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Modern R Programming Cookbook

You're reading from Modern R Programming Cookbook Recipes to simplify your statistical applications

Product type Paperback

Published in Oct 2017

Publisher Packt

ISBN-13 9781787129054

Length 236 pages

Edition 1st Edition

Languages

R

Concepts

Programming Language

Author (1):

Jaynal Abedin

View More author details

Table of Contents (16) Chapters

Title Page

Credits

About the Author

About the Reviewer

www.PacktPub.com

Customer Feedback

Preface

1. Installing and Configuring R and its Libraries FREE CHAPTER

2. Data Structures in R

3. Writing Customized Functions

4. Conditional and Iterative Operations

5. R Objects and Classes

6. Querying, Filtering, and Summarizing

7. R for Text Processing

8. R and Databases

9. Parallel Processing in R

Comparing computation time with data frame and XDF

Computation time is one of the important things to consider while doing big data analytics. The efficiency of the algorithm is assessed by the computation time along with other parameters. The objective of using an XDF file instead of the default R data frame is to achieve high speed computation. In this recipe, you will compare the performance in terms of computation time using the default data frame and the XDF file.

Getting ready

Suppose you have a dataset stored in two different formats. The first one is an CSV file containing nine variables, and the other one is the XDF file containing the same variables. The following are the variable names:

YEAR
QUARTER
MONTH
DAY_OF_MONTH
DAY_OF_WEEK
ORIGIN
DEST
DEP_DELAY
ARR_DELAY

The objective is to calculate mean departure delay for each combination of origin and destination airports. The required library for this recipe is RevoScaleR.

How to do it…

The following are the steps to calculate the processing time...

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Authors (1)

Jaynal Abedin

Jaynal Abedin

Jaynal Abedin currently holds the position of Statistician at the Centre for Communicable Diseases (CCD) at icddr,b ( www.icddrb.org). He attained his Bachelor's and Master's degrees in Statistics from the University of Rajshahi, Rajshahi, Bangladesh. He has vast experience in R programming and Stata and has efficient leadership qualities. He is currently leading a team of statisticians. He has hands-on experience in developing training material and facilitating training in R programming and Stata along with statistical aspects in public health research. His primary area of interest in research includes causal inference and machine learning. He is currently involved in several ongoing public health research projects and is a co-author of several work-in-progress manuscripts. In the useR! Conference 2013, he presented a poster—edeR: Email Data Extraction using R, available at http://www.edii.uclm.es/~useR-2013/abstracts/files/34_edeR_Email_Data_Extraction_using_R.pdf—and obtained the best application poster award. He is also involved in reviewing scientific manuscripts for the Journal of Applied Statistics (JAS) and the Journal of Health Population and Nutrition (JHPN). He is also a successful freelance statistician on online platforms and has an excellent reputation through his high-quality work, especially in R programming. He can be contacted at [email protected], http://bd.linkedin.com/in/jaynal; his Twitter handle is @jaynal83.

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