Indexing and missing values

The idea

R uses one-based indices: the first element is x[1]. Positive indices select positions, negative indices exclude positions, and logical vectors select where their entries are true. Zero selects no position. Match a logical selector to the data it describes so recycling does not quietly change the selection. A comparison such as x >= 10 builds a vector of logical results rather than one overall answer.

NA represents a missing value, and calculations or comparisons involving it often remain unknown. Use is.na to test for missingness; comparing a value to NA does not answer whether it is missing. Many summary functions accept na.rm = TRUE, but removing missing entries is a policy choice. Decide what an entirely missing input should mean before treating its summary as a meaningful measurement.

x <- c(4, NA, 9, 2)
keep <- !is.na(x) & x >= 4
cat(x[keep], sep = ",")
cat("
")
cat(sum(x, na.rm = TRUE), "
", sep = "")

4,9
15

The explicit missingness check makes the selector false at the missing position. The sum excludes that missing value and adds the three known numbers.