missing: Tools for Working With Missing Values

In arkhe: Tools for Cleaning Rectangular Data

Tools for Working With Missing Values

Description

• remove_NA() remove rows/columns that contain missing values.

• replace_NA replaces missing values values.

Usage

remove_NA(x, ...)

replace_NA(x, ...)

## S4 method for signature 'ANY'
remove_NA(x, margin = 1, all = FALSE)

## S4 method for signature 'matrix'
replace_NA(x, value = 0)

## S4 method for signature 'data.frame'
replace_NA(x, value = 0)

Arguments

x	An R object (should be a matrix or a data.frame).
...	Currently not used.
margin	A length-one numeric vector giving the subscripts which the function will be applied over (1 indicates rows, 2 indicates columns).
all	A logical scalar. If TRUE, only the rows/columns whose values all meet the condition defined by f are considered. If FALSE (the default), only rows/columns where at least one value validates the condition defined by f are considered.
value	A possible replacement value.

Author(s)

N. Frerebeau

See Also

Other data cleaning tools: compact(), count(), detect(), discard(), empty, infinite, keep(), remove_constant(), zero

Examples

## Create a data matrix
X <- matrix(sample(1:10, 25, TRUE), nrow = 5, ncol = 5)

## Add NA
k <- sample(1:25, 3, FALSE)
X[k] <- NA
X

## Remove rows with NA
remove_NA(X, margin = 1)

## Replace NA with zeros
replace_NA(X, value = 0)

arkhe documentation built on Nov. 17, 2023, 5:09 p.m.