NanPercentile
=============

Compute the percentile of the data along the specified axis, ignoring NaN values.

**Abstract Signature:**

``NanPercentile(a: Tensor, q: number | Tensor, axis: int | Sequence[int] | None, method: str = linear, keepdims: bool = False)``

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        <div id="PyTorch_0" class="op-tab-pane active"><h4>PyTorch</h4><div class="op-detail-row"><span class="label">API:</span> <code>torch.nanquantile</code></div><div class="op-detail-row"><span class="label">Strategy:</span> <span>Direct Mapping</span></div><div class="op-detail-row"><a href="https://pytorch.org/docs/stable/generated/torch.nanquantile.html" target="_blank" class="op-doc-link">Official Docs ↗</a></div></div><div id="JAX (Core)_1" class="op-tab-pane "><h4>JAX (Core)</h4><div class="op-detail-row"><span class="label">API:</span> <code>jax.numpy.nanpercentile</code></div><div class="op-detail-row"><span class="label">Strategy:</span> <span>Direct Mapping</span></div><div class="op-detail-row"><a href="https://jax.readthedocs.io/en/latest/_autosummary/jax.numpy.nanpercentile.html" target="_blank" class="op-doc-link">Official Docs ↗</a></div></div><div id="NumPy_2" class="op-tab-pane "><h4>NumPy</h4><div class="op-detail-row"><span class="label">API:</span> <code>numpy.nanpercentile</code></div><div class="op-detail-row"><span class="label">Strategy:</span> <span>Direct Mapping</span></div><div class="op-detail-row"><a href="https://numpy.org/doc/stable/reference/generated/numpy.nanpercentile.html" target="_blank" class="op-doc-link">Official Docs ↗</a></div></div> 
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