Nothing
We can work an example similar to the rquery
example using a data.table
back-end.
library("rqdatatable")
# data example dL <- wrapr::build_frame( "subjectID", "surveyCategory" , "assessmentTotal" | 1 , "withdrawal behavior", 5 | 1 , "positive re-framing", 2 | 2 , "withdrawal behavior", 3 | 2 , "positive re-framing", 4 )
scale <- 0.237 # example rquery pipeline rquery_pipeline <- local_td(dL) %.>% extend_nse(., one = 1) %.>% extend_nse(., probability = exp(assessmentTotal * scale)/ sum(exp(assessmentTotal * scale)), count = sum(one), partitionby = 'subjectID') %.>% extend_nse(., rank = cumsum(one), partitionby = 'subjectID', orderby = c('probability', 'surveyCategory')) %.>% extend_nse(., isdiagnosis = rank == count, diagnosis = surveyCategory) %.>% select_rows_nse(., isdiagnosis == TRUE) %.>% select_columns(., c('subjectID', 'diagnosis', 'probability')) %.>% orderby(., 'subjectID')
Show expanded form of query tree.
cat(format(rquery_pipeline))
Execute the calculation.
ex_data_table(rquery_pipeline)
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.