Comparison {base} | R Documentation

## Relational Operators

### Description

Binary operators which allow the comparison of values in atomic vectors.

### Usage

    x < y
    x > y
    x <= y
    x >= y
    x == y
    x != y

### Arguments

`x, y` | atomic vectors, symbols, calls, or other objects for which methods have been written.

### Details

The binary comparison operators are generic functions: methods can be written for them individually or via the `Ops`) group generic function. (See `Ops` for how dispatch is computed.)

Comparison of strings in character vectors is lexicographic within the strings using the collating sequence of the locale in use: see `locales`. The collating sequence of locales such as `en_US` is normally different from `C` (which should use ASCII) and can be surprising.

At least one of `x` and `y` must be an atomic vector, but if the other is a list R attempts to coerce it to the type of the atomic vector: this will succeed if the list is made up of elements of length one that can be coerced to the correct type.

If the two arguments are atomic vectors of different types, one is coerced to the type of the other, the (decreasing) order of precedence being character, complex, numeric, integer, logical and raw.

When comparisons are made between character strings, parts of the strings after embedded `nul` characters are ignored. (This is necessary as the position of `nul` in the collation sequence is undefined, and we want one of `<`, `==` and `>` to be true for any comparison.)

Missing values (`NA`) and `NaN` values are regarded as non-comparable even to themselves, so comparisons involving them will always result in `NA`. Missing values can also result when character strings are compared and one is not valid in the current collation locale.

Language objects such as symbols and calls are deparsed to character strings before comparison.

### Value

A vector of logicals indicating the result of the element by element comparison. The elements of shorter vectors are recycled as necessary.
Objects such as arrays or time-series can be compared this way provided they are conformable.

### Note

Do not use `==` and `!=` for tests, such as in `if` expressions, where you must get a single `TRUE` or `FALSE`. Unless you are absolutely sure that nothing unusual can happen, you should use the `identical` function instead.

For numerical and complex values, remember `==` and `!=` do not allow for the finite representation of fractions, nor for rounding error. Using `all.equal` with `identical` is almost always preferable. See the examples.

### References

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

### See Also

`factor` for the behaviour with factor arguments.

`Syntax` for operator precedence.

### Examples

    x <- rnorm(20)
    x < 1
    x[x > 0]

    x1 <- 0.5 - 0.3
    x2 <- 0.3 - 0.1
    x1 == x2                           # FALSE on most machines
    identical(all.equal(x1, x2), TRUE) # TRUE everywhere

[Package base version 2.5.0 Index]