Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Hands-On Data Science with R

You're reading from   Hands-On Data Science with R Techniques to perform data manipulation and mining to build smart analytical models using R

Arrow left icon
Product type Paperback
Published in Nov 2018
Publisher Packt
ISBN-13 9781789139402
Length 420 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Authors (4):
Arrow left icon
Nataraj Dasgupta Nataraj Dasgupta
Author Profile Icon Nataraj Dasgupta
Nataraj Dasgupta
Vitor Bianchi Lanzetta Vitor Bianchi Lanzetta
Author Profile Icon Vitor Bianchi Lanzetta
Vitor Bianchi Lanzetta
Doug Ortiz Doug Ortiz
Author Profile Icon Doug Ortiz
Doug Ortiz
Ricardo Anjoleto Farias Ricardo Anjoleto Farias
Author Profile Icon Ricardo Anjoleto Farias
Ricardo Anjoleto Farias
Arrow right icon
View More author details
Toc

Table of Contents (16) Chapters Close

Preface 1. Getting Started with Data Science and R FREE CHAPTER 2. Descriptive and Inferential Statistics 3. Data Wrangling with R 4. KDD, Data Mining, and Text Mining 5. Data Analysis with R 6. Machine Learning with R 7. Forecasting and ML App with R 8. Neural Networks and Deep Learning 9. Markovian in R 10. Visualizing Data 11. Going to Production with R 12. Large Scale Data Analytics with Hadoop 13. R on Cloud 14. The Road Ahead 15. Other Books You May Enjoy

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 
 
install.packages("nycflights13") 
library(nycflights13)
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 
 
flights[,c(unique(origin))] 
# [1] "JFK" "EWR" "LGA" 
 
# Using describe.by, we can get descriptive...
lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at ₹800/month. Cancel anytime