## Issue

Here’s my example dataframe:

```
data <- data.frame(matrix(NA, nrow = 5, ncol = 2))
colnames(data) <- c("Variables", "Value")
Xs <- combn(c("X1", "X2", "X3", "X4", "X5", "X6"), 4, simplify = FALSE)
for(j in 1:5)
{
data$Variables[j] <- Xs[j]
data$Value[j] <- sin(j)
}
```

That looks like this:

```
Variables Value
1 X1, X2, X3, X4 0.8414710
2 X1, X2, X3, X5 0.9092974
3 X1, X2, X3, X6 0.1411200
4 X1, X2, X4, X5 -0.7568025
5 X1, X2, X4, X6 -0.9589243
```

Where elements of column `Variables`

are lists:

```
typeof(data$Variables[1])
[1] "list"
```

Now, I have a second dataframe:

```
vals <- data.frame(matrix(NA, nrow = 6, ncol = 2))
colnames(vals) <- c("Variable", "Val")
for(j in 1:6)
{
vals$Variable[j] <- paste0("X", j, sep = "")
vals$Val[j] <- cos(j)
}
```

Here’s the output:

```
Variable Val
1 X1 0.5403023
2 X2 -0.4161468
3 X3 -0.9899925
4 X4 -0.6536436
5 X5 0.2836622
6 X6 0.9601703
```

**My question** is: I want to create another column of my `data`

dataframe in such a way that, i.e. for the first row of `data`

:

```
Variables Value
1 X1, X2, X3, X4 0.8414710
```

I apply a `sum`

(or mean, min, max, weighted mean) function based on values of `vals`

:

`X1, X2, X3, X4 -> 0.5403023 - 0.4161468 - 0.9899925 - 0.6536436 = -1.5194806`

And it results in a new column of `data`

:

```
Variables Value Sum
1 X1, X2, X3, X4 0.8414710 -1.5194806
```

Is this even possible?

## Solution

Yes, you can do:

```
data$Sum <- sapply(data$Variables, function(x) sum(vals$Val[match(x, vals$Variable)]))
data
#> Variables Value Sum
#> 1 X1, X2, X3, X4 0.8414710 -1.51948065
#> 2 X1, X2, X3, X5 0.9092974 -0.58217484
#> 3 X1, X2, X3, X6 0.1411200 0.09433326
#> 4 X1, X2, X4, X5 -0.7568025 -0.24582597
#> 5 X1, X2, X4, X6 -0.9589243 0.43068214
```

Answered By – Allan Cameron

Answer Checked By – David Goodson (BugsFixing Volunteer)