Dataset.interp(self, coords: Mapping[Hashable, Any] = None, method: str = 'linear', assume_sorted: bool = False, kwargs: Mapping[str, Any] = None, **coords_kwargs: Any) → 'Dataset'

Multidimensional interpolation of Dataset.

  • coords (dict, optional) – Mapping from dimension names to the new coordinates. New coordinate can be a scalar, array-like or DataArray. If DataArrays are passed as new coordates, their dimensions are used for the broadcasting.

  • method (string, optional.) – {‘linear’, ‘nearest’} for multidimensional array, {‘linear’, ‘nearest’, ‘zero’, ‘slinear’, ‘quadratic’, ‘cubic’} for 1-dimensional array. ‘linear’ is used by default.

  • assume_sorted (boolean, optional) – If False, values of coordinates that are interpolated over can be in any order and they are sorted first. If True, interpolated coordinates are assumed to be an array of monotonically increasing values.

  • kwargs (dictionary, optional) – Additional keyword passed to scipy’s interpolator.

  • **coords_kwarg ({dim: coordinate, ..}, optional) – The keyword arguments form of coords. One of coords or coords_kwargs must be provided.


interpolated – New dataset on the new coordinates.

Return type



scipy is required.

See also

scipy.interpolate.interp1d(), scipy.interpolate.interpn()