What happened?

On upgrading from xarray 2022.3.0 to 2022.6.0, f-string formatting of sparse-backed DataArray raises an exception.

What did you expect to happen?

• Code does not error, or
• A breaking change is listed in the “Breaking changes” section of the docs.

Minimal Complete Verifiable Example

```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)

print(f"{da}") ```

MVCE confirmation

• [X] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
• [X] Complete example — the example is self-contained, including all data and the text of any traceback.
• [X] Verifiable example — the example copy & pastes into an IPython prompt or Binder notebook, returning the result.
• [X] New issue — a search of GitHub Issues suggests this is not a duplicate.

Relevant log output

```Python

xarray 2022.3.0:

<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'

xarray 2022.6.0:

Traceback (most recent call last):
File "/home/khaeru/bug.py", line 11, in <module> print(f"{da}") File "/home/khaeru/.local/lib/python3.10/site-packages/xarray/core/common.py", line 168, in format
return self.values.format(format_spec) File "/home/khaeru/.local/lib/python3.10/site-packages/xarray/core/dataarray.py", line 685, in values
return self.variable.values File "/home/khaeru/.local/lib/python3.10/site-packages/xarray/core/variable.py", line 527, in values
return _as_array_or_item(self._data) File "/home/khaeru/.local/lib/python3.10/site-packages/xarray/core/variable.py", line 267, in _as_array_or_item
data = np.asarray(data) File "/home/khaeru/.local/lib/python3.10/site-packages/sparse/_sparse_array.py", line 229, in array
raise RuntimeError( RuntimeError: Cannot convert a sparse array to dense automatically. To manually densify, use the todense method. ```

Anything else we need to know?

Along with the versions below, I have confirmed the error occurs with both sparse 0.12 and sparse 0.13.

Environment

With xarray 0.7.2, following this basic example from the docs, but with a modification in the last line to use pd.Period instead of pd.Timestamp:

``` python import numpy as np import xarray as xr

temp = 15 + 8 * np.random.randn(2, 2, 3) precip = 10 * np.random.rand(2, 2, 3) lon = [[-99.83, -99.32], [-99.79, -99.23]] lat = [[42.25, 42.21], [42.63, 42.59]]

ds = xr.Dataset({'temperature': (['x', 'y', 'time'], temp), 'precipitation': (['x', 'y', 'time'], precip)}, coords={'lon': (['x', 'y'], lon), 'lat': (['x', 'y'], lat), 'time': pd.date_range('2014-09-06', periods=3), 'reference_time': pd.Period('2014')}) ```

This raises:

ValueError: dimensions ('reference_time',) must have the same length as the number of data dimensions, ndim=0

I noticed (#645) that there are other issues stemming from pandas' PeriodIndex & company, so if this is not a straightforward fix I will understand!

I am working on some code that creates xray.Datasets with a 'bool' dtype.

Trying to call Dataset.to_netcdf() on this code causes _nc4_values_and_dtype() to raise a ValueError, so I added these few lines to force the storage of these variables as 1-byte integers.

Perhaps it should be 'u1' instead; I can change that if need be.