colwise: 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

Run this code

# NOT RUN {
# 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)
# }

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