drHexbin: HexBin Aggregation for Distributed Data Frames
In datadr: Divide and Recombine for Large, Complex Data

Description Usage Arguments Value Author(s) References See Also Examples

Create "hexbin" object of hexagonally binned data for a distributed data frame. This computation is division agnostic - it does not matter how the data frame is split up.

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drHexbin(data, xVar, yVar, by = NULL, xTransFn = identity,
  yTransFn = identity, xRange = NULL, yRange = NULL, xbins = 30,
  shape = 1, params = NULL, packages = NULL, control = NULL)

`data`	a distributed data frame
`xVar, yVar`	names of the variables to use
`by`	an optional variable name or vector of variable names by which to group hexbin computations
`xTransFn, yTransFn`	a transformation function to apply to the x and y variables prior to binning
`xRange, yRange`	range of x and y variables (can be left blank if summaries have been computed)
`xbins`	the number of bins partitioning the range of xbnds
`shape`	the shape = yheight/xwidth of the plotting regions
`params`	a named list of objects external to the input data that are needed in the distributed computing (most should be taken care of automatically such that this is rarely necessary to specify)
`packages`	a vector of R package names that contain functions used in `fn` (most should be taken care of automatically such that this is rarely necessary to specify)
`control`	parameters specifying how the backend should handle things (most-likely parameters to `rhwatch` in RHIPE) - see `rhipeControl` and `localDiskControl`

a "hexbin" object

Ryan Hafen

Carr, D. B. et al. (1987) Scatterplot Matrix Techniques for Large N. JASA 83, 398, 424–436.

drQuantile

# create dummy data and divide it
dat <- data.frame(
  xx = rnorm(1000),
  yy = rnorm(1000),
  by = sample(letters, 1000, replace = TRUE))
d <- divide(dat, by = "by", update = TRUE)
# compute hexbins on divided object
dhex <- drHexbin(d, xVar = "xx", yVar = "yy")
# dhex is equivalent to running on undivided data:
hexbin(dat$xx, dat$yy)