R is capable of pulling the desired portion of data. Subsetting a data frame in R is the most essential part of data manipulation. We will go through subsetting data in detail.
Author: Data Science Team (Page 4 of 4)
Cleaning data is one of the most essential parts in data analysis. In this article, we learn how to clean the variable names, how to remove empty rows and columns, and how to remove duplicate rows.
Continue readingSometimes we need to export our results or data to other software. In this tutorial, you’ll learn how to export or write data from R or RStudio to .txt (tab-separated values), .csv (comma-separated values) and .xlsx (excel) file formats.
Continue readingR is capable of importing data from different file types. Reading data from .txt, .csv, .xlsx file types is the most popular way. We go through importing data into R from these file types in detail.
Continue readingR involves various data structures. Some of these structures in R are scalar, vector, matrix, array, data frame and list. We go through these data structures in detail.
Continue readingR includes a variety of data types. These are numeric, integer, logical, complex and character data types in R. We go through these data types in detail. We will look at the differences among them.
Continue readingR always points a default working directory. You will learn what is your working directory, how to change working directory and how to clear working directory in R or RStudio.
Continue readingIn this tutorial, we will discover how to install an R package and how to select a CRAN mirror in R. After its installation is completed, we will follow to call the R package in R console.
Continue readingIn this page, you will see how to download and install R for Windows. You can follow the steps given below.
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