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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

Product type Paperback

Published in Nov 2017

Publisher Packt

ISBN-13 9781787286139

Length 204 pages

Edition 1st Edition

Languages

Python

Tools

RStudio

Concepts

Data Analysis

Author (1):

Allan Visochek

View More author details

Table of Contents (10) Chapters

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

Logistical overview

In this chapter, I will do a demonstration of a single program called process_data.py. The process_data.py program will read a JSON file containing the data for this chapter, extract some of the variables from the data and output a new dataset to an output JSON file.

At the end of the chapter, I will demonstrate an alternative version of process_data.py called process_data2.py that allows for external specification of the input and output filenames.

The finished product for all of the code is available in the code folder of the external resources. All external resources are available at the following link: https://goo.gl/8S58ra.

Installation requirements

For this chapter, you will need the following:

Atom, an open source text editor created by GitHub
The latest version of Python 3

Links and guidelines for all of the installation requirements are made available in the Installation a part of the reference material. Visit https://goo.gl/8S58ra and find the Atom and Python 3 headlines...

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Authors (1)

Visochek

Visochek

Allan Visochek is a freelance web developer and data analyst in New Haven, Connecticut. Outside of work, Allan has a deep interest in machine learning and artificial intelligence. Allan thoroughly enjoys teaching and sharing knowledge. After graduating from the Udacity Data Analyst Nanodegree program, he was contracted to Udacity for several months as a forum mentor and project reviewer, offering guidance to students working on data analysis projects. He has also written technical content for LearnToProgram.

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