### 11.2 Floating-Point Data Types ¶

Floating point is the binary analogue of scientific notation: internally it represents a number as a fraction and a binary exponent; the value is that fraction multiplied by the specified power of 2. (The C standard nominally permits other bases, but in GNU C the base is always 2.)

For instance, to represent 6, the fraction would be 0.75 and the exponent would be 3; together they stand for the value 0.75 * 23, meaning 0.75 * 8. The value 1.5 would use 0.75 as the fraction and 1 as the exponent. The value 0.75 would use 0.75 as the fraction and 0 as the exponent. The value 0.375 would use 0.75 as the fraction and −1 as the exponent.

These binary exponents are used by machine instructions. You can write a floating-point constant this way if you wish, using hexadecimal; but normally we write floating-point numbers in decimal (base 10). See Floating-Point Constants.

C has three floating-point data types:

`double`

  “Double-precision” floating point, which uses 64 bits. This is the normal floating-point type, and modern computers normally do their floating-point computations in this type, or some wider type. Except when there is a special reason to do otherwise, this is the type to use for floating-point values.

`float`

  “Single-precision” floating point, which uses 32 bits. It is useful for floating-point values stored in structures and arrays, to save space when the full precision of `double` is not needed. In addition, single-precision arithmetic is faster on some computers, and occasionally that is useful. But not often—most programs don’t use the type `float`.

  C would be cleaner if `float` were the name of the type we use for most floating-point values; however, for historical reasons, that’s not so.

`long double`

  “Extended-precision” floating point is either 80-bit or 128-bit precision, depending on the machine in use. On some machines, which have no floating-point format wider than `double`, this is equivalent to `double`.

Floating-point arithmetic raises many subtle issues. See Floating Point in Depth, for more information.