Book Image

Modern R Programming Cookbook

By : Jaynal Abedin
Book Image

Modern R Programming Cookbook

By: Jaynal Abedin

Overview of this book

R is a powerful tool for statistics, graphics, and statistical programming. It is used by tens of thousands of people daily to perform serious statistical analyses. It is a free, open source system whose implementation is the collective accomplishment of many intelligent, hard-working people. There are more than 2,000 available add-ons, and R is a serious rival to all commercial statistical packages. The objective of this book is to show how to work with different programming aspects of R. The emerging R developers and data science could have very good programming knowledge but might have limited understanding about R syntax and semantics. Our book will be a platform develop practical solution out of real world problem in scalable fashion and with very good understanding. You will work with various versions of R libraries that are essential for scalable data science solutions. You will learn to work with Input / Output issues when working with relatively larger dataset. At the end of this book readers will also learn how to work with databases from within R and also what and how meta programming helps in developing applications.
Table of Contents (10 chapters)

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