ffill
- UnitsAwareDataArray.ffill(dim: Hashable, limit: int | None = None) Self
Fill NaN values by propagating values forward
Requires bottleneck.
- Parameters:
dim (Hashable) – Specifies the dimension along which to propagate values when filling.
limit (int or None, default: None) – The maximum number of consecutive NaN values to forward 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
- Return type:
DataArray
Examples
>>> temperature = np.array( ... [ ... [np.nan, 1, 3], ... [0, np.nan, 5], ... [5, np.nan, np.nan], ... [3, np.nan, np.nan], ... [0, 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([[nan, 1., 3.], [ 0., nan, 5.], [ 5., nan, nan], [ 3., nan, nan], [ 0., 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.ffill(dim="Y", limit=None) <xarray.DataArray (Y: 5, X: 3)> Size: 120B array([[nan, 1., 3.], [ 0., 1., 5.], [ 5., 1., 5.], [ 3., 1., 5.], [ 0., 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.ffill(dim="Y", limit=1) <xarray.DataArray (Y: 5, X: 3)> Size: 120B array([[nan, 1., 3.], [ 0., 1., 5.], [ 5., nan, 5.], [ 3., nan, nan], [ 0., 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