• Rely on array backend for string formatting instead of forcing to numpy arrays. The previous implementation used .values to force to numpy arrays which doesn't work for sparse arrays and might be scary in the case of large dask arrays.

• Only allow format_spec when dealing with scalar arrays, shape=(). Using f-strings is a common method to print the repr. If we want to have full support of .__format__ we should probably add format_spec as input to formatting.array_repr.

• [x] Closes #6822

• [x] Tests added
• [x] User visible changes (including notable bug fixes) are documented in whats-new.rst

```python import pandas as pd import xarray as xr

s = pd.Series( range(4), index=pd.MultiIndex.from_product([list("ab"), list("cd")]), )

da = xr.DataArray.from_series(s, sparse=True)

Handle sparse:

print(f"Error: {da} is sparse") Error: <xarray.DataArray (level_0: 2, level_1: 2)> <COO: shape=(2, 2), dtype=float64, nnz=4, fill_value=nan> Coordinates: * level_0 (level_0) object 'a' 'b' * level_1 (level_1) object 'c' 'd' is sparse

Handle format_spec:

da = xr.DataArray([1, 2, 3])

print(f'{da[0]}') <xarray.DataArray ()> array(1)

print(f'{da[0]:d}') 1

print(f'{da[0]:f}') 1.000000

da = xr.DataArray([1, 2, 3]) print(f'{da:.f}') Traceback (most recent call last): (...) NotImplementedError: Using format_spec is only supported when shape is (). Got shape = (3,). ```