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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 I

Even if you are new to programming, opening, modifying and saving files within programs should be a relatively familiar process. You have likely opened and edited a document with a word processor or entered data into an Excel spread sheet.

Like a computer program, a dataset can be represented using a text file with a specific syntactical structure. The text in a data file specifies both the information contained in the data and the structure in which that information is placed. In a sense, writing a program to process data files is a similar to the process of editing a document or a spreadsheet. First, the content of a file is opened, observed, and modified, and then the result is saved.

Another general strategy to store and retrieve digital data is to use a database. Databases are organized collections of data that allow for efficient...
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