Tidyeval evaluate case_when - r

Question

Somewhat related to Tidy evaluation programming with dplyr::case_when and Making tidyeval function inside case_when, I want to create strings (using a shiny app) to be parsed later inside a case_when function. Here's an example:
library(tidyverse)
# simulated shiny inputs
new_column = sym("COL_NAME")
number_of_categories = 3
col1_text = "Big"
col1_min = 7.0
col1_max = 8.0
col2_text = "Medium"
col2_min = 5.0
col2_max = 6.9
col3_text = "Small"
col3_max = 4.9
col3_min = 4.0
columninput = sym("Sepal.Length")
DESIRED OUTPUT
iris %>%
mutate(new_column =
case_when(
!!columninput >= col1_min & !!columninput <= col1_max ~ col1_text,
!!columninput >= col2_min & !!columninput <= col2_max ~ col2_text,
!!columninput >= col3_min & !!columninput <= col3_max ~ col3_text
)
)
Because the only thing changing between functions is the index, I was thinking we can use the general pattern to create a string
# create single string
my_string <-function(i) {
paste0("!!", columninput, " >= col", i, "_min & ", "!!", columninput, " <= col", i, "_max ~ col", i, "_text")
}
Then repeat the string for the dynamic number of cases
mega_string <- map_chr(1:number_of_categories, ~ my_string(.x))
TODO:
This is the part I cant quite piece together: using those strings as the arguments within a case_when.
# evaluate somehow?
iris %>%
mutate(
new_column = case_when(
# tidyeval mega_string?
paste(mega_string, collapse = "," )
)
)
Is this even the right approach? How else would you go about solving this - any help high level or otherwise is greatly appreciated!

Answer 1

We could create an expression and evaluate
library(dplyr)
library(stringr)
iris %>%
mutate(new_column = eval(rlang::parse_expr(str_c('case_when(',
str_c(mega_string, collapse=","), ')'))))
# Sepal.Length Sepal.Width Petal.Length Petal.Width Species new_column
#1 5.1 3.5 1.4 0.2 setosa Medium
#2 4.9 3.0 1.4 0.2 setosa Small
#3 4.7 3.2 1.3 0.2 setosa Small
#4 4.6 3.1 1.5 0.2 setosa Small
#5 5.0 3.6 1.4 0.2 setosa Medium
#6 5.4 3.9 1.7 0.4 setosa Medium
#7 4.6 3.4 1.4 0.3 setosa Small
#8 5.0 3.4 1.5 0.2 setosa Medium
#9 4.4 2.9 1.4 0.2 setosa Small
#10 4.9 3.1 1.5 0.1 setosa Small
# ...
Or using parse_expr with !!!
library(purrr)
iris %>%
mutate(new_column = case_when(!!! map(mega_string, rlang::parse_expr)))
# Sepal.Length Sepal.Width Petal.Length Petal.Width Species new_column
#1 5.1 3.5 1.4 0.2 setosa Medium
#2 4.9 3.0 1.4 0.2 setosa Small
#3 4.7 3.2 1.3 0.2 setosa Small
#4 4.6 3.1 1.5 0.2 setosa Small
#5 5.0 3.6 1.4 0.2 setosa Medium
#6 5.4 3.9 1.7 0.4 setosa Medium
#7 4.6 3.4 1.4 0.3 setosa Small
#8 5.0 3.4 1.5 0.2 setosa Medium
#...

Answer 2

thx for the nice question and answer.
I'm using in same context (shiny).
I'd like to mention another approach that suits my needs better, and that I find more easy to read the logic off: rather than passing variables in the string to be evaluated you directly pass the values in the string coming from a tibble and str_glue_data
mega <- tribble(
~min, ~max, ~size,
7, 8, "Big",
5, 6.9, "Medium",
4.9, 4, "Small"
) %>%
str_glue_data("Sepal.Length >= {min} & Sepal.Length <= {max} ~ '{size}'")
iris %>%
mutate(new_column = case_when(!!! map(mega, rlang::parse_expr)))