rqdatatable
re-maps a number of symbols for data.table
translation (for rquery
/SQL
re-mappings, please see here). For instance, please take note of the n()
and rank()
functions in the following code example.
library("rqdatatable")
library("wrapr")
<- build_frame(
dL "subjectID", "surveyCategory" , "assessmentTotal"|
1 , "withdrawal behavior", 5 |
1 , "positive re-framing", 2 |
2 , "withdrawal behavior", 3 |
2 , "positive re-framing", 4 |
2 , "other" , 0 )
<- 0.237
scale <- local_td(dL) %.>%
rquery_pipeline extend_nse(.,
probability :=
exp(assessmentTotal * scale)/
sum(exp(assessmentTotal * scale)),
count := n(),
rank := rank(),
orderby = c("assessmentTotal", "surveyCategory"),
reverse = c("assessmentTotal"),
partitionby = 'subjectID') %.>%
orderby(., c("subjectID", "probability"))
<- ex_data_table(rquery_pipeline, tables = list(dL = dL))
res ::kable(res) knitr
subjectID | surveyCategory | assessmentTotal | probability | count | rank |
---|---|---|---|---|---|
1 | positive re-framing | 2 | 0.3293779 | 2 | 2 |
1 | withdrawal behavior | 5 | 0.6706221 | 2 | 1 |
2 | other | 0 | 0.1780446 | 3 | 3 |
2 | withdrawal behavior | 3 | 0.3625035 | 3 | 2 |
2 | positive re-framing | 4 | 0.4594519 | 3 | 1 |
The common re-mappings are can be found in the package-private variable rqdatatable:::data_table_extend_fns
.
str(rqdatatable:::data_table_extend_fns)
## List of 6
## $ ngroup :List of 2
## ..$ data.table_version: chr ".GRP"
## ..$ need_one_col : logi TRUE
## $ rank :List of 2
## ..$ data.table_version: chr "cumsum(rqdatatable_temp_one_col)"
## ..$ need_one_col : logi TRUE
## $ row_number:List of 2
## ..$ data.table_version: chr "cumsum(rqdatatable_temp_one_col)"
## ..$ need_one_col : logi TRUE
## $ n :List of 2
## ..$ data.table_version: chr "sum(rqdatatable_temp_one_col)"
## ..$ need_one_col : logi TRUE
## $ random :List of 2
## ..$ data.table_version: chr "runif(.N)"
## ..$ need_one_col : logi FALSE
## $ rand :List of 2
## ..$ data.table_version: chr "runif(.N)"
## ..$ need_one_col : logi FALSE
The column rqdatatable_temp_one_col
is introduced (and removed) from intermediate data frames as needed.
These mappings help allow the same operator pipeline to be used in R
and in a database. For the database mappings please see here.