R Advanced

NULL represents a null object, and sometimes, it’s logical for the project to filter it out from either a list or data frame. Here are three ways to remove NULL values from a list in R: Using Filter() with Negate() and is.null() Using sapply() or lapply() with Subsetting Using purrr::discard() (Tidyverse Approach) For example, if … Read more

The basename() is a base R function that extracts the last component (or the ‘base name’) of a file or directory path and returns the name of the file or directory. So, if you have a path like “/Users/krunallathiya/Desktop/Code/pypro/data.pdf,“ basename() would return “data.pdf.“ The opposite function of basename() is dirname(), which gives the directory part of the path. Syntax basename(path) … Read more

The best and most efficient way to remove rows from a data frame is using “negative indexing”. It is a base R approach that does not require any packages. However, there are different approaches you should be aware of, depending on the situation you are encountering. Here are five ways: Using negative indexing (For single … Read more

Transposing means switching rows to columns and columns to rows. It is a common operation in the matrix.  The above figure shows that column names from the original data frame have become row names, and the first column values of the original data frame have become column names. Everything has been switched. Here are two … Read more

Here are the two most prominent ways to select rows by single or multiple conditions in R: Subsetting with [ ] Using dplyr::filter() Method 1: Subsetting with [ ] Subsetting with square brackets ([ ]) is a basic method for selecting rows where a column meets a specific condition. For example, df[df$column_name > value, ]. Here is … Read more

Here are the five ways to add single or multiple columns to a data frame in R: Using $ operator Using square ([ ]) notation Using cbind() Using tidyverse::add_column() Using dplyr::mutate() Let’s understand how this works behind the scenes. In the Data Frame, each column represents a vector. To add a column, we just need to … Read more

The square root of a number is a value that is multiplied by itself, giving the original number. For example, the square root of 16 is 4 because if you multiply 4 by 4, it will give us 16, so the original number is 4. To calculate the square root of a number, vector, matrix, … Read more

Duplicate rows refer to all the values across all columns that are the same in two or more rows. To avoid redundant data, we must remove duplicates from a data frame. For example, if the same row appears three times in a data frame, we must remove two rows because they are duplicates of one … Read more

A vector is a data structure that holds the same type of data. When working with real-time data, it may contain missing data, and it can be represented by NA (not available). For a proper data analysis, we need to exclude NA values from the vector. Now, you may have one question in your mind. … Read more

No matter how much technology has improved over the years for storing and sharing data, one format is still widely used in the industry: Excelsheet, which has file extensions like “.xls” or “.xlsx.“ Here are three ways to import Excel files in R: Using the readxl package (Efficient way) Using xlsx package RStudio’s Import Dataset tool For this tutorial’s … Read more