Summary
In light of the various changes to the detail of the question, here are two solutions to the problem that can be phrased as:
Given
col_names <- c("Obj1$Var1", "Obj2$Var2")
how to return a data frame that would be the equivalent of
cbind(Obj1$Var1, Obj2$Var2)
?
The simplest solution would be
as.data.frame(sapply(col_names, function(x) eval(parse(text = x))))
but that uses parse() which shouldn't be relied on for things like this. An alternative, but somewhat longer solution is
get4 <- function(x, ...) {
fun <- function(text, ...) {
obj <- get(text[1], ...)
obj[[text[2]]]
}
sx <- strsplit(x, "\\$")
lx <- lapply(sx, fun, ...)
out <- do.call(cbind.data.frame, lx)
names(out) <- x
out
}
get4(col_names)
The second solution has advantages, despite being somewhat longer, in that it
- will work for data of different types as it works with a list and converts that to a data frame. The
eval(parse(text = ....)) solution simplifies to an array first. Using lapply() instead of sapply() is an option that gets round this, but needs extra work to change the names of the resulting object.
- uses common function
get() to grab the object with stated name, and basic subsetting syntax.
- doesn't use
parse ;-)
Original Answer
The original Answer with greater detail continues below:
eval(parse(....)) will work
data1 <- data.frame(column1 = 1:10, column2 = letters[1:10])
txt <- "data1$column2"
> eval(parse(text = txt))
[1] a b c d e f g h i j
Levels: a b c d e f g h i j
As @texb mentions, this can trivially be extended to handle a vector of strings via (modified to return a data frame)
col_names <- c("iris$Sepal.Length", "iris$Sepal.Width")
as.data.frame(sapply(col_names, function(x) eval(parse(text = x))))
It may be more acceptable to use get but you'll have to do a bit of precessing, something along the lines of
get2 <- function(x, ...) {
sx <- strsplit(x, "\\$")[[1]]
obj <- get(sx[1], ...)
obj[[sx[2]]]
}
> get2(txt)
[1] a b c d e f g h i j
Levels: a b c d e f g h i j
iris example from OP's question
As @texb mentions, the eval(parse(text = ....)) version can trivially be extended to handle a vector of strings via (modified to return a data frame)
col_names <- c("iris$Sepal.Length", "iris$Sepal.Width")
as.data.frame(sapply(col_names, function(x) eval(parse(text = x))))
iris$Sepal.Length iris$Sepal.Width
1 5.1 3.5
2 4.9 3.0
3 4.7 3.2
4 4.6 3.1
5 5.0 3.6
6 5.4 3.9
....
Modifiying get2() is also possible to allow it to work on a vector of strings such as col_names. Here I loop over the first elements of sx to extract the object string (checking that there is only one unique object name), then I get that object and then subset it using the variable names (extracted using sapply(sx, `[`, 2))
get3 <- function(x, ...) {
sx <- strsplit(x, "\\$")
obj <- unique(sapply(sx, `[`, 1))
stopifnot(length(obj) == 1L)
obj <- get(obj, ...)
obj[sapply(sx, `[`, 2)]
}
col_names <- c("iris$Sepal.Length", "iris$Sepal.Width")
head(get3(col_names))
> head(get3(col_names))
Sepal.Length Sepal.Width
1 5.1 3.5
2 4.9 3.0
3 4.7 3.2
4 4.6 3.1
5 5.0 3.6
6 5.4 3.9
If you have multiple objects referenced in col_names then you will need a different solution, along the lines of
get4 <- function(x, ...) {
fun <- function(text, ...) {
obj <- get(text[1], ...)
obj[[text[2]]]
}
sx <- strsplit(x, "\\$")
lx <- lapply(sx, fun, ...)
out <- do.call(cbind.data.frame, lx)
names(out) <- x
out
}
col_names2 <- c("iris$Sepal.Length", "iris2$Sepal.Length")
get4(col_names2)
> head(get4(col_names2))
iris$Sepal.Length iris2$Sepal.Length
1 5.1 5.1
2 4.9 4.9
3 4.7 4.7
4 4.6 4.6
5 5.0 5.0
6 5.4 5.4
