What this book covers

Chapter 1, Programming with Data, discusses the context of data wrangling and offers a high-level overview of the rest of the book's content.

Section 1: A generalized programming approach to data wrangling

Chapter 2, Introduction to Programming in Python, introduces programming using the Python programming language, which used in most of the chapters of the book.

Chapter 3, Reading, Exploring, and Modifying Data - Part I, is an overview of the steps for processing a data file and an introduction to JSON data.

Chapter 4, Reading, Exploring, and Modifying Data - Part II, continues from the previous chapter, extending to the CSV and XML data formats.

Chapter 5, Manipulating Text Data - An Introduction to Regular Expressions, is an introduction to regular expressions with the application of extracting street names from street addresses.

Section 2: A formulated approach to data wrangling

Chapter 6, Cleaning Numerical Data - An Introduction to R and RStudio, introduces R and RStudio with the application of cleaning numerical data.

Chapter 7, Simplifying Data Manipulation with dplyr, is an introduction to the dplyr package for R, which can be used to express multiple data processing steps elegantly and concisely.

Section 3: Advanced methods for retrieving and storing data

Chapter 8, Getting Data from the Web, is an introduction to APIs. This chapter shows how to extract data from APIs using Python.

Chapter 9, Working with Large Datasets, has an overview of the issues when working with large amounts of data and a very brief introduction to MongoDB.