# How to add calculated variables in R

Add calculated variables in R, To add new calculated variables to a data frame and remove all old variables, use the transmute() function in R.

The following is the fundamental syntax for this function.

`df %>% transmute(var_new = var1 * 2)`

In this example, we’ll make a new variable called var new by multiplying an existing variable called var1 by 2.

The examples below demonstrate how to use the transmute() function in R with the following data frame.

Let’s create a data frame

```df <- data.frame(team=c('A1', 'B1', 'C1', 'D1', 'E1'),
score=c(89, 70, 76, 78, 75))```

Now we can view the data frame

`df`
```  team score
1   A1    89
2   B1    70
3   C1    76
4   D1    78
5   E1    75```

## Example 1: Create One New Variable using transmute()

The following code demonstrates how to create a new variable with transmute():

`library(dplyr)`

create a new variable called score1

`df %>% transmute(score1 = score * 2)`
```   score1
1    178
2    140
3    152
4    156
5    150```

The original values in the score column are multiplied by two to get the score1 values.

It’s worth noting that the transmute() function doesn’t change the original data frame.

You must save the results of the transmute() method in a variable to save them in a new data frame:

`library(dplyr)`

Transmute results are saved in a variable.

`df\$score1<- df %>% transmute(score1 = score * 2)`

View the results

`df`
```  team score score1
1   A1    89    178
2   B1    70    140
3   C1    76    152
4   D1    78    156
5   E1    75    150```

The results of transmute() are now stored in a data frame.

## Example 2: Create Multiple New Variables using transmute()

Transmute() can be used to create several new variables from existing variables, as shown in the following code.

`library(dplyr)`

Let’s create a multiple new variables.

Group wise Correlation in R » finnstats

```df %>%
transmute(
score1 = score * 2,
scoresquared = score^2,
scorehalf = score / 2,
name= paste0('team_', team)
)```
```  score1 scoresquared scorehalf    name
1    178         7921      44.5 team_A1
2    140         4900      35.0 team_B1
3    152         5776      38.0 team_C1
4    156         6084      39.0 team_D1
5    150         5625      37.5 team_E1```

Four new variables have been created, as you can see.