Examples/LogisticExample/Logistic2.md

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

Logistic2.Rmd

library(wrapr)
library(rquery)

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

print(prob_calculation)

## locum() %.>%
##    extend(., `:=`(probability, exp(assessmentTotal * 0.237))) %.>%
##    extend(., `:=`(probability, probability/sum(probability)), partitionby = c("subjectID"))

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)

## locum() %.>%
##    extend(., `:=`(row_number, row_number()), partitionby = c("subjectID"), 
##      orderby = c("probability", "surveyCategory"), reverse = c("probability")) %.>%
##    select_rows(., row_number <= 1)

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

print(clean_up)

## locum() %.>%
##    rename_columns(., c(diagnosis = "surveyCategory")) %.>%
##    select_columns(., c("subjectID", "diagnosis", "probability")) %.>%
##    order_rows(., c("subjectID"))

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

cat(format(ops))

## mk_td("d", c(
##   "subjectID",
##   "surveyCategory",
##   "assessmentTotal",
##   "irrelevantCol1",
##   "irrelevantCol2")) %.>%
##  extend(.,
##   probability := exp(assessmentTotal * 0.237)) %.>%
##  extend(.,
##   probability := probability / sum(probability),
##   partitionby = c('subjectID'),
##   orderby = c(),
##   reverse = c()) %.>%
##  extend(.,
##   row_number := row_number(),
##   partitionby = c('subjectID'),
##   orderby = c('probability', 'surveyCategory'),
##   reverse = c('probability')) %.>%
##  select_rows(.,
##    row_number <= 1) %.>%
##  rename_columns(.,
##   c('diagnosis' = 'surveyCategory')) %.>%
##  select_columns(., c(
##    "subjectID", "diagnosis", "probability")) %.>%
##  order_rows(.,
##   c('subjectID'),
##   reverse = c(),
##   limit = NULL)

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

##    subjectID           diagnosis probability
## 1:         1 withdrawal behavior   0.6706221
## 2:         2 positive re-framing   0.5589742

WinVector/rquery documentation built on Aug. 24, 2023, 11:12 a.m.