Clean column data in R

Question

I am stuck with a small problem while trying to clean my data. I have a property data set which has listing of property size as character. Most of the data for the size column is just numeric but in text format. If I convert them to numeric data, I will loose many data due to coercion. There are particular data where it is like (20*40)....which I am unable to convert. As this data is getting coerced to NA while conversion. Any guidance on how to handle this kind of issue?

Answer 1

Maybe this function can be of help.

evalCell <- function(x){
  f <- function(x) eval(parse(text = x))
  sapply(x, f)
}

x <- c("(20*40)", 123, "1 + 2*3", "(1 + 2)*3")
evalCell(x)
#  (20*40)       123   1 + 2*3 (1 + 2)*3 
#      800       123         7         9 

If the return vector's names are not wanted, have the function return unname(sapply(etc)) .

Answer 2

We can use map with parse_expr

library(purrr)
map_dbl(x, ~ eval(rlang::parse_expr(.x)))
#[1] 800 123   7   9

data

x <- c("(20*40)", 123, "1 + 2*3", "(1 + 2)*3")

Answer 3

You can try

sapply(yourColumn, function(X) eval(parse(text=X)))

Example:

> sapply(c("5+5", "22", "10*5"), function(X) eval(parse(text=X)) )
 5+5   22 10*5 
  10   22   50