Book Image

Hands-On Data Science with R

By : Vitor Bianchi Lanzetta, Doug Ortiz, Nataraj Dasgupta, Ricardo Anjoleto Farias
Book Image

Hands-On Data Science with R

By: Vitor Bianchi Lanzetta, Doug Ortiz, Nataraj Dasgupta, Ricardo Anjoleto Farias

Overview of this book

R is the most widely used programming language, and when used in association with data science, this powerful combination will solve the complexities involved with unstructured datasets in the real world. This book covers the entire data science ecosystem for aspiring data scientists, right from zero to a level where you are confident enough to get hands-on with real-world data science problems. The book starts with an introduction to data science and introduces readers to popular R libraries for executing data science routine tasks. This book covers all the important processes in data science such as data gathering, cleaning data, and then uncovering patterns from it. You will explore algorithms such as machine learning algorithms, predictive analytical models, and finally deep learning algorithms. You will learn to run the most powerful visualization packages available in R so as to ensure that you can easily derive insights from your data. Towards the end, you will also learn how to integrate R with Spark and Hadoop and perform large-scale data analytics without much complexity.
Table of Contents (16 chapters)

Installing the package and Spark

To begin, you need to install a few packages and the Spark itself. To do it, call the following codes; it can take some time to download Spark:

install.packages(c("dplyr", "sparklyr", "DAAG"))
library(sparklyr); library(dplyr)

#installing Spark

The DAAG package contains the dataset we are going to use. So, let's start our learning. This chapter is divided into five sections plus this introduction. The next section teaches you how to manipulate Spark data using dplyr and SQL query. In the second section, we bring Spark data into R, for analysis and visualization. The third section shows how to use the Spark or the H2O machine learning algorithms. The fourth section presents the Spark API. Lastly, there is a final section to see the Spark connection on RStudio IDE.