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)

Tutorial – looking at airline flight times data

This is a general tutorial aimed at finding interesting snippets of information from Flights data available in the nycflights13 package.

The dataset contains On-time data for all flights that departed NYC (i.e. JFK, LGA or EWR) in 2013 as per its description:

# First, install the package if you haven't already 
library(data,table) flights <- data.table(nycflights13::flights) flights # Get descriptive information about the dataset describe(flights)

The output of the preceding code is as follows:

We can also get descriptive information on a per NYC Airport basis:

# There are 3 major airports in the nycflights13 dataset 
# [1] "JFK" "EWR" "LGA" 
# Using, we can get descriptive...