datadr (version 0.8.4)

combMean: Mean Recombination

Description

Mean recombination -- Calculate the elementwise mean of a vector in each value

Usage

combMean(...)

Arguments

...

additional attributes to define the combiner (currently only used internally)

Details

combMean is passed to the argument combine in recombine

This method assumes that the values of the key-value pairs each consist of a numeric vector (with the same length). The mean is calculated elementwise across all the keys.

See Also

divide, recombine, combCollect, combDdo, combDdf, combRbind, combMeanCoef

Examples

# Create a distributed data frame using the iris data set
bySpecies <- divide(iris, by = "Species")

# Add a transformation that returns a vector of sums for each subset, one
# mean for each variable
bySpeciesTrans <- addTransform(bySpecies, function(x) apply(x, 2, sum))
bySpeciesTrans[[1]]

# Calculate the elementwise mean of the vector of sums produced by
# the transform, across the keys
out1 <- recombine(bySpeciesTrans, combine = combMean)
out1

# A more concise (and readable) way to do it
bySpecies %>%
  addTransform(function(x) apply(x, 2, sum)) %>%
  recombine(combMean)

# This manual, non-datadr approach illustrates the above computation

# This step mimics the transformation above
sums <- aggregate(. ~ Species, data = iris, sum)
sums

# And this step mimics the mean recombination
out2 <- apply(sums[,-1], 2, mean)
out2

# These are the same
identical(out1, out2)

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