R: Numeric Vectors

numeric {base} | R Documentation

## Numeric Vectors

### Description

Creates or coerces objects of type `"numeric"`. `is.numeric` is a more general test of an object being interpretable as numbers.

### Usage

    numeric(length = 0)
    as.numeric(x, ...)
    is.numeric(x)

### Arguments

`length` | A non-negative integer specifying the desired length. Double values will be coerced to integer: supplying an argument of length other than one is an error.
`x` | object to be coerced or tested.
`...` | further arguments passed to or from other methods.

### Details

`numeric` is identical to `double` (and `real`). It creates a double-precision vector of the specified length with each element equal to `0`.

`as.numeric` is a generic function, but S3 methods must be written for `as.double`. It is identical to `as.double`.

`is.numeric` is an internal generic `primitive` function: you can write methods to handle specific classes of objects, see InternalMethods. It is not the same as `is.double`. Factors are handled by the default method, and there are methods for classes `"Date"`, `"POSIXt"` and `"difftime"` (all of which return false). Methods for `is.numeric` should only return true if the base type of the class is `double` or `integer` and values can reasonably be regarded as numeric (e.g., arithmetic on them makes sense, and comparison should be done via the base type).

### Value

for `numeric` and `as.numeric` see `double`.

The default method for `is.numeric` returns `TRUE` if its argument is of mode `"numeric"` (type `"double"` or type `"integer"`) and not a factor, and `FALSE` otherwise. That is, `is.integer(x) || is.double(x)`, or `(mode(x) == "numeric") && !is.factor(x)`.

### Warning

If `x` is a `factor`, `as.numeric` will return the underlying numeric (integer) representation, which is often meaningless as it may not correspond to the `factor` `levels`, see the ‘Warning’ section in `factor` (and the 2nd example below).

### S4 methods

`as.numeric` and `is.numeric` are internally S4 generic and so methods can be set for them via `setMethod`.

To ensure that `as.numeric` and `as.double` remain identical, S4 methods can only be set for `as.numeric`.

### Note on names

It is a historical anomaly that R has two names for its floating-point vectors, `double` and `numeric` (and formerly had `real`).

`double` is the name of the type. `numeric` is the name of the mode and also of the implicit class. As an S4 formal class, use `"numeric"`.

The potential confusion is that R has used mode `"numeric"` to mean ‘double or integer’, which conflicts with the S4 usage. Thus `is.numeric` tests the mode, not the class, but `as.numeric` (which is identical to `as.double`) coerces to the class.

### References

Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) The New S Language. Wadsworth & Brooks/Cole.

### See Also

`double`, `integer`, `storage.mode`.

### Examples

    ## Conversion does trim whitespace; non-numeric strings give NA + warning
    as.numeric(c("-.1"," 2.7 ","B"))

    ## Numeric values are sometimes accidentally converted to factors.
    ## Converting them back to numeric is trickier than you'd expect.
    f <- factor(5:10)
    as.numeric(f) # not what you might expect, probably not what you want
    ## what you typically meant and want:
    as.numeric(as.character(f))
    ## the same, considerably more efficient (for long vectors):
    as.numeric(levels(f))[f]

[Package base version 4.0.5 Index]