CODEWITHSUNDEEP
rif-statementdplyrgroup-bytidyverse
Garn_R
Garn_R

Reputation: 77

Conditional group_by with example

I have a task to identify unique trial (1,2,3,...) in a dataset. Here is an example:

"source","ID","cultivar","design"
"PDMR_vol_12","CF027","Ambassador","RCBD"
"PDMR_vol_12","CF027","Ambassador","RCBD"
"PDMR_vol_12","CF027","Ambassador","RCBD"
"PDMR_vol_12","CF027","Ambassador","RCBD"
"PDMR_vol_7","CF026","ASG2000","RCBD"
"PDMR_vol_7","CF026","ASG2000","RCBD"
"PDMR_vol_7","CF026","ASG2000","RCBD"
"PDMR_vol_7","CF026","P26R61","RCBD"
"PDMR_vol_7","CF026","P26R61","RCBD"
"PDMR_vol_7","CF026","P26R61","RCBD"
"PDMR_vol_4","CF011","Roane","SP"
"PDMR_vol_4","CF011","Roane","SP"
"PDMR_vol_4","CF011","Tomahawk","SP"
"PDMR_vol_4","CF011","Tomahawk","SP"
"PDMR_vol_4","CF011","Everest","SP"
"PDMR_vol_4","CF011","Everest","SP"

The conditional columns are:

unique_trials_RCBD<- ("source","ID","cultivar","design")

unique_trials_SP<-unique_trials_RCBD[-3]

Using a conditional group_by based on a few columns, we almost get the correct result, with the exception that it does not correctly identify (PDMR_vol_7 CF026) as two trials.

doAGroupBy <- function(data, some_condition) {

 if (some_condition == TRUE) {

   group_args <- unique_trials_RCBD

  } else {

   group_args <- unique_trials_SP

 }

  data %>%
    group_by_at(vars(group_args))
}


 a<-doAGroupBy(data, FALSE) %>% 
   mutate(trial_number=cur_group_id())

In total, there should be 4 trials there. Any ideas on how to improve this code? thanks

Upvotes: 0

Views: 62

Answers (1)

Vin&#237;cius F&#233;lix
Vin&#237;cius F&#233;lix

Reputation: 8811

If I understood the problem correctly, this should work:

Data

df <-
tibble::tribble(~`source`, ~`ID`,~`cultivar`,~`design`,
  "PDMR_vol_12", "CF027", "Ambassador",  "RCBD",
  "PDMR_vol_12", "CF027", "Ambassador",  "RCBD",
  "PDMR_vol_12", "CF027", "Ambassador",  "RCBD",
  "PDMR_vol_12", "CF027", "Ambassador",  "RCBD",
   "PDMR_vol_7", "CF026",    "ASG2000",  "RCBD",
   "PDMR_vol_7", "CF026",    "ASG2000",  "RCBD",
   "PDMR_vol_7", "CF026",    "ASG2000",  "RCBD",
   "PDMR_vol_7", "CF026",     "P26R61",  "RCBD",
   "PDMR_vol_7", "CF026",     "P26R61",  "RCBD",
   "PDMR_vol_7", "CF026",     "P26R61",  "RCBD",
   "PDMR_vol_4", "CF011",      "Roane",    "SP",
   "PDMR_vol_4", "CF011",      "Roane",    "SP",
   "PDMR_vol_4", "CF011",   "Tomahawk",    "SP",
   "PDMR_vol_4", "CF011",   "Tomahawk",    "SP",
   "PDMR_vol_4", "CF011",    "Everest",    "SP",
   "PDMR_vol_4", "CF011",    "Everest",    "SP"
  )

Code

df %>% 
  # Creating auxiliar variable, consdering cultivar only for a RCBD design
  mutate(aux = if_else(design == "RCBD", cultivar,NA_character_)) %>%
  # Groupinp by source,ID,design and aux
  group_by(source,ID,design,aux) %>% 
  # Creating index grouped by variables above
  mutate(trial = group_indices())

Result

# A tibble: 16 x 6
# Groups:   source, ID, design, aux [4]
   source      ID    cultivar   design aux        trial
   <chr>       <chr> <chr>      <chr>  <chr>      <int>
 1 PDMR_vol_12 CF027 Ambassador RCBD   Ambassador     1
 2 PDMR_vol_12 CF027 Ambassador RCBD   Ambassador     1
 3 PDMR_vol_12 CF027 Ambassador RCBD   Ambassador     1
 4 PDMR_vol_12 CF027 Ambassador RCBD   Ambassador     1
 5 PDMR_vol_7  CF026 ASG2000    RCBD   ASG2000        3
 6 PDMR_vol_7  CF026 ASG2000    RCBD   ASG2000        3
 7 PDMR_vol_7  CF026 ASG2000    RCBD   ASG2000        3
 8 PDMR_vol_7  CF026 P26R61     RCBD   P26R61         4
 9 PDMR_vol_7  CF026 P26R61     RCBD   P26R61         4
10 PDMR_vol_7  CF026 P26R61     RCBD   P26R61         4
11 PDMR_vol_4  CF011 Roane      SP     NA             2
12 PDMR_vol_4  CF011 Roane      SP     NA             2
13 PDMR_vol_4  CF011 Tomahawk   SP     NA             2
14 PDMR_vol_4  CF011 Tomahawk   SP     NA             2
15 PDMR_vol_4  CF011 Everest    SP     NA             2
16 PDMR_vol_4  CF011 Everest    SP     NA             2

Upvotes: 1

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