Missing values in R

drop_na, replace_na and fill: three answers to a gap.

library(tidyr)
library(dplyr)

runs <- tibble(
  lang = c("r", NA, "python", "python"),
  tpm = c(88, 96, NA, 104),
  note = c(NA, NA, "slow", NA)
)

print(drop_na(runs))
print(drop_na(runs, tpm))
print(replace_na(runs, list(lang = "unknown", tpm = 0, note = "")))
print(fill(runs, lang, .direction = "down"))
print(colSums(is.na(runs)))

How it works

1. drop_na with no arguments drops any row with an NA.
2. replace_na takes a value per column.
3. fill carries the last value down, which suits time series.

Keywords and builtins used here

• c
• colSums
• drop_na
• fill
• library
• list
• print
• replace_na
• tibble

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Step 2 of 3 in Nesting & gaps, step 7 of 12 in Reshaping & reading.

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