Split H2O Dataset, Apply Function, and Return Results

For each subset of an H2O data set, apply a user-specified function, then combine the results. This is an experimental feature.

h2o.ddply(X, .variables, FUN, ..., .progress = "none")

Arguments

X	An H2OFrame object to be processed.
.variables	Variables to split X by, either the indices or names of a set of columns.
FUN	Function to apply to each subset grouping.
...	Additional arguments passed on to FUN.
.progress	Name of the progress bar to use. #TODO: (Currently unimplemented)

Value

Returns an H2OFrame object containing the results from the split/apply operation, arranged

See also

ddply for the plyr library implementation.

Examples

# NOT RUN {
library(h2o)
h2o.init()

# Import iris dataset to H2O
irisPath <- system.file("extdata", "iris_wheader.csv", package = "h2o")
iris.hex <- h2o.uploadFile(path = irisPath, destination_frame = "iris.hex")
# Add function taking mean of sepal_len column
fun <- function(df) { sum(df[,1], na.rm = TRUE)/nrow(df) }
# Apply function to groups by class of flower
# uses h2o's ddply, since iris.hex is an H2OFrame object
res <- h2o.ddply(iris.hex, "class", fun)
head(res)
# }