xarray.DataArray.bfill#

DataArray.bfill(dim, limit=None)[source] #

Fill NaN values by propagating values backward

Requires bottleneck.

Parameters:

• dim (str) – Specifies the dimension along which to propagate values when filling.

• limit (int or None, default: None) – The maximum number of consecutive NaN values to backward fill. In other words, if there is a gap with more than this number of consecutive NaNs, it will only be partially filled. Must be greater than 0 or None for no limit. Must be None or greater than or equal to axis length if filling along chunked axes (dimensions).

Returns:

filled (DataArray)

Examples

>>> temperature = np.array(
...  [
...  [0, 1, 3],
...  [0, np.nan, 5],
...  [5, np.nan, np.nan],
...  [3, np.nan, np.nan],
...  [np.nan, 2, 0],
...  ]
... )
>>> da = xr.DataArray(
...  data=temperature,
...  dims=["Y", "X"],
...  coords=dict(
...  lat=("Y", np.array([-20.0, -20.25, -20.50, -20.75, -21.0])),
...  lon=("X", np.array([10.0, 10.25, 10.5])),
...  ),
... )
>>> da
<xarray.DataArray (Y: 5, X: 3)> Size: 120B
array([[ 0., 1., 3.],
 [ 0., nan, 5.],
 [ 5., nan, nan],
 [ 3., nan, nan],
 [nan, 2., 0.]])
Coordinates:
 lat (Y) float64 40B -20.0 -20.25 -20.5 -20.75 -21.0
 lon (X) float64 24B 10.0 10.25 10.5
Dimensions without coordinates: Y, X

Fill all NaN values:

>>> da.bfill(dim="Y", limit=None)
<xarray.DataArray (Y: 5, X: 3)> Size: 120B
array([[ 0., 1., 3.],
 [ 0., 2., 5.],
 [ 5., 2., 0.],
 [ 3., 2., 0.],
 [nan, 2., 0.]])
Coordinates:
 lat (Y) float64 40B -20.0 -20.25 -20.5 -20.75 -21.0
 lon (X) float64 24B 10.0 10.25 10.5
Dimensions without coordinates: Y, X

Fill only the first of consecutive NaN values:

>>> da.bfill(dim="Y", limit=1)
<xarray.DataArray (Y: 5, X: 3)> Size: 120B
array([[ 0., 1., 3.],
 [ 0., nan, 5.],
 [ 5., nan, nan],
 [ 3., 2., 0.],
 [nan, 2., 0.]])
Coordinates:
 lat (Y) float64 40B -20.0 -20.25 -20.5 -20.75 -21.0
 lon (X) float64 24B 10.0 10.25 10.5
Dimensions without coordinates: Y, X

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