Creation of conditional Random IDs for students

[kuttan98]

Hi,
I have a data with student names. I want to create unique IDs for them with condition. The ID should have 3 capital alphabets (A,B,C, etc.) with 3 numbers. Hence the ID will have 6 characters like say, FGY675 as given in the data frame "data_id" below.
Is this possible to create?

library(tidyverse)
data<-tibble::tribble(
  ~student_name, ~teacher,
         "Ravi",   "Jaya",
       "Gandhi",   "Jaya",
        "Nehru",   "Jaya",
         "Giri",   "Jaya",
        "Nivin",   "Jaya",
       "Nithin",  "Shiva",
       "Mithun",  "Shiva",
      "Vinayak",  "Shiva",
      "Girirsh",  "Shiva",
       "Akshay",  "Shiva"
  )

data_id<-tibble::tribble(
  ~student_name, ~teacher, ~random_id,
         "Ravi",   "Jaya",   "BGH142",
       "Gandhi",   "Jaya",   "GHT675",
        "Nehru",   "Jaya",   "JUS098",
         "Giri",   "Jaya",   "NJS767",
        "Nivin",   "Jaya",   "POI999",
       "Nithin",  "Shiva",   "MIU567",
       "Mithun",  "Shiva",   "NUY144",
      "Vinayak",  "Shiva",   "MRE235",
      "Girirsh",  "Shiva",   "MMS258",
       "Akshay",  "Shiva",   "MAE257"
  )
Created on 2022-08-10 by the reprex package (v2.0.1)

[JackDavison]

This is a way of doing it. Get all combinations of three letters and three numbers, combine them, and then randomly sample from that list without replacement.

set.seed(123)

library(tidyverse, warn.conflicts = F)

grid <- crossing(
  a = LETTERS,
  b = LETTERS,
  c = LETTERS,
  d = 0:9,
  e = 0:9,
  f = 0:9
) %>%
  mutate(id = str_c(a, b, c, d, e, f, sep = ""))

data <- tibble::tribble(
  ~student_name, ~teacher,
  "Ravi",   "Jaya",
  "Gandhi",   "Jaya",
  "Nehru",   "Jaya",
  "Giri",   "Jaya",
  "Nivin",   "Jaya",
  "Nithin",  "Shiva",
  "Mithun",  "Shiva",
  "Vinayak",  "Shiva",
  "Girirsh",  "Shiva",
  "Akshay",  "Shiva"
)

mutate(data, id = sample(
  grid$id,
  size = length(data$student_name),
  replace = F
))
#> # A tibble: 10 × 3
#>    student_name teacher id    
#>    <chr>        <chr>   <chr> 
#>  1 Ravi         Jaya    RIX277
#>  2 Gandhi       Jaya    SVC969
#>  3 Nehru        Jaya    XPQ957
#>  4 Giri         Jaya    ISP674
#>  5 Nivin        Jaya    YSW436
#>  6 Nithin       Shiva   APM857
#>  7 Mithun       Shiva   NHC029
#>  8 Vinayak      Shiva   ULI691
#>  9 Girirsh      Shiva   HNH584
#> 10 Akshay       Shiva   ECK694

^{Created on 2022-08-10 by the reprex package (v2.0.1)}

[kuttan98]

Wow! This is too good. But may I know two things:

1. Would there be any IDs that will be duplicate?
2. What exactly does the function crossing do?
3. And what is the sample function used in mutate?

[JackDavison]

To answer your questions out of order: sample() samples from a vector, randomly. So if you give it the numbers one to ten, it'll grab you a random number.

You can set "replace" to be TRUE or FALSE. If replace is FALSE, it will never return a duplicate value.

See examples below:

# with replacement (get duplicates)
sample(1:10, size = 10, replace = T)
#>  [1]  1  8  2  2  4  6  6 10  1  2

# without replacement (no duplicates)
sample(1:10, size = 10, replace = F)
#>  [1]  2  3 10  1  9  8  5  4  6  7

crossing() gets all combinations of vectors and returns a dataframe. Consider this example:

tidyr::crossing(
  animal = c("dog", "cat"),
  colour = c("brown", "black", "golden"),
  attitude = c("friendly", "aloof", "angry", "independent")
)
#> # A tibble: 24 × 3
#>    animal colour attitude   
#>    <chr>  <chr>  <chr>      
#>  1 cat    black  aloof      
#>  2 cat    black  angry      
#>  3 cat    black  friendly   
#>  4 cat    black  independent
#>  5 cat    brown  aloof      
#>  6 cat    brown  angry      
#>  7 cat    brown  friendly   
#>  8 cat    brown  independent
#>  9 cat    golden aloof      
#> 10 cat    golden angry      
#> # … with 14 more rows

So what my code does is find all combinations between 3 vectors of all letters and 3 vectors of all single-digit numbers, combines the columns into one vector, and then samples from that vector randomly without replacement.

[kuttan98]

Thanks for the explanation.. It was of great help.