Found 2038 Articles for R Programming

Machine Learning ML is the investigation of PC calculations that learn without being unequivocally modified by people. They accomplish this by ingesting and preparing information, which assists them with recognizing examples and patterns. ML is generally pertinent in healthcare, marketing, medical services, logistics, human resources, energy, protection, e-commerce, manufacturing, art & creativity, finance, transportation, automobile, government & surveillance, insurance, and digital media and entertainment. Huge corporate goliaths like Apple, Google, Microsoft, IBM, and to a greater extent, use ML. In addition to the tech monsters, however little and mid-sized new companies likewise depend on ML. Most tech organizations use AI ... Read More

Data science may be a continually advancing field that requires an assorted set of aptitudes and instruments to keep up with the ever-changing information scene. While Python, R, and SQL are undoubtedly the foremost commonly utilized devices within the information science industry, there are a few other tools and advances that information researchers are anticipated to be capable of. In this article, we'll investigate a few of the other fundamental apparatuses that each information researcher ought to be recognizable with. Excel Excel may be an effective tool for data examination and is broadly utilized within the trading world. It ... Read More

Writing efficient code is very important as it makes the development time faster and leads our program to be able to understand, debug and maintain easily. We will discuss various techniques like benchmarking, vectorization and parallel programming to make our R code faster. You must learn these techniques if you are aspiring to be a data scientist. So, let’s get started − Benchmarking One of the easiest optimizations is to have the latest R version to work for. The new version cannot modify our existing code but it always comes with robust library functions that provide improved execution time. The ... Read More

The stringr package is a popular R package that provides functions and tools for manipulating and processing strings in R. This package provides a consistent and convenient interface for working with strings, and it offers a wide range of functions for tasks such as searching, matching, replacing, and splitting strings. In this article, we will discuss string manipulation in R with "stringr” package. The “stringr” package provides us the following families of functions in “stringr” − Character manipulating functions: Such functions allows us to deal with the characters of a string. A family of functions to deal with whitespaces. ... Read More

Most of the time, the R programmers encounter large data that causes problems as by default variables are stored in the memory. The R language doesn’t work well with a huge amount of data larger than 10% of the computer’s RAM. But data processing should be scalable if we want to excel in the field of data science. So, we will discuss how we can apply certain operations and use scalable data processing easily when the data is sufficiently larger than the computer’s RAM. The discussion would also be focussed on dealing with “out of core” objects. What is Scalable ... Read More

Object-oriented programming focuses on data and objects rather than procedures. The object-oriented model helps us to model real-life objects. It is important to master object-oriented programming concepts in order to excel in the field of data science. Each program has special types of classes. In this tutorial, the discussion will be focused on S3 and S4 classes in R, generic functions, inheritances between classes, and polymorphism. In this tutorial, we will discuss object-oriented programming concepts in R. Object-Oriented Programming in R Object oriented programming is a programming model that revolves around classes and objects rather than functions. In R we ... Read More

The R package collection known as tidyverse was created with the goal of collaborating and handling data effectively. The Tidyverse package is open-source and constantly improved by the data science community. A data scientist must have a fundamental understanding of every package included under the tidyverse umbrella. All eight packages—purr, ggplot2, dplyr, tidyr, stringr, tibble, readr, and forcats —will be covered in depth. Tidyverse Packages Tidyverse groups several packages in R. It consists of the following packages − Package Name Usage purrr Used for function programming ggplot2 Used for creating graphics dplyr ... Read More

The dates and times appear simple and easy at first impression as we deal with them in our day-to-day life. But a lot of complexity involves when we work with dates and times objects in R. This article focuses on working with dates and times using the lubridate package in R. You can install this package locally by using the following command in the CRAN’s terminal − install.packages("lubridate") Types of data/time objects in R There are three types of data/time objects and are listed below − Date () object − Prints the date. Time () object − Prints ... Read More

Parallel programming is a software development practice that involves dividing a computation or task into smaller parts that can be executed concurrently or in parallel. Parallel programming can help improve the performance and efficiency of your R code by utilizing multiple processors or cores in a computer or cluster. The main concept of parallel programming is, if one operation can be performed in S seconds using a single processor, then it should be able to get executed in S / N seconds when N processors are involved. Need for Parallel Programming in R Most of the time the code in ... Read More

The xts and zoo are two R packages that provide tools and functions for manipulating time series data. Both packages offer functions for reading, writing, and manipulating time series data stored in various formats, such as CSV, Excel, and other data sources. We shall start by introducing xts and zoo classes, basic manipulations, merging and modifying time series, and by the end, we will be discussing applying and aggregating by time. XTS and Zoo class Syntax In R, xts extends the zoo class. An xts object is similar to a matrix of observations that are indexed by a time object. ... Read More