How to use mutate function in R?
This recipe helps you use mutate() function in R
Recipe Objective
It is essential to learn mutate() function which is one of the fundamental tools in data manipulation in R. This function is available in dplyr package which is an add-on package most widely used to carry out data manipulation tasks. ​
The mutate() function is mainly used to create new variables by manipulating existing variables or using some pre-defined values/functions.
There things you need to use mutate() function are the name of a dataframe, name of the new variable and the value to be assigned to that new variable.
Example Syntax: mutate(dataframe, name_ of_new_variable = name_of_existing_variable^2)
In this recipe, we will learn how to mutate a column using dplyr package in R ​
Step 1: Loading the required library and Creating a DataFrame
Creating a STUDENT dataframe with Name and marks of two subjects in 3 Trimester exams. ​
# data manipulation
library(dplyr)
library(tidyverse)
STUDENT = data.frame(Name = c("Ram","Ram", "Ram", "Shyam", "Shyam", "Shyam", "Jessica", "Jessica", "Jessica"),
Science_Marks = c(55, 60, 65, 80, 70, 75, 45, 65, 70),
Math_Marks = c(70, 75, 73, 50, 53, 55, 65, 78, 75),
Trimester = c(1, 2, 3, 1, 2, 3, 1, 2, 3))
glimpse(STUDENT)
Rows: 9 Columns: 4 $ NameRam, Ram, Ram, Shyam, Shyam, Shyam, Jessica, Jessica,... $ Science_Marks 55, 60, 65, 80, 70, 75, 45, 65, 70 $ Math_Marks 70, 75, 73, 50, 53, 55, 65, 78, 75 $ Trimester 1, 2, 3, 1, 2, 3, 1, 2, 3
Step 2: Application of mutate Function
# to check the various arguements of the function
?mutate()
Query: To create a new variable Total marks by summing up the marks in each subject (in Trimester 1, 2 and 3) ​
query_1 = mutate(STUDENT, Total_marks = Science_Marks+Math_Marks)
glimpse(query_1)
Rows: 9 Columns: 5 $ NameRam, Ram, Ram, Shyam, Shyam, Shyam, Jessica, Jessica,... $ Science_Marks 55, 60, 65, 80, 70, 75, 45, 65, 70 $ Math_Marks 70, 75, 73, 50, 53, 55, 65, 78, 75 $ Trimester 1, 2, 3, 1, 2, 3, 1, 2, 3 $ Total_marks 125, 135, 138, 130, 123, 130, 110, 143, 145
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