CFUN {ff} | R Documentation |
Collapsing functions for batch processing
Description
These are used in aggregating the chunks resulting from batch processing. They are usually called via do.call
Usage
ccbind(...)
crbind(...)
cfun(..., FUN, FUNARGS = list())
cquantile(..., probs = seq(0, 1, 0.25), na.rm = FALSE, names = TRUE, type = 7)
csummary(..., na.rm = "ignored")
cmedian(..., na.rm = FALSE)
clength(..., na.rm = FALSE)
csum(..., na.rm = FALSE)
cmean(..., na.rm = FALSE)
Arguments
... |
|
FUN |
a aggregating function |
FUNARGS |
further arguments to the aggregating function |
na.rm |
TRUE to remove NAs |
probs |
see |
names |
see |
type |
see |
Details
CFUN | FUN | comment |
ccbind | cbind | like cbind but respecting names |
crbind | rbind | like rbind but respecting names |
cfun | crbind the input chunks and then apply 'FUN' to each column |
|
cquantile | quantile | crbind the input chunks and then apply 'quantile' to each column |
csummary | summary | crbind the input chunks and then apply 'summary' to each column |
cmedian | median | crbind the input chunks and then apply 'median' to each column |
clength | length | crbind the input chunks and then determine the number of values in each column |
csum | sum | crbind the input chunks and then determine the sum values in each column |
cmean | mean | crbind the input chunks and then determine the (unweighted) mean in each column |
In order to use CFUNs on the result of lapply
or ffapply
use do.call
.
Value
depends on the CFUN used
ff options
xx TODO: extend this for weighted means, weighted median etc.,
google "Re: [R] Weighted median"
Note
Currently - for command line convenience - we map the elements of a single list argument to ..., but this may change in the future.
Author(s)
Jens Oehlschlägel
See Also
Examples
X <- lapply(split(rnorm(1000), 1:10), summary)
do.call("crbind", X)
do.call("csummary", X)
do.call("cmean", X)
do.call("cfun", c(X, list(FUN=mean, FUNARGS=list(na.rm=TRUE))))
rm(X)
[Package ff version 4.0.12 Index]