Book Image

R Programming By Example

By : Omar Trejo Navarro
Book Image

R Programming By Example

By: Omar Trejo Navarro

Overview of this book

R is a high-level statistical language and is widely used among statisticians and data miners to develop analytical applications. Often, data analysis people with great analytical skills lack solid programming knowledge and are unfamiliar with the correct ways to use R. Based on the version 3.4, this book will help you develop strong fundamentals when working with R by taking you through a series of full representative examples, giving you a holistic view of R. We begin with the basic installation and configuration of the R environment. As you progress through the exercises, you'll become thoroughly acquainted with R's features and its packages. With this book, you will learn about the basic concepts of R programming, work efficiently with graphs, create publication-ready and interactive 3D graphs, and gain a better understanding of the data at hand. The detailed step-by-step instructions will enable you to get a clean set of data, produce good visualizations, and create reports for the results. It also teaches you various methods to perform code profiling and performance enhancement with good programming practices, delegation, and parallelization. By the end of this book, you will know how to efficiently work with data, create quality visualizations and reports, and develop code that is modular, expressive, and maintainable.
Table of Contents (12 chapters)

Activating our system with two simple functions

After you have loaded some data into the system, you will be able to execute the update-markets.R and update-assets.R files, whose contents are shown below. The first one loads the required definitions, as we did previously when creating the user data, and provides the update_markets_loop() function, which receives a parameter that specifies the number of minutes between each time the live market data is retrieved. Every 60 minutes is a good option, and it's what we use below. The function simply creates a Storage instance using the SETTINGS specification shown before, gets the existing exchanges (which is only CoinMarketCap at this point), and calls the public update_markets() method on each of them, with the corresponding parameters:

library(R6)
library(methods)

source("../storage/storage.R", chdir = TRUE)
source(&quot...