well for sources of data that are low volume, self contained, and infrequently updated. Many sources of data, however, are a part of massive web applications or data archives that are updated constantly. Sources, such as Wikipedia and Seeclickfix, that store data in large databases will often make their data available through APIs (application programming interfaces) that allow users to retrieve small selections of the data. In fact, the Seeclickfix and Wikipedia datasets used in previous chapters were obtained using APIs.

In this chapter, I will walk through the steps of using Python to retrieve the data from the Seeclickfix API. This chapter will include the following sections:

  • Logistical overview
  • Introducing APIs
  • Using Python to retrieve data from APIs
  • Using URL parameters to filter the results
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