Book Image

Data Analysis with R, Second Edition - Second Edition

Book Image

Data Analysis with R, Second Edition - Second Edition

Overview of this book

Frequently the tool of choice for academics, R has spread deep into the private sector and can be found in the production pipelines at some of the most advanced and successful enterprises. The power and domain-specificity of R allows the user to express complex analytics easily, quickly, and succinctly. Starting with the basics of R and statistical reasoning, this book dives into advanced predictive analytics, showing how to apply those techniques to real-world data though with real-world examples. Packed with engaging problems and exercises, this book begins with a review of R and its syntax with packages like Rcpp, ggplot2, and dplyr. From there, get to grips with the fundamentals of applied statistics and build on this knowledge to perform sophisticated and powerful analytics. Solve the difficulties relating to performing data analysis in practice and find solutions to working with messy data, large data, communicating results, and facilitating reproducibility. This book is engineered to be an invaluable resource through many stages of anyone’s career as a data analyst.
Table of Contents (24 chapters)
Title Page
Copyright and Credits
Packt Upsell
Contributors
Preface
Index

Using JSON


Javascript Object Notation (JSON) is a standardized human-readable data format that plays an enormous role in communication between web browsers and web servers. JSON was originally borne out of a need to represent arbitrarily complex data structures in Javascript, a web scripting language, but it has since grown into a language agnostic data serialization format.

It is a common need to import and parse JSON in R, particularly when working with web data. For example, it is very common for websites to offer web services that take an arbitrary query from a web browser, and return the response as JSON. We will look at an example of this very use case later in this section.

For our first look into JSON parsing for R, we'll use the jsonlite package to read a small JSON string, which serializes some information about the best musical act in history, The Beatles:

library(jsonlite) 
 
example.json <- ' 
{ 
  "thebeatles": { 
    "formed": 1960, 
    "members": [ 
      { 
        "firstname...