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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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Allan Visochek Allan Visochek
Author Profile Icon Allan Visochek
Allan Visochek
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Table of Contents (10) Chapters Close

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

Using URL parameters to filter the results


In this section, I will retrieve all of the issue reports from the Seeclickfix API that occurred on the first day of January 2017. To start with, I will create a new file called get_scf_date_range.py, and import the requests module and the csv as follows:

import requests
import csv

The goal will be to gather all of the issue reports that occur during the first day of January 2017 and to store the results in a CSV file. In order to do this, you will need to make use of URLparameters. URL parameters are custom values that are added on to the end of a URL to further specify the get request.

The Seeclickfix API documentation on the issues resource shows a number of URL parameters that can be used. After looking through the Seeclickfix API documentation at http://dev.seeclickfix.com/v2/issues/, you may identify three particular parameters that are of use. The first two of these are the after and before parameters: 

These parameters can be used to specify...

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