Data frame typecasting entire column to character from numeric

Question

Suppose I have a data.frame that's completely numeric. If I make one entry of the first column a character (for example), then the entire first column will become character.

Question: How do I reverse this. That is, how do I make it such that any character objects inside the data.frame that are "obviously" numeric objects are forced to be numeric?

MWE:

test <- data.frame(matrix(rnorm(50),10))
is(test[3,1])
test[1,1] <- "TEST"
is(test[3,1])
print(test)

So my goal here would be to go FROM the way that test is now, TO a state of affairs where test[2:10] is numeric. So I guess I'm asking for a function that does this over an entire data.frame.

Answer 1

Short answer is you cannot.
As was mentioned in the comments, in a data frame, all elements of a column must have the same mode.

If you would like to specifically find the values that are "number like" you can use the following (where vec here would be, say, a data frame column)

  vec[!is.na(as.numeric((vec)))]

You can then convert these, but unfortunately you cannot put the converted values back into the same column. As as you do, they will be coerced back to character

---

As for a function that can convert the whole dataframe to numeric (realizing that isolating specific entries as exceptions is not possible), you can use sapply

  sapply(dataFrameName, as.numeric)

Answer 2

You are allowed to have vectors of type list in a data.frame, and the list can contain any type of object except functions as long as it is of the same length as the other columns in the data.frame, e.g.:

mydataframe <- data.frame(numbers=1:3)
mydataframe$mylist <- list(1, 'plum', 5)
mydataframe
#  numbers mylist
#1       1      1
#2       2   plum
#3       3      5
sapply(mydataframe, typeof)
#  numbers    mylist 
#"integer"    "list" 
sapply(mydataframe$mylist, typeof)
#[1] "double"    "character" "double"