xarray.Dataset.interpolate_na¶
-
Dataset.
interpolate_na
(dim: Hashable = None, method: str = 'linear', limit: int = None, use_coordinate: Union[bool, Hashable] = True, max_gap: Union[int, float, str, pandas._libs.tslibs.timedeltas.Timedelta, numpy.timedelta64] = None, **kwargs) → xarray.core.dataset.Dataset¶ Fill in NaNs by interpolating according to different methods.
Parameters: - dim (str) – Specifies the dimension along which to interpolate.
- method (str, optional) –
String indicating which method to use for interpolation:
- ’linear’: linear interpolation (Default). Additional keyword
arguments are passed to
numpy.interp()
- ’nearest’, ‘zero’, ‘slinear’, ‘quadratic’, ‘cubic’, ‘polynomial’:
are passed to
scipy.interpolate.interp1d()
. Ifmethod='polynomial'
, theorder
keyword argument must also be provided. - ’barycentric’, ‘krog’, ‘pchip’, ‘spline’, ‘akima’: use their
respective
scipy.interpolate
classes.
- ’linear’: linear interpolation (Default). Additional keyword
arguments are passed to
- use_coordinate (bool, str, default True) – Specifies which index to use as the x values in the interpolation
formulated as y = f(x). If False, values are treated as if
eqaully-spaced along
dim
. If True, the IndexVariable dim is used. Ifuse_coordinate
is a string, it specifies the name of a coordinate variariable to use as the index. - limit (int, default None) – Maximum number of consecutive NaNs to fill. Must be greater than 0
or None for no limit. This filling is done regardless of the size of
the gap in the data. To only interpolate over gaps less than a given length,
see
max_gap
. - max_gap (int, float, str, pandas.Timedelta, numpy.timedelta64, default None.) –
Maximum size of gap, a continuous sequence of NaNs, that will be filled. Use None for no limit. When interpolating along a datetime64 dimension and
use_coordinate=True
,max_gap
can be one of the following:- a string that is valid input for pandas.to_timedelta
- a
numpy.timedelta64
object - a
pandas.Timedelta
object
Otherwise,
max_gap
must be an int or a float. Use ofmax_gap
with unlabeled dimensions has not been implemented yet. Gap length is defined as the difference between coordinate values at the first data point after a gap and the last value before a gap. For gaps at the beginning (end), gap length is defined as the difference between coordinate values at the first (last) valid data point and the first (last) NaN. For example, consider:<xarray.DataArray (x: 9)> array([nan, nan, nan, 1., nan, nan, 4., nan, nan]) Coordinates: * x (x) int64 0 1 2 3 4 5 6 7 8
The gap lengths are 3-0 = 3; 6-3 = 3; and 8-6 = 2 respectively
- kwargs (dict, optional) – parameters passed verbatim to the underlying interpolation function
Returns: interpolated – Filled in Dataset.
Return type: See also
numpy.interp()
,scipy.interpolate()