# Float32, Float64

Types are equivalent to types of C:

• `Float32``float`.
• `Float64``double`.

We recommend that you store data in integer form whenever possible. For example, convert fixed precision numbers to integer values, such as monetary amounts or page load times in milliseconds.

Aliases:

• `Float32``FLOAT`.
• `Float64``DOUBLE`.

When creating tables, numeric parameters for floating point numbers can be set (e.g. `FLOAT(12)`, `FLOAT(15, 22)`, `DOUBLE(12)`, `DOUBLE(4, 18)`), but ClickHouse ignores them.

## Using Floating-point Numbers​

• Computations with floating-point numbers might produce a rounding error.
``SELECT 1 - 0.9``
``┌───────minus(1, 0.9)─┐│ 0.09999999999999998 │└─────────────────────┘``
• The result of the calculation depends on the calculation method (the processor type and architecture of the computer system).
• Floating-point calculations might result in numbers such as infinity (`Inf`) and “not-a-number” (`NaN`). This should be taken into account when processing the results of calculations.
• When parsing floating-point numbers from text, the result might not be the nearest machine-representable number.

## NaN and Inf​

In contrast to standard SQL, ClickHouse supports the following categories of floating-point numbers:

• `Inf` – Infinity.
``SELECT 0.5 / 0``
``┌─divide(0.5, 0)─┐│            inf │└────────────────┘``
• `-Inf` — Negative infinity.
``SELECT -0.5 / 0``
``┌─divide(-0.5, 0)─┐│            -inf │└─────────────────┘``
• `NaN` — Not a number.
``SELECT 0 / 0``
``┌─divide(0, 0)─┐│          nan │└──────────────┘``

See the rules for `NaN` sorting in the section ORDER BY clause.