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datatree.DataTree.fillna

DataTree.fillna(value: Any) → Self

Fill missing values in this object.

This operation follows the normal broadcasting and alignment rules that xarray uses for binary arithmetic, except the result is aligned to this object (join='left') instead of aligned to the intersection of index coordinates (join='inner').

Parameters:

value (scalar, ndarray, DataArray, dict or Dataset) – Used to fill all matching missing values in this dataset’s data variables. Scalars, ndarrays or DataArrays arguments are used to fill all data with aligned coordinates (for DataArrays). Dictionaries or datasets match data variables and then align coordinates if necessary.

Returns:

Dataset

Examples

>>> ds = xr.Dataset(
...     {
...         "A": ("x", [np.nan, 2, np.nan, 0]),
...         "B": ("x", [3, 4, np.nan, 1]),
...         "C": ("x", [np.nan, np.nan, np.nan, 5]),
...         "D": ("x", [np.nan, 3, np.nan, 4]),
...     },
...     coords={"x": [0, 1, 2, 3]},
... )
>>> ds
<xarray.Dataset> Size: 160B
Dimensions:  (x: 4)
Coordinates:
  * x        (x) int64 32B 0 1 2 3
Data variables:
    A        (x) float64 32B nan 2.0 nan 0.0
    B        (x) float64 32B 3.0 4.0 nan 1.0
    C        (x) float64 32B nan nan nan 5.0
    D        (x) float64 32B nan 3.0 nan 4.0

Replace all NaN values with 0s.

>>> ds.fillna(0)
<xarray.Dataset> Size: 160B
Dimensions:  (x: 4)
Coordinates:
  * x        (x) int64 32B 0 1 2 3
Data variables:
    A        (x) float64 32B 0.0 2.0 0.0 0.0
    B        (x) float64 32B 3.0 4.0 0.0 1.0
    C        (x) float64 32B 0.0 0.0 0.0 5.0
    D        (x) float64 32B 0.0 3.0 0.0 4.0

Replace all NaN elements in column ‘A’, ‘B’, ‘C’, and ‘D’, with 0, 1, 2, and 3 respectively.

>>> values = {"A": 0, "B": 1, "C": 2, "D": 3}
>>> ds.fillna(value=values)
<xarray.Dataset> Size: 160B
Dimensions:  (x: 4)
Coordinates:
  * x        (x) int64 32B 0 1 2 3
Data variables:
    A        (x) float64 32B 0.0 2.0 0.0 0.0
    B        (x) float64 32B 3.0 4.0 1.0 1.0
    C        (x) float64 32B 2.0 2.0 2.0 5.0
    D        (x) float64 32B 3.0 3.0 3.0 4.0