Calculate formula from string saved in variable-CodePudding

Sorry, but I'm struggling with a quite simple problem: A formula/an expression like 1.28*10^2 is saved as a character in a data frame. Now I want to convert this string into a numeric value - this should result in "128", but it does not.

library(dplyr)

mydata <- data.frame(
  formula = c("5.89*10^3", "1.28*10^2", "4.11*10^5")
)

mydata <- mydata %>% 
  dplyr::mutate(eval = eval(parse(text = formula)))

The variable "eval" should contain the values 5890, 128 and 411000 in the end.

Can anyone help where my mistake is? Thank you!

CodePudding user response：

Yet another solution, based on rlang::parse_expr:

library(dplyr)
library(rlang)

mydata <- data.frame(
  formula = c("5.89*10^3", "1.28*10^2", "4.11*10^5")
)

mydata %>% 
  rowwise %>% 
  mutate(eval = eval(parse_expr(formula)))

#> # A tibble: 3 × 2
#> # Rowwise: 
#>   formula     eval
#>   <chr>      <dbl>
#> 1 5.89*10^3   5890
#> 2 1.28*10^2    128
#> 3 4.11*10^5 411000

CodePudding user response：

By default eval(parse()) is not vectorized. Here are a couple of workarounds,

sapply(mydata$formula, function(i)eval(parse(text = i)))
#5.89*10^3 1.28*10^2 4.11*10^5 
#     5890       128    411000 

f1 <- function(x)eval(parse(text = x))
f2 <- Vectorize(f1)
mydata %>% 
  dplyr::mutate(eval = f2(formula))

  formula   eval
#1 5.89*10^3   5890
#2 1.28*10^2    128
#3 4.11*10^5 411000

CodePudding user response：

I dont think we must use rowwise. A simple lapply/purrr::map will do the job

library(purrr)
library(dplyr)
library(rlang)

mydata %>%
    mutate(result = map_dbl(formula, ~eval(parse_expr(.x))))

We can also use base R with lapply:

mydata$formula[]<-lapply(mydata$formula, \(x) eval(parse(text=x)))

  formula
1    5890
2     128
3  411000

CodePudding user response：

1) Perform one conversion at a time:

library(dplyr)

mydata %>% 
  rowwise %>%
  mutate(eval = eval(parse(text = formula))) %>%
  ungroup
## # A tibble: 3 x 2
##   formula     eval
##   <chr>      <dbl>
## 1 5.89*10^3   5890
## 2 1.28*10^2    128
3 4.11*10^5 411000

2) or use sapply:

mydata %>%
  mutate(eval = sapply(parse(text = formula), eval))

3) If all the formulas are of the form shown in the question then we can convert them to e notation and use as.numeric:

mydata %>%
  mutate(eval = as.numeric(sub('*10^', 'e', formula, fixed = TRUE)))

4) Without dplyr (2) and (3) could be done like this:

transform(mydata, eval = sapply(parse(text = formula), eval))

transform(mydata, eval = as.numeric(sub('*10^', 'e', formula, fixed = TRUE)))