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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
Languages
Tools
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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

Introducing a basic data wrangling work flow


This chapter is about understanding the components of a program that processes data. As mentioned in the introduction, the approach taken here will be to process data on a basic level. A particular emphasis is placed on opening, reading and writing data in this chapter. Later chapters will focus more on exploration and modification of data.

The following is a basic work flow for data wrangling that applies to processing data files. Data wrangling is not necessarily a linear process, but these steps will help to give a frame of reference for the range of tools and approaches that will be demonstrated in this chapter and throughout the rest of the book.

  1. Open the file containing the input data from within the program:
    • In order for a program to gain access to the data in a particular file, the program first needs to interact with the computer's file system to open the file. This is referred to as file I/O and Python has built-in support to make this...
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