Testing numeric variables for NA/NaN/Inf
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In R, a numeric variable is either a number (like 0, 42, or -3.14), or one of 4 special values: NA, NaN, Inf or -Inf. It can be hard to remember how the is.x functions treat each of the special values, especially NA and NaN! The table below summarizes how each of these values is treated by different base R functions. Functions are listed in alphabetical order.
| Function | Typical number | NA | NaN | Inf | -Inf |
|---|---|---|---|---|---|
| is.double | TRUE | FALSE | TRUE | TRUE | TRUE |
| is.finite | TRUE | FALSE | FALSE | FALSE | FALSE |
| is.infinite | FALSE | FALSE | FALSE | TRUE | TRUE |
| is.integer | *1 | FALSE | FALSE | FALSE | FALSE |
| is.na | FALSE | TRUE | TRUE | FALSE | FALSE |
| is.nan | FALSE | FALSE | TRUE | FALSE | FALSE |
| is.null | FALSE | FALSE | FALSE | FALSE | FALSE |
| is.numeric | TRUE | *2 | TRUE | TRUE | TRUE |
*1: is.integer can return TRUE or FALSE, depending on whether the number is an integer or not.
*2: R actually has different types of NAs (see here for more details). is.numeric(NA) returns FALSE, but is.numeric(NA_integer_) and is.numeric(NA_real_) return TRUE. Interestingly, is.numeric(NA_complex_) returns FALSE.
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