R/map_fields.R
map_fields_q.Rd
Map field values from one column into new derived columns (query based, takes name of table).
map_fields_q(
dname,
cname,
mname,
my_db,
rname,
...,
d_qualifiers = NULL,
m_qualifiers = NULL
)
name of table to re-map.
name of column to re-map.
name of table of data describing the mapping (cname column is source, derived columns are destinations).
database handle.
name of result table.
force later arguments to be by name.
optional named ordered vector of strings carrying additional db hierarchy terms, such as schema.
optional named ordered vector of strings carrying additional db hierarchy terms, such as schema.
re-mapped table
if (requireNamespace("DBI", quietly = TRUE) &&
requireNamespace("RSQLite", quietly = TRUE)) {
my_db <- DBI::dbConnect(RSQLite::SQLite(),
":memory:")
DBI::dbWriteTable(
my_db,
'd',
data.frame(what = c("acc", "loss",
"val_acc", "val_loss"),
score = c(0.8, 1.2,
0.7, 1.7),
stringsAsFactors = FALSE),
overwrite = TRUE,
temporary = TRUE)
DBI::dbWriteTable(
my_db,
'm',
data.frame(what = c("acc", "loss",
"val_acc", "val_loss"),
measure = c("accuracy", "log-loss",
"accuracy", "log-loss"),
dataset = c("train", "train", "validation", "validation"),
stringsAsFactors = FALSE),
overwrite = TRUE,
temporary = TRUE)
map_fields_q('d', 'what', 'm', my_db, "dm")
cdata::qlook(my_db, 'dm')
DBI::dbDisconnect(my_db)
}
#> table `dm` SQLiteConnection
#> nrow: 4
#> 'data.frame': 4 obs. of 4 variables:
#> $ what : chr "acc" "loss" "val_acc" "val_loss"
#> $ score : num 0.8 1.2 0.7 1.7
#> $ measure: chr "accuracy" "log-loss" "accuracy" "log-loss"
#> $ dataset: chr "train" "train" "validation" "validation"