xarray.DataTree.any (original) (raw)

DataTree.any(dim=None, *, keep_attrs=None, **kwargs)[source]#

Reduce this DataTree’s data by applying any along some dimension(s).

Parameters:

• dim (str, Iterable of Hashable, "..." or None, default: None) – Name of dimension[s] along which to apply any. For e.g. dim="x"or dim=["x", "y"]. If “…” or None, will reduce over all dimensions.
• keep_attrs (bool or None, optional) – If True, attrs will be copied from the original object to the new one. If False, the new object will be returned without attributes.
• **kwargs (Any) – Additional keyword arguments passed on to the appropriate array function for calculating any on this object’s data. These could include dask-specific kwargs like split_every.

Returns:

reduced (DataTree) – New DataTree with any applied to its data and the indicated dimension(s) removed

Examples

dt = xr.DataTree( ... xr.Dataset( ... data_vars=dict( ... foo=( ... "time", ... np.array([True, True, True, True, True, False], dtype=bool), ... ) ... ), ... coords=dict( ... time=( ... "time", ... pd.date_range("2001-01-01", freq="ME", periods=6), ... ), ... labels=("time", np.array(["a", "b", "c", "c", "b", "a"])), ... ), ... ), ... ) dt <xarray.DataTree> Group: / Dimensions: (time: 6) Coordinates: * time (time) datetime64[ns] 48B 2001-01-31 2001-02-28 ... 2001-06-30 labels (time) <U1 24B 'a' 'b' 'c' 'c' 'b' 'a' Data variables: foo (time) bool 6B True True True True True False

dt.any() <xarray.DataTree> Group: / Dimensions: () Data variables: foo bool 1B True