Repeated consecutive values of group columns will be used to define the title of the groups and will be added as a row title.

as_grouped_data(x, groups, columns = NULL)

Arguments

x

dataset

groups

columns names to be used as row separators.

columns

columns names to keep

See also

Examples

# as_grouped_data -----
library(data.table)
CO2 <- CO2
setDT(CO2)
CO2$conc <- as.integer(CO2$conc)

data_co2 <- dcast(CO2, Treatment + conc ~ Type,
  value.var = "uptake", fun.aggregate = mean)
data_co2
#>      Treatment conc   Quebec Mississippi
#>  1: nonchilled   95 15.26667    11.30000
#>  2: nonchilled  175 30.03333    20.20000
#>  3: nonchilled  250 37.40000    27.53333
#>  4: nonchilled  350 40.36667    29.90000
#>  5: nonchilled  500 39.60000    30.60000
#>  6: nonchilled  675 41.50000    30.53333
#>  7: nonchilled 1000 43.16667    31.60000
#>  8:    chilled   95 12.86667     9.60000
#>  9:    chilled  175 24.13333    14.76667
#> 10:    chilled  250 34.46667    16.10000
#> 11:    chilled  350 35.80000    16.60000
#> 12:    chilled  500 36.66667    16.63333
#> 13:    chilled  675 37.50000    18.26667
#> 14:    chilled 1000 40.83333    18.73333
data_co2 <- as_grouped_data(x = data_co2, groups = c("Treatment"))
data_co2
#>     Treatment conc   Quebec Mississippi
#> 1  nonchilled   NA       NA          NA
#> 3        <NA>   95 15.26667    11.30000
#> 4        <NA>  175 30.03333    20.20000
#> 5        <NA>  250 37.40000    27.53333
#> 6        <NA>  350 40.36667    29.90000
#> 7        <NA>  500 39.60000    30.60000
#> 8        <NA>  675 41.50000    30.53333
#> 9        <NA> 1000 43.16667    31.60000
#> 2     chilled   NA       NA          NA
#> 10       <NA>   95 12.86667     9.60000
#> 11       <NA>  175 24.13333    14.76667
#> 12       <NA>  250 34.46667    16.10000
#> 13       <NA>  350 35.80000    16.60000
#> 14       <NA>  500 36.66667    16.63333
#> 15       <NA>  675 37.50000    18.26667
#> 16       <NA> 1000 40.83333    18.73333