To standardize the data column in R, you can use the scale() function or manually calculate the mean and standard deviation. Method 1: Using the scale() function # Create a data frame df <- data.frame( A = c(21, 19, 46), B = c(11, 18, 20) ) # Standardize the data columns standardized_data <- scale(df) # Print … Read more
To add leading zeros to a number or a vector of numbers in R, you can use the sprintf() function or the str_pad() function from the stringr package. Method 1: Using the sprintf() function # Define the number number <- 21 # Specify the total number of digits (including leading zeros) total_digits <- 5 # … Read more
To measure a function execution time in R, you can use the system.time() function. # Define a simple function to calculate the sum of integers from 1 to n sum_integers <- function(n) { return(sum(1:n)) } # Measure the execution time of the function execution_time <- system.time({ result <- sum_integers(1000000) }) # Print the execution time … Read more
To extract the last n characters from a string in R, you can use the substr() function along with the nchar() function. # Define the string main_string <- “John Wick 4!” # Specify the number of characters to extract n <- 7 # Calculate the starting position for extraction start_position <- nchar(main_string) – n + 1 … Read more
There are the following methods to extract specific columns from the data frame in R. Method 1: Using the dplyr package’s select() function You can use the dplyr package’s select() function to extract columns as variable names from the R data frame. library(dplyr) df <- data.frame( name = c(“Krunal”, “Ankit”, “Rushabh”, “Niva”), age = c(30, … Read more
To get a last value of a vector in R, you can use the length() function to get the index of the last element. # Define the vector main_vector <- c(11, 21, 18, 46, 19) # Access the last value of the vector last_element <- main_vector[length(main_vector)] # Print the last value print(last_element) Output [1] 19 … Read more
To split a vector into chunks in R, you can use the split() function along with the ceiling() and seq_along() functions. # Define the vector main_vector <- 1:24 # Specify the chunk size chunk_size <- 6 # Create an index for splitting index <- ceiling(seq_along(main_vector) / chunk_size) # Split the vector into chunks chunked_vector <- … Read more
To remove multiple elements from a list in R: Method 1: Using the negative indexing Method 2: Using Filter and %in% operator Method 3: Using lapply and sapply with != operator Method 1: Using negative indexing To remove multiple elements by their positions in the list, you can use negative indexing. For example, to remove … Read more
There are three methods to remove an element from a list in R. Method 1: Using the negative indexing You can use negative indexing to remove an element at a specific position from the list in R. For example, remove the second element from the main_list using the main_list[–2] expression. main_list <- list(“bmw”, “audi”, “benley”, … Read more
To split the data frame string column into multiple columns in R, you can use the separate() function from the tidyverse package or the str_split_fixed() function along with the dplyr package. Method 1: Using the separate() function You can use the separate() function from the tidyverse package to split a data frame column into multiple columns … Read more