expss (version 0.11.4)

if_na: Replace values with NA and vice-versa

Description

• if_na replaces NA values in vector/data.frame/matrix/list with supplied value. For single value argument label can be provided with label argument. If replacement value is vector then if_na uses for replacement values from appropriate positions. An opposite operation is na_if.

• na_if replaces values with NA in vector/data.frame/matrix/list. Another alias for this is mis_val.

• valid returns logical vector which indicate the presence of at least one not-NA value in row. For vector or single column data.frame result is the same as with complete.cases. There is a special case for data.frame of class dichotomy. In this case result indicate the presence of at least one 1 in a row.

Usage

if_na(x, value, label = NULL)
if_na(x, label = NULL) <- value
x %if_na% value
na_if(x, value, with_labels = FALSE)
na_if(x, with_labels = FALSE) <- value
x %na_if% value
mis_val(x, value, with_labels = FALSE)
mis_val(x, with_labels = FALSE) <- value
valid(x)

Value

object of the same form and class as x. valid returns logical vector.

Format

An object of class character of length 1.

Arguments

x

vector/matrix/data.frame/list

value

single value, vector of the same length as number of rows in x, or function (criteria) for na_if. See recode for details.

label

a character of length 1. Label for value which replace NA.

with_labels

logical. FALSE by default. Should we also remove labels of values which we recode to NA?

Examples

# simple case
a = c(NA, 2, 3, 4, NA)
if_na(a, 99)

# the same result
a %if_na% 99

# with label
a = c(NA, 2, 3, 4, NA)
if_na(a, 99, label = "Hard to say")

# in-place replacement. The same result:
if_na(a, label = "Hard to say") = 99 
a # c(99, 2, 3, 4, 99)

# replacement with values from other variable
a = c(NA, 2, 3, 4, NA)
b = 1:5
if_na(a, b)

# replacement with group means
# make data.frame 
set.seed(123)
group = sample(1:3, 30, replace = TRUE)
param = runif(30)
param[sample(30, 10)] = NA # place 10 NA's
df = data.frame(group, param)

# replace NA's with group means
if_na(df$param) = window_fun(df$param, df$group, mean_col)
df

######################
### na_if examples ###
######################

a = c(1:5, 99)
# 99 to NA
na_if(a, 99)    # c(1:5, NA)

a %na_if% 99    # same result

# values which greater than 4 to NA
na_if(a, gt(4)) # c(1:4, NA, NA)

# alias 'mis_val', with_labels = TRUE
a = c(1, 1, 2, 2, 99)
val_lab(a) = c(Yes = 1, No = 2, "Hard to say" = 99)
mis_val(a, 99, with_labels = TRUE)

set.seed(123)
dfs = data.frame(
      a = c("bad value", "bad value", "good value", "good value", "good value"),
      b = runif(5)
)

# rows with 'bad value' will be filled with NA
# logical argument and recycling by columns
na_if(dfs, dfs$a=="bad value")

a = rnorm(50)
# values greater than 1 or less than -1 will be set to NA
# special functions usage
na_if(a, lt(-1) | gt(1))

# values inside [-1, 1] to NA
na_if(a, -1 %thru% 1)