How to Standardize Data Columns in R

How to Standardize Data Columns in R

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

How to Add Leading Zeros in R

How to Add Leading Zeros in R

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

How to Measure Function Execution Time in R

How to Measure Function Execution Time in R

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

How to Extract Specific Columns from a Data Frame in R

How to Extract Specific Columns from a Data Frame in R

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

How to Split a Vector into Chunks in R

How to Split a Vector into Chunks in R

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