colwise: Column-wise function.

In plyr: Tools for Splitting, Applying and Combining Data

Column-wise function.

Description

Turn a function that operates on a vector into a function that operates column-wise on a data.frame.

Usage

colwise(.fun, .cols = true, ...)

catcolwise(.fun, ...)

numcolwise(.fun, ...)

Arguments

.fun	function
.cols	either a function that tests columns for inclusion, or a quoted object giving which columns to process
...	other arguments passed on to .fun

Details

catcolwise and numcolwise provide version that only operate on discrete and numeric variables respectively.

Examples

# Count number of missing values
nmissing <- function(x) sum(is.na(x))

# Apply to every column in a data frame
colwise(nmissing)(baseball)
# This syntax looks a little different.  It is shorthand for the
# the following:
f <- colwise(nmissing)
f(baseball)

# This is particularly useful in conjunction with d*ply
ddply(baseball, .(year), colwise(nmissing))

# To operate only on specified columns, supply them as the second
# argument.  Many different forms are accepted.
ddply(baseball, .(year), colwise(nmissing, .(sb, cs, so)))
ddply(baseball, .(year), colwise(nmissing, c("sb", "cs", "so")))
ddply(baseball, .(year), colwise(nmissing, ~ sb + cs + so))

# Alternatively, you can specify a boolean function that determines
# whether or not a column should be included
ddply(baseball, .(year), colwise(nmissing, is.character))
ddply(baseball, .(year), colwise(nmissing, is.numeric))
ddply(baseball, .(year), colwise(nmissing, is.discrete))

# These last two cases are particularly common, so some shortcuts are
# provided:
ddply(baseball, .(year), numcolwise(nmissing))
ddply(baseball, .(year), catcolwise(nmissing))

# You can supply additional arguments to either colwise, or the function
# it generates:
numcolwise(mean)(baseball, na.rm = TRUE)
numcolwise(mean, na.rm = TRUE)(baseball)

plyr documentation built on Oct. 2, 2023, 9:07 a.m.