cdata

John Mount, Win-Vector LLC

2019-04-20

The cdata package is a demonstration of the “coordinatized data” theory and includes an implementation of the “fluid data” methodology. The recommended tutorial is: Fluid data reshaping with cdata. We also have a short free cdata screencast (and another example can be found here).

Briefly cdata supplies data transform operators that:

• Work on local data or with any DBI data source.
• Are powerful generalizations of the operators commonly called pivot and un-pivot.

A quick example:

run_vignette <- requireNamespace("RSQLite", quietly = TRUE) &&
  requireNamespace("DBI", quietly = TRUE)

library("cdata")
my_db <- DBI::dbConnect(RSQLite::SQLite(), 
                        ":memory:")

# pivot example
d <- build_frame(
   "meas", "val" /
   "AUC" , 0.6   /
   "R2"  , 0.2   )

DBI::dbWriteTable(my_db,
                  'd',
                  d,
                  temporary = TRUE)
qlook(my_db, 'd')

## table `d` SQLiteConnection 
##  nrow: 2 
## 'data.frame':    2 obs. of  2 variables:
##  $ meas: chr  "AUC" "R2"
##  $ val : num  0.6 0.2

cT <- build_pivot_control_q('d',
                            columnToTakeKeysFrom= 'meas',
                            columnToTakeValuesFrom= 'val',
                            my_db = my_db)
tab <- blocks_to_rowrecs_q('d',
                           keyColumns = NULL,
                           controlTable = cT,
                           my_db = my_db)
qlook(my_db, tab)

## table `mvtcq_46255426283341597082_0000000000` SQLiteConnection 
##  nrow: 1 
## 'data.frame':    1 obs. of  2 variables:
##  $ AUC: num 0.6
##  $ R2 : num 0.2

DBI::dbDisconnect(my_db)

Install via CRAN:

install.packages("cdata")

Note: cdata is targeted at data with “tame column names” (column names that are valid both in databases, and as R unquoted variable names) and basic types (column values that are simple R types such as character, numeric, logical, and so on).