Missing data in R

Detecting, removing, and imputing NA values.

values <- c(3, NA, 7, NA, 12)

which_missing <- is.na(values)
how_many <- sum(is.na(values))
complete <- values[!is.na(values)]

avg <- mean(values, na.rm = TRUE)
filled <- ifelse(is.na(values), avg, values)

df <- data.frame(a = c(1, NA), b = c(NA, 4))
clean_rows <- df[complete.cases(df), ]

How it works

1. is.na flags gaps; summing it counts them.
2. na.rm = TRUE excludes them from statistics.
3. complete.cases keeps only fully observed rows.

Keywords and builtins used here

• c
• ifelse
• mean
• sum

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Step 4 of 4 in Reshaping & combining, step 7 of 8 in Data frames in base R.

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Missing data in other languages

• Python