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- DataArray.dropna(dim, *, how='any', thresh=None)[source]#
Returns a new array with dropped labels for missing values alongthe provided dimension.
- Parameters:
dim (
Hashable) – Dimension along which to drop missing values. Dropping alongmultiple dimensions simultaneously is not yet supported.how (
{"any", "all"}, default:"any") –any : if any NA values are present, drop that label
all : if all values are NA, drop that label
thresh (
intorNone, default:None) – If supplied, require this many non-NA values.
- Returns:
dropped (
DataArray)
Examples
>>> temperature = [... [0, 4, 2, 9],... [np.nan, np.nan, np.nan, np.nan],... [np.nan, 4, 2, 0],... [3, 1, 0, 0],... ]>>> da = xr.DataArray(... data=temperature,... dims=["Y", "X"],... coords=dict(... lat=("Y", np.array([-20.0, -20.25, -20.50, -20.75])),... lon=("X", np.array([10.0, 10.25, 10.5, 10.75])),... ),... )>>> da<xarray.DataArray (Y: 4, X: 4)> Size: 128Barray([[ 0., 4., 2., 9.], [nan, nan, nan, nan], [nan, 4., 2., 0.], [ 3., 1., 0., 0.]])Coordinates: lat (Y) float64 32B -20.0 -20.25 -20.5 -20.75 lon (X) float64 32B 10.0 10.25 10.5 10.75Dimensions without coordinates: Y, X
>>> da.dropna(dim="Y", how="any")<xarray.DataArray (Y: 2, X: 4)> Size: 64Barray([[0., 4., 2., 9.], [3., 1., 0., 0.]])Coordinates: lat (Y) float64 16B -20.0 -20.75 lon (X) float64 32B 10.0 10.25 10.5 10.75Dimensions without coordinates: Y, X
Drop values only if all values along the dimension are NaN:
>>> da.dropna(dim="Y", how="all")<xarray.DataArray (Y: 3, X: 4)> Size: 96Barray([[ 0., 4., 2., 9.], [nan, 4., 2., 0.], [ 3., 1., 0., 0.]])Coordinates: lat (Y) float64 24B -20.0 -20.5 -20.75 lon (X) float64 32B 10.0 10.25 10.5 10.75Dimensions without coordinates: Y, X
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