Iteratively create global environment objects from tibble-CodePudding

I'm trying to make objects directly from information listed in a tibble that can be called on by later functions/tibbles in my environment. I can make the objects manually but I'm working to do this iteratively.

library(tidyverse)    
##determine mean from 2x OD Negatives in experimental plates, then save summary for use in appending table

ELISA_negatives = "my_file.csv"  
neg_tibble <- as_tibble(read_csv(ELISA_negatives, col_names = TRUE))  %>%
  group_by(Species_ab, Antibody, Protein) %>% 
  filter(str_detect(Animal_ID, "2x.*")) %>%
  summarize(ave_neg_U_mL = mean(U_mL, na.rm = TRUE), n=sum(!is.na(U_mL))) 

neg_tibble
# A tibble: 4 x 5
# Groups:   Species_ab, Antibody [2]
  Species_ab Antibody Protein ave_neg_U_mL     n
  <chr>      <chr>    <chr>          <dbl> <int>
1 Mouse      IgG      GP             28.2      6
2 Mouse      IgG      NP             45.9      6
3 Rat        IgG      GP              5.24     4
4 Rat        IgG      NP              1.41     1

I can write the object manually based off the above tibble:

Mouse_IgG_GP_cutoff <- as.numeric(neg_tibble[1,4])
Mouse_IgG_GP_cutoff
[1] 28.20336

In my attempt to do this iteratively, I can make a new tibble neg_tibble_string with the information I need. All I would need to do now is make a global object from the Name in the first column Test_Name, and assign it to the numeric value in the second column ave_neg_U_mL (which is where I'm getting stuck).

 neg_tibble_string <- neg_tibble %>%
      select(Species_ab:Protein) %>%
      unite(col='Test_Name', c('Species_ab', 'Antibody', 'Protein'), sep = "_") %>%
      mutate(Test_Name = str_c(Test_Name, "_cutoff")) %>%
      bind_cols(neg_tibble[4])
    
    neg_tibble_string
        # A tibble: 4 x 2
      Test_Name           ave_neg_U_mL
      <chr>                      <dbl>
    1 Mouse_IgG_GP_cutoff        28.2 
    2 Mouse_IgG_NP_cutoff        45.9 
    3 Rat_IgG_GP_cutoff           5.24
    4 Rat_IgG_NP_cutoff           1.41

I feel like there has to be a way to do this to get this from the above tibble neg_tibble_string, and make this for all four of the rows. I've tried a variant of this and this, but can't get anywhere.

> list_df <- mget(ls(pattern = "neg_tibble_string"))
> list_output <- map(list_df, ~neg_tibble_string$ave_neg_U_mL)
Warning message:
Unknown or uninitialised column: `ave_neg_U_mL`. 
> list_output
$neg_tibble_string
NULL

As always, any insight is appreciated! I'm making progress on my R journey but I know I am missing large gaps in knowledge.

CodePudding user response：

As we already returned the object value in a list, we need only to specify the lambda function i.e. .x returns the value of the list element which is a tibble and extract the column

library(purrr)
list_output <- map(list_df,  ~.x$ave_neg_U_ml)

If the intention is to create global objects, deframe, convert to a list and then use list2env

library(tibble)
list2env(as.list(deframe(neg_tibble_string)), .GlobalEnv)