xarray.DataArray.drop_duplicates#
- DataArray.drop_duplicates(dim, *, keep='first')[source]#
Returns a new DataArray with duplicate dimension values removed.
- Parameters:
dim (
dimension label
orlabels
) – Pass … to drop duplicates along all dimensions.keep (
{"first", "last", False}
, default:"first"
) – Determines which duplicates (if any) to keep."first"
: Drop duplicates except for the first occurrence."last"
: Drop duplicates except for the last occurrence.False : Drop all duplicates.
- Returns:
See also
Examples
>>> da = xr.DataArray( ... np.arange(25).reshape(5, 5), ... dims=("x", "y"), ... coords={"x": np.array([0, 0, 1, 2, 3]), "y": np.array([0, 1, 2, 3, 3])}, ... ) >>> da <xarray.DataArray (x: 5, y: 5)> Size: 200B array([[ 0, 1, 2, 3, 4], [ 5, 6, 7, 8, 9], [10, 11, 12, 13, 14], [15, 16, 17, 18, 19], [20, 21, 22, 23, 24]]) Coordinates: * x (x) int64 40B 0 0 1 2 3 * y (y) int64 40B 0 1 2 3 3
>>> da.drop_duplicates(dim="x") <xarray.DataArray (x: 4, y: 5)> Size: 160B array([[ 0, 1, 2, 3, 4], [10, 11, 12, 13, 14], [15, 16, 17, 18, 19], [20, 21, 22, 23, 24]]) Coordinates: * x (x) int64 32B 0 1 2 3 * y (y) int64 40B 0 1 2 3 3
>>> da.drop_duplicates(dim="x", keep="last") <xarray.DataArray (x: 4, y: 5)> Size: 160B array([[ 5, 6, 7, 8, 9], [10, 11, 12, 13, 14], [15, 16, 17, 18, 19], [20, 21, 22, 23, 24]]) Coordinates: * x (x) int64 32B 0 1 2 3 * y (y) int64 40B 0 1 2 3 3
Drop all duplicate dimension values:
>>> da.drop_duplicates(dim=...) <xarray.DataArray (x: 4, y: 4)> Size: 128B array([[ 0, 1, 2, 3], [10, 11, 12, 13], [15, 16, 17, 18], [20, 21, 22, 23]]) Coordinates: * x (x) int64 32B 0 1 2 3 * y (y) int64 32B 0 1 2 3