[R] impute.transcan missing original variables

[m@icei m@iii@g oii i@iomed@sid@cu]

I’m trying to select only one dataframe, after performing an imputation with aregImpute and impute.transcan. However, I cannot get back a variable that was kept out of the imputation model. Can somebody tell me how to do it? If we illustrate this problem using the following reproducible example, how could I get the dataframe with all the variables that were not imputated, such as Species and id variables?
Best !


Data
data("iris") 
library(missForest)
library(tidyverse)
library(Hmisc)

# example
iris.missing <- iris %>% 
  group_by(Species) %>% 
  prodNA(noNA = 0.1) %>% 
  ungroup() %>% 
  mutate(id=row_number())

imputation_model <- aregImpute(~Sepal.Length+Sepal.Width+Petal.Width,
                               n.impute=3,
                               data=iris.missing,
                               pr=F, 
                               type='pmm')

data_imp <- impute.transcan(imputation_model,
                                  imputation=1,
                                  data=iris.missing,
                                  list.out=TRUE,
                                  pr=FALSE,
                                  check=FALSE)


datos_imp <- bind_rows(data_imp)


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