dropRowsWithAllNA {petersenlab}

Drop NA rows.

Description

Drop rows with all missing (NA) values.

Usage

dropRowsWithAllNA(data, ignore = NULL)

Arguments

data

Dataframe to drop rows from.

ignore

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

Details

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

Value

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

See Also

Other dataManipulation: columnBindFill(), convert.magic(), dropColsWithAllNA()

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

Examples

# Prepare Data
df <- expand.grid(ID = 1:100, time = c(1, 2, 3))
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
dropRowsWithAllNA(df, ignore = c("ID","time"))