Functional programming is a programming methodology in which we construct programs by constructing and applying functions. More specifically in programs, we apply sequential pure functions rather than statements. A pure function is a function that accepts an input and produces a consistent value as an output. Also, during this process ... Read More

In data science, one of the common tasks is dealing with missing data. If we have missing data in your dataset, there are several ways to handle it in R programming. One way is to simply remove any rows or columns that contain missing data. Another way to handle missing ... 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 ... 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. ... 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 ... 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 ... 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, ... 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 ... 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 ... 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 ... Read More