In WinVector/rquery: Relational Query Generator for Data Manipulation at Scale

library(wrapr)
library(rquery)

prob_calculation <- locum() %.>%
 extend(.,
  probability := exp(assessmentTotal * 0.237)) %.>%
 extend(.,
  probability := probability / sum(probability),
  partitionby = c('subjectID'))

print(prob_calculation)

top_rank <- locum() %.>%
 extend(.,
  row_number := row_number(),
  partitionby = c('subjectID'),
  orderby = c('probability', 'surveyCategory'),
  reverse = c('probability')) %.>%
 select_rows(.,
   row_number <= 1)

print(top_rank)

clean_up <- locum() %.>%
 rename_columns(.,
  c('diagnosis' = 'surveyCategory')) %.>%
 select_columns(., c(
   "subjectID", "diagnosis", "probability")) %.>%
 order_rows(.,
  c('subjectID'))

print(clean_up)

ops <- mk_td("d", c(
  "subjectID",
  "surveyCategory",
  "assessmentTotal",
  "irrelevantCol1",
  "irrelevantCol2")) %.>%
  prob_calculation %.>%
  top_rank %.>%
  clean_up

cat(format(ops))

d_local <- build_frame(
   "subjectID", "surveyCategory"     , "assessmentTotal", "irrelevantCol1", "irrelevantCol2" |
   1L         , "withdrawal behavior", 5                , "irrel1"        , "irrel2"         |
   1L         , "positive re-framing", 2                , "irrel1"        , "irrel2"         |
   2L         , "withdrawal behavior", 3                , "irrel1"        , "irrel2"         |
   2L         , "positive re-framing", 4                , "irrel1"        , "irrel2"         )

d_local %.>% ops