Examples/yaml/yaml.md

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

yaml

This is an example of R reading a YAML representation of a Python data_algebra pipeline. The example being read comes from here.

library(yaml)
library(wrapr)
library(rquery)
library(rqdatatable)

rep <- yaml.load_file("pipeline_yaml.txt")
ops <- convert_yaml_to_pipeline(rep)
cat(format(ops))

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

cat(to_sql(ops, rquery_default_db_info()))

## SELECT * FROM (
##  SELECT
##   "subjectID" AS "subjectID",
##   "surveyCategory" AS "diagnosis",
##   "probability" AS "probability"
##  FROM (
##   SELECT
##    "subjectID",
##    "surveyCategory",
##    "probability"
##   FROM (
##    SELECT * FROM (
##     SELECT
##      "subjectID",
##      "surveyCategory",
##      "probability",
##      row_number ( ) OVER (  PARTITION BY "subjectID" ORDER BY "probability" DESC, "surveyCategory" ) AS "row_number"
##     FROM (
##      SELECT
##       "subjectID",
##       "surveyCategory",
##       "probability" / "total"  AS "probability"
##      FROM (
##       SELECT
##        "subjectID",
##        "surveyCategory",
##        "probability",
##        sum ( "probability" ) OVER (  PARTITION BY "subjectID" ) AS "total"
##       FROM (
##        SELECT
##         "subjectID",
##         "surveyCategory",
##         exp ( "assessmentTotal" * 0.237 )  AS "probability"
##        FROM (
##         SELECT
##          "subjectID",
##          "surveyCategory",
##          "assessmentTotal"
##         FROM
##          "d"
##         ) tsql_23156251825930618619_0000000000
##        ) tsql_23156251825930618619_0000000001
##       ) tsql_23156251825930618619_0000000002
##      ) tsql_23156251825930618619_0000000003
##    ) tsql_23156251825930618619_0000000004
##    WHERE "row_number" = 1
##   ) tsql_23156251825930618619_0000000005
##  ) tsql_23156251825930618619_0000000006
## ) tsql_23156251825930618619_0000000007 ORDER BY "subjectID"

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 %.>% 
  knitr::kable(.)

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

ops %.>%
  op_diagram(.) %.>% 
  DiagrammeR::grViz(.)

See also https://github.com/WinVector/data_algebra/tree/master/Examples/LogisticExample .

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