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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

Reading the contents of a file


A data file, like Python code, is simply a collection of text that follows a set of syntactical rules. In order for a Python program to make use of the data in the data file, it has to be converted to a data structure that can be processed programmatically.

Reading a file typically refers to the process a program uses to collect raw data, while converting data from a raw text format to a data structure is called parsing the data. The term reading a file can also refer to both collecting and parsing data. Usually, there are tools that take care of reading and parsing the data for you. In order to parse the JSON data in this chapter, I will be using Python's built-in json module. As mentioned previously, the structure of Python dictionaries and arrays correspond to the structures of JSON data, so representing JSON data in Python is quite intuitive.

Modules in Python

A Python module is a set of already made code that can be included in a program to add on extra functionality...

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