Split H2O Dataset, Apply Function, and Return Results

Share:

Description

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

Usage

1
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

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
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)

Want to suggest features or report bugs for rdrr.io? Use the GitHub issue tracker.