# tensorplay._composite_funcs.nanquantile

Source: https://www.tensorplay.cn/docs/generated/tensorplay._composite_funcs.nanquantile.html

```python
tensorplay._composite_funcs.nanquantile(input, q, dim=None, keepdim=False, *, interpolation='linear', out=None) → Tensor
```

This is a variant of tensorplay.quantile() that “ignores” NaN values,
computing the quantiles q as if NaN values in input did
not exist. If all values in a reduced row are NaN then the quantiles for
that reduction will be NaN. See the documentation for tensorplay.quantile().

Parameters:

- input ([Tensor](/docs/generated/tensorplay.Tensor.html#tensorplay.Tensor)) – the input tensor.

- q ([float](https://docs.python.org/3/builtins/functions.html#float) or [Tensor](/docs/generated/tensorplay.Tensor.html#tensorplay.Tensor)) – a scalar or 1D tensor of quantile values in the range [0, 1]

- dim ([int](https://docs.python.org/3/builtins/functions.html#int), optional) – the dimension to reduce. If None, all dimensions are reduced. keepdim (bool, optional): whether the output tensor has dim retained or not. Default: False.

Keyword Arguments:

- interpolation ([str](https://docs.python.org/3/builtins/stdtypes.html#str)) – interpolation method to use when the desired quantile lies between two data points. Can be linear, lower, higher, midpoint and nearest. Default is linear.

- out ([Tensor](/docs/generated/tensorplay.Tensor.html#tensorplay.Tensor), optional) – the output tensor.

Example:

```
>>> t = tensorplay.tensor([float('nan'), 1, 2])
>>> t.quantile(0.5)
tensor(nan)
>>> t.nanquantile(0.5)
tensor(1.5000)
>>> t = tensorplay.tensor([[float('nan'), float('nan')], [1, 2]])
>>> t
tensor([[nan, nan],
        [1., 2.]])
>>> t.nanquantile(0.5, dim=0)
tensor([1., 2.])
>>> t.nanquantile(0.5, dim=1)
tensor([   nan, 1.5000])
```