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Method quantile

xarray/core/dataarray.py:5311–5428  ·  view source on GitHub ↗

Compute the qth quantile of the data along the specified dimension. Returns the qth quantiles(s) of the array elements. Parameters ---------- q : float or array-like of float Quantile to compute, which must be between 0 and 1 inclusive. dim : str

(
        self,
        q: ArrayLike,
        dim: Dims = None,
        *,
        method: QuantileMethods = "linear",
        keep_attrs: bool | None = None,
        skipna: bool | None = None,
        interpolation: QuantileMethods | None = None,
    )

Source from the content-addressed store, hash-verified

5309 return self._from_temp_dataset(ds)
5310
5311 def quantile(
5312 self,
5313 q: ArrayLike,
5314 dim: Dims = None,
5315 *,
5316 method: QuantileMethods = "linear",
5317 keep_attrs: bool | None = None,
5318 skipna: bool | None = None,
5319 interpolation: QuantileMethods | None = None,
5320 ) -> Self:
5321 """Compute the qth quantile of the data along the specified dimension.
5322
5323 Returns the qth quantiles(s) of the array elements.
5324
5325 Parameters
5326 ----------
5327 q : float or array-like of float
5328 Quantile to compute, which must be between 0 and 1 inclusive.
5329 dim : str or Iterable of Hashable, optional
5330 Dimension(s) over which to apply quantile.
5331 method : str, default: "linear"
5332 This optional parameter specifies the interpolation method to use when the
5333 desired quantile lies between two data points. The options sorted by their R
5334 type as summarized in the H&F paper [1]_ are:
5335
5336 1. "inverted_cdf"
5337 2. "averaged_inverted_cdf"
5338 3. "closest_observation"
5339 4. "interpolated_inverted_cdf"
5340 5. "hazen"
5341 6. "weibull"
5342 7. "linear" (default)
5343 8. "median_unbiased"
5344 9. "normal_unbiased"
5345
5346 The first three methods are discontiuous. The following discontinuous
5347 variations of the default "linear" (7.) option are also available:
5348
5349 * "lower"
5350 * "higher"
5351 * "midpoint"
5352 * "nearest"
5353
5354 See :py:func:`numpy.quantile` or [1]_ for details. The "method" argument
5355 was previously called "interpolation", renamed in accordance with numpy
5356 version 1.22.0.
5357
5358 keep_attrs : bool or None, optional
5359 If True, the dataset's attributes (`attrs`) will be copied from
5360 the original object to the new one. If False (default), the new
5361 object will be returned without attributes.
5362 skipna : bool or None, optional
5363 If True, skip missing values (as marked by NaN). By default, only
5364 skips missing values for float dtypes; other dtypes either do not
5365 have a sentinel missing value (int) or skipna=True has not been
5366 implemented (object, datetime64 or timedelta64).
5367
5368 Returns

Calls 2

_to_temp_datasetMethod · 0.95
_from_temp_datasetMethod · 0.95