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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, Exploring, and Modifying Data - Part II

In the previous chapter, you learned how to apply Python programming to the task of processing data from external files. This chapter will build on the skills covered in the previous chapter with an introduction to the XML and CSV data formats. In addition to python's built-in tools for handling CSV and XML files, I will also cover pandas, which is a popular framework for working with tabular data. This chapter will include the following sections:

  • Logistical overview 
  • Understanding the CSV format
  • Introducing the csv module 
  • Using the csv module to read and process CSV data
  • Using the csv module to write CSV data
  • Using the pandas module to read and process data
  • Handling non-standard CSV encoding and dialect
  • Understanding XML
  • Using the xml.etree.ElementTree module to parse XML data
...
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