# xarray.DataArray.interp_like

`DataArray.``interp_like`(other: Union[DataArray, xarray.core.dataset.Dataset], method: str = 'linear', assume_sorted: bool = False, kwargs: Mapping[str, Any] = None) → xarray.core.dataarray.DataArray

  Interpolate this object onto the coordinates of another object, filling out of range values with NaN.

  Parameters:

  - other (Dataset or DataArray) – Object with an ‘indexes’ attribute giving a mapping from dimension names to an 1d array-like, which provides coordinates upon which to index the variables in this dataset.
  - 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.

  Returns: | interpolated – Another dataarray by interpolating this dataarray’s data along the coordinates of the other object.
  Return type: | xr.DataArray

  Notes

  scipy is required. If the dataarray has object-type coordinates, reindex is used for these coordinates instead of the interpolation.

  See also

  `DataArray.interp()`, `DataArray.reindex_like()`