Apply R function to multiple objects and rewrite object - r

Question

I'm trying to do the following:
define a function which creates an additional column based on existing columns in a data frame
apply said function to multiple objects (data frames), rewriting the original data frame
For example, say the function is to divide the Petal.Length by Petal.Width in iris.
divvy <- function(mydataframe){mydataframe$divvy <- mydataframe$Petal.Length/mydataframe$Petal.Width}
This part is easy.
Now imagine I have three (or three thousand) iris dataframes:
iris2 <- iris
iris4 <- iris
iris5 <- iris
What I am trying to avoid is this:
iris <- divvy(iris)
iris2 <- divvy(iris2)
iris4 <- divvy(iris4)
iris5 <- divvy(iris5)
times infinity for the number of iris data frames that I have
... with something along the lines of
lapply(c(iris,iris2,iris4,iris4), function(x) divvy(x))
And end up with iris, iris2, iris4, and iris5 having the new divvy column. How do I do this?
Please note: I do NOT want to create a meta-object that has all of the irises within it.

Answer 1

We could use data.table to do this:
library(data.table)
divvy <- function(x){x[,divvy := Petal.Length/Petal.Width]}
iris2 <- data.table(iris)
iris4 <- data.table(iris)
iris5 <- data.table(iris)
test <- lapply(list(iris2,iris4,iris5), function(x) divvy(x))
Where test looks like this (just showing the first 2 elements of the list):
> test
[[1]]
Sepal.Length Sepal.Width Petal.Length Petal.Width Species divvy
1: 5.1 3.5 1.4 0.2 setosa 7.000000
2: 4.9 3.0 1.4 0.2 setosa 7.000000
3: 4.7 3.2 1.3 0.2 setosa 6.500000
4: 4.6 3.1 1.5 0.2 setosa 7.500000
5: 5.0 3.6 1.4 0.2 setosa 7.000000
---
146: 6.7 3.0 5.2 2.3 virginica 2.260870
147: 6.3 2.5 5.0 1.9 virginica 2.631579
148: 6.5 3.0 5.2 2.0 virginica 2.600000
149: 6.2 3.4 5.4 2.3 virginica 2.347826
150: 5.9 3.0 5.1 1.8 virginica 2.833333
[[2]]
Sepal.Length Sepal.Width Petal.Length Petal.Width Species divvy
1: 5.1 3.5 1.4 0.2 setosa 7.000000
2: 4.9 3.0 1.4 0.2 setosa 7.000000
3: 4.7 3.2 1.3 0.2 setosa 6.500000
4: 4.6 3.1 1.5 0.2 setosa 7.500000
5: 5.0 3.6 1.4 0.2 setosa 7.000000
---
146: 6.7 3.0 5.2 2.3 virginica 2.260870
147: 6.3 2.5 5.0 1.9 virginica 2.631579
148: 6.5 3.0 5.2 2.0 virginica 2.600000
149: 6.2 3.4 5.4 2.3 virginica 2.347826
150: 5.9 3.0 5.1 1.8 virginica 2.833333
EDIT*** In response to OP updating questions specs:
You could try this:
for(i in c("iris2", "iris4", "iris5")){
x <- divvy(get(i))
assign(paste0(i,"divvied"), x)
}
Although i'd recommend against assign, especially for a lot of objects. You could extract the elements from the test list which i made in the first half of the answer, you'd still get the same answer, just a little cleaner and less clutter.
What the code does is pulls in the iris data tables as a string, and then reads them using get. This is passed to your divvy function, creating a data.table x. I then use assign to create the data.table with the suffix divvied.