petersenlab (version 1.1.0)

dropColsWithAllNA: Drop NA columns.

Description

Drop columns with all missing (NA) values.

Usage

dropColsWithAllNA(data, ignore = NULL)

Value

A dataframe with columns removed that had all missing values in non-ignored columns.

Arguments

data

Dataframe to drop columns from.

ignore

Names of columns to ignore for determining whether each row had all missing values.

Details

Drop columns that have no observed values, i.e., all values in the column are missing (NA), excluding the ignored columns.

See Also

Other dataManipulation: columnBindFill(), convert.magic(), dropRowsWithAllNA(), varsDifferentTypes()

Other dataEvaluations: dropRowsWithAllNA(), is.nan.data.frame(), not_all_na(), not_any_na()

Examples

# Prepare Data
df <- expand.grid(ID = 1:100, time = c(1, 2, 3), rater = c(1, 2),
naCol1 = NA, naCol2 = NA)
df <- df[order(df$ID),]
row.names(df) <- NULL
df$score1 <- rnorm(nrow(df))
df$score2 <- rnorm(nrow(df))
df$score3 <- rnorm(nrow(df))
df[sample(1:nrow(df), size = 100), c("score1","score2","score3")] <- NA

# Drop Rows with All NA in Non-Ignored Columns
dropColsWithAllNA(df)
dropColsWithAllNA(df, ignore = c("naCol2"))