Get errors from pmap_safely_output for a specified variable.

Allows for errors to be easily analyzed.

get_errors_one_var(pmap_safely_output, var, specific = FALSE)

get_errors(pmap_safely_output, specific = FALSE)

Arguments

pmap_safely_output	The data frame outputted by the function pmap_safely_output. More specifically, must have an error and a result column (which is a list containing named lists or vectors).
var	The input variable to analyzed errors based on.
specific	Do you just want a summary or specific errors?

Examples

# a function to apply
calculate_if_positive <- function(a, b){
    if(a < 0 & b < 0) {stop("Both numbers are negative.")}
    else if(a < 0) {stop("Just the first number is negative")}
    else if(b < 0) {stop("Just the second number is negative")}

    list(add = a + b,
         subtract = a - b,
         multiply = a * b,
         divide = a / b)
}
# data frame to apply the function to by row
numbers <- data.frame(a = c(-1, 0, 1, 2),
                      b = c(2, 1, 0, -1),
                      irrelevant = c("minneapolis", "st_paul", "minneapolis", "st_paul"))

# apply and get errors
output <- pmap_safely(numbers, calculate_if_positive)
#> Note that the function does not use the following variables: irrelevant

get_errors_one_var(output, var = "a")
#> # A tibble: 4 x 5
#>   variable value n_errors count error_rate
#>   <chr>    <chr>    <int> <int>      <dbl>
#> 1 a        -1           1     1          1
#> 2 a        2            1     1          1
#> 3 a        0            0     1          0
#> 4 a        1            0     1          0
get_errors_one_var(output, var = "a", specific = TRUE)
#> # A tibble: 4 x 6
#>   variable value error                                  n count  rate
#>   <chr>    <chr> <chr>                              <int> <int> <dbl>
#> 1 a        -1    Just the first number is negative      1     1     1
#> 2 a        0     <NA>                                   1     1     1
#> 3 a        1     <NA>                                   1     1     1
#> 4 a        2     Just the second number is negative     1     1     1
get_errors(output)
#> # A tibble: 10 x 5
#>    variable   value       n_errors count error_rate
#>    <chr>      <chr>          <int> <int>      <dbl>
#>  1 a          -1                 1     1        1  
#>  2 a          2                  1     1        1  
#>  3 a          0                  0     1        0  
#>  4 a          1                  0     1        0  
#>  5 b          -1                 1     1        1  
#>  6 b          2                  1     1        1  
#>  7 b          0                  0     1        0  
#>  8 b          1                  0     1        0  
#>  9 irrelevant minneapolis        1     2        0.5
#> 10 irrelevant st_paul            1     2        0.5
get_errors(output, specific = TRUE)
#> # A tibble: 12 x 6
#>    variable   value       error                                  n count  rate
#>    <chr>      <chr>       <chr>                              <int> <int> <dbl>
#>  1 a          -1          Just the first number is negative      1     1   1  
#>  2 a          0           <NA>                                   1     1   1  
#>  3 a          1           <NA>                                   1     1   1  
#>  4 a          2           Just the second number is negative     1     1   1  
#>  5 b          -1          Just the second number is negative     1     1   1  
#>  6 b          0           <NA>                                   1     1   1  
#>  7 b          1           <NA>                                   1     1   1  
#>  8 b          2           Just the first number is negative      1     1   1  
#>  9 irrelevant minneapolis <NA>                                   1     2   0.5
#> 10 irrelevant minneapolis Just the first number is negative      1     2   0.5
#> 11 irrelevant st_paul     <NA>                                   1     2   0.5
#> 12 irrelevant st_paul     Just the second number is negative     1     2   0.5