# has_nans#

ivy.has_nans(x, /, *, include_infs=True)[source]#

Determine whether the array contains any nans, as well as infs or -infs if specified.

Parameters:
• x (`Union`[`Array`, `NativeArray`]) – Input array.

• include_infs (`bool`, default: `True`) – Whether to include `+infinity` and `-infinity` in the check. Default is `True`.

Return type:

`bool`

Returns:

ret – Boolean as to whether the array contains nans.

Both the description and the type hints above assumes an array input for simplicity, but this function is nestable, and therefore also accepts `ivy.Container` instances in place of any of the arguments.

Examples

With `ivy.Array` input:

```>>> x = ivy.array([1, 2, 3])
>>> y = ivy.has_nans(x)
>>> print(y)
False
```
```>>> x = ivy.array([float('nan'), 2, 3])
>>> y = ivy.has_nans(x)
>>> print(y)
True
```
```>>> x = ivy.array([float('inf'), 2, 3])
>>> y = ivy.has_nans(x)
>>> print(y)
True
```
```>>> x = ivy.array([float('inf'), 2, 3])
>>> y = ivy.has_nans(x, include_infs=False)
>>> print(y)
False
```

With `ivy.Container` input:

```>>> x = ivy.Container(a=ivy.array([0., 1., 2.]), b=ivy.array([3., 4., 5.]))
>>> y = ivy.has_nans(x)
>>> print(y)
{
a: False,
b: False
}
```
Array.has_nans(self, /, *, include_infs=True)[source]#

ivy.Array instance method variant of ivy.has_nans. This method simply wraps the function, and so the docstring for ivy.has_nans also applies to this method with minimal changes.

Parameters:
• self (`Array`) – input array

• include_infs (`bool`, default: `True`) – Whether to include `+infinity` and `-infinity` in the check. Default is `True`.

Returns:

ret – Boolean as to whether the array contains nans.

Examples

```>>> x = ivy.array([1, 2, 3])
>>> y = x.has_nans()
>>> print(y)
False
```
Container.has_nans(self, /, *, include_infs=True, key_chains=None, to_apply=True, prune_unapplied=False, map_sequences=False)[source]#

Determine whether arrays in the container contain any nans, as well as infs or -infs if specified.

Parameters:
• include_infs (`Union`[`bool`, `Container`], default: `True`) – Whether to include infs and -infs in the check. Default is True.

• key_chains (`Optional`[`Union`[`List`[`str`], `Dict`[`str`, `str`], `Container`]], default: `None`) – The key-chains to apply or not apply the method to. Default is `None`.

• to_apply (`Union`[`bool`, `Container`], default: `True`) – If True, the method will be applied to key_chains, otherwise key_chains will be skipped. Default is `True`.

• prune_unapplied (`Union`[`bool`, `Container`], default: `False`) – Whether to prune key_chains for which the function was not applied. Default is `False`.

• map_sequences (`Union`[`bool`, `Container`], default: `False`) – Whether to also map method to sequences (lists, tuples). Default is `False`.

Return type:

`Container`

Returns:

Whether the container has any nans, applied across the entire container.

Examples

```>>> x = ivy.Container(a=ivy.array([1, 2]), b=ivy.array([float('nan'), 2]))
>>> y = x.has_nans()
>>> print(y)
{
a: False,
b: True
}
```