ClickHouse/docs/en/data_types/float.md
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# Float32, Float64
[Floating point numbers](https://en.wikipedia.org/wiki/IEEE_754).
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.
## Using Floating-point Numbers
- Computations with floating-point numbers might produce a rounding error.
```sql
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 reading floating point numbers from rows, 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.
```sql
SELECT 0.5 / 0
```
```
┌─divide(0.5, 0)─┐
│ inf │
└────────────────┘
```
- `-Inf` Negative infinity.
```sql
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](../query_language/select.md#query_language-queries-order_by).