rowrecs_to_blocks: Map a data records from row records to block records.

In cdata: Fluid Data Transformations

Map a data records from row records to block records.

Description

Map a data records from row records (records that are exactly single rows) to block records (records that may be more than one row).

Usage

rowrecs_to_blocks(
  wideTable,
  controlTable,
  ...,
  checkNames = TRUE,
  checkKeys = FALSE,
  strict = FALSE,
  controlTableKeys = colnames(controlTable)[[1]],
  columnsToCopy = NULL,
  tmp_name_source = wrapr::mk_tmp_name_source("rrtbl"),
  temporary = TRUE,
  allow_rqdatatable = FALSE
)

## Default S3 method:
rowrecs_to_blocks(
  wideTable,
  controlTable,
  ...,
  checkNames = TRUE,
  checkKeys = FALSE,
  strict = FALSE,
  controlTableKeys = colnames(controlTable)[[1]],
  columnsToCopy = NULL,
  tmp_name_source = wrapr::mk_tmp_name_source("rrtobd"),
  temporary = TRUE,
  allow_rqdatatable = FALSE
)

## S3 method for class 'relop'
rowrecs_to_blocks(
  wideTable,
  controlTable,
  ...,
  checkNames = TRUE,
  checkKeys = FALSE,
  strict = FALSE,
  controlTableKeys = colnames(controlTable)[[1]],
  columnsToCopy = NULL,
  tmp_name_source = wrapr::mk_tmp_name_source("rrtbl"),
  temporary = TRUE,
  allow_rqdatatable = FALSE
)

Arguments

wideTable	data.frame containing data to be mapped (in-memory data.frame).
controlTable	table specifying mapping (local data frame).
...	force later arguments to be by name.
checkNames	logical, if TRUE check names.
checkKeys	logical, if TRUE check columnsToCopy form row keys (not a requirement, unless you want to be able to invert the operation).
strict	logical, if TRUE check control table name forms.
controlTableKeys	character, which column names of the control table are considered to be keys.
columnsToCopy	character array of column names to copy.
tmp_name_source	a tempNameGenerator from cdata::mk_tmp_name_source()
temporary	logical, if TRUE use temporary tables
allow_rqdatatable	logical, if TRUE allow rqdatatable shortcutting on simple conversions.

Details

The controlTable defines the names of each data element in the two notations: the notation of the tall table (which is row oriented) and the notation of the wide table (which is column oriented). controlTable[ , 1] (the group label) cross colnames(controlTable) (the column labels) are names of data cells in the long form. controlTable[ , 2:ncol(controlTable)] (column labels) are names of data cells in the wide form. To get behavior similar to tidyr::gather/spread one builds the control table by running an appropriate query over the data.

Some discussion and examples can be found here: https://winvector.github.io/FluidData/FluidData.html and here https://github.com/WinVector/cdata.

rowrecs_to_blocks.default will change some factor columns to character, and there are issues with time columns with different time zones.

Value

long table built by mapping wideTable to one row per group

See Also

build_unpivot_control, blocks_to_rowrecs

Examples

  # un-pivot example
  d <- data.frame(AUC = 0.6, R2 = 0.2)
  cT <- build_unpivot_control(nameForNewKeyColumn= 'meas',
                              nameForNewValueColumn= 'val',
                              columnsToTakeFrom= c('AUC', 'R2'))
  rowrecs_to_blocks(d, cT)



d <- data.frame(AUC = 0.6, R2 = 0.2)
cT <- build_unpivot_control(
  nameForNewKeyColumn= 'meas',
  nameForNewValueColumn= 'val',
  columnsToTakeFrom= c('AUC', 'R2'))

ops <- rquery::local_td(d) %.>%
  rowrecs_to_blocks(., cT)
cat(format(ops))

if(requireNamespace("rqdatatable", quietly = TRUE)) {
  library("rqdatatable")
  d %.>%
    ops %.>%
    print(.)
}

if(requireNamespace("RSQLite", quietly = TRUE)) {
  db <- DBI::dbConnect(RSQLite::SQLite(), ":memory:")
  DBI::dbWriteTable(db,
                    'd',
                    d,
                    overwrite = TRUE,
                    temporary = TRUE)
  db %.>%
    ops %.>%
    print(.)
  DBI::dbDisconnect(db)
}

cdata documentation built on Aug. 20, 2023, 1:06 a.m.