sjmisc (version 2.8.10)

has_na: Check if variables or cases have missing / infinite values

Description

This functions checks if variables or observations in a data frame have NA, NaN or Inf values.

Usage

has_na(x, ..., by = c("col", "row"), out = c("table", "df", "index"))
incomplete_cases(x, ...)
complete_cases(x, ...)
complete_vars(x, ...)
incomplete_vars(x, ...)

Value

If x is a vector, returns TRUE if x has any missing or infinite values. If x is a data frame, returns TRUE for each variable (if by = "col") or observation (if by = "row") that has any missing or infinite values. If out = "table", results are returned as data frame, with column number, variable name and label, and a logical vector indicating if a variable has missing values or not. However, it's printed in colors, with green rows indicating that a variable has no missings, while red rows indicate the presence of missings or infinite values. If out = "index", a named vector is returned.

Arguments

x

A data frame.

...

Optional, unquoted names of variables that should be selected for further processing. Required, if x is a data frame (and no vector) and only selected variables from x should be processed. You may also use functions like : or tidyselect's select-helpers. See 'Examples' or package-vignette.

by

Whether to check column- or row-wise for missing and infinite values. If by = "col", has_na() checks for NA/NaN/Inf in columns; If by = "row", has_na() checks each row for these values.

out

Output (return) format of the results. May be abbreviated.

Examples

data(efc)
has_na(efc$e42dep)
has_na(efc, e42dep, tot_sc_e, c161sex)
has_na(efc)

has_na(efc, e42dep, tot_sc_e, c161sex, out = "index")
has_na(efc, out = "df")

has_na(efc, by = "row")
has_na(efc, e42dep, tot_sc_e, c161sex, by = "row", out = "index")
has_na(efc, by = "row", out = "df")

complete_cases(efc, e42dep, tot_sc_e, c161sex)
incomplete_cases(efc, e42dep, tot_sc_e, c161sex)
complete_vars(efc, e42dep, tot_sc_e, c161sex)
incomplete_vars(efc, e42dep, tot_sc_e, c161sex)