Krunal Lathiya 
To create an empty data frame in R, “specify the column names and set the number of rows to 0 using the data.frame() function”. df <- data.frame(name = character(0), address = character(0), date = as.Date(character(0)), stringsAsFactors = FALSE) str(df) Output ‘data.frame’: 0 obs. of 3 variables: $ date: ‘Date’ num(0) $ file: chr $ user: … Read more
The if else statement in R “evaluates a condition and executes different statements based on whether the condition is TRUE or FALSE”. Syntax if (condition) { expression A } else { expression B } Here, the “condition” is an expression that evaluates to TRUE or FALSE. If the condition is TRUE, the code within the first … Read more
In R, you can add comments to your code using the “hash symbol (#)”. Any text following the hash symbol on the same line will be treated as a comment and will not be executed. Comments help explain your code, making it more readable and understandable. Single-Line Comments in R R only supports single-line comments … Read more
An operator in R is a symbol that tells the compiler to perform a mathematical or logical operation. Types of operators Arithmetic Operators Relational Operators Logical Operators Assignment Operators Miscellaneous Operators Arithmetic Operators in R Add(+) operator in R To add two vectors, you can use the “+ operator”. a <- c(1, 2, 3) b … Read more
Variables in R can store an atomic vector, a group of atomic vectors, or different R Objects. To consider a valid variable name in R, the name consists of letters, numbers, and a dot or underlined characters. In the current version of R, there is support for underscore (_) as a valid identifier. Still, it … Read more
R data types are the essential features that accept and store various data types. Some of the most common data types in R are: numeric: Decimal numbers like 10.5, 55, 787. integer: Whole numbers like 1L, 55L, and 100L (the letter “L” declares this as an integer). character: Strings of text like “hello”, “R”, and … Read more
To find the second and third lowest values in R Data Frame Column, you can use the “sort()” method. Example df <- data.frame( name = c(“A”, “B”, “C”, “D”, “E”, “F”, “G”), value = c(51, 12, 41, 21, 20, 81, 11) ) # Second and third lowest values sorted_values_asc <- sort(df$value, decreasing = FALSE) second_lowest_value … Read more
To find the second and third highest values in R Data Frame Column, you can use the “sort()” method. Example # Sample data frame df <- data.frame(name = c(“A”, “B”, “C”, “D”, “E”, “F”, “G”), value = c(51, 12, 41, 21, 20, 81, 11)) # Second and third highest values sorted_values_desc <- sort(df$value, decreasing = … Read more
To find the second and third lowest values in R Vector, you can use the “sort()” method. rv <- c(5, 12, 4, 2, 20, 8, 1) # Second and third lowest values sorted_rv_asc <- sort(rv, decreasing = FALSE) second_lowest <- sorted_rv_asc[2] third_lowest <- sorted_rv_asc[3] cat(“Second lowest value in vector:”, second_lowest, “\n”) cat(“Third lowest value in … Read more
To find the second and third highest values in R Vector, you can use the “sort()” method. x <- c(5, 12, 4, 2, 20, 8, 1) # Second and third highest values sorted_x_desc <- sort(x, decreasing = TRUE) second_highest <- sorted_x_desc[2] third_highest <- sorted_x_desc[3] cat(“Second highest value in vector:”, second_highest, “\n”) cat(“Third highest value in … Read more