What happened?

Now that Scipy is moving to support sparse NDarrays, we would expect that Xarray should work with them as any other array like data.

What did you expect to happen?

Doesn't work. It seems that why trying to use a scipy sparse array as the data, Xarray wraps the the sparse array in a 0-D dense array. (there are likely more issues after this but this was the first hurdle)

With sparse array s: print(s) <4x4 sparse array of type '<class 'numpy.float64'>' with 4 stored elements in COOrdinate format> print(xr.DataArray(s).data) array(<4x4 sparse array of type '<class 'numpy.float64'>' with 4 stored elements in COOrdinate format>, dtype=object)

Minimal Complete Verifiable Example

```Python import numpy as np import xarray as xr from scipy.sparse import coo_array

row = np.array([0, 3, 1, 0])

col = np.array([0, 3, 1, 2])

data = np.array([4, 5.4, 7, 9.2])

s= coo_array((data, (row, col)), shape=(4, 4)) da = xr.DataArray(s) print(da.repr_html()) ```

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

AttributeError Traceback (most recent call last) Input In [4], in <cell line: 13>() 11 s= coo_array((data, (row, col)), shape=(4, 4)) 12 da = xr.DataArray(s) ---> 13 print(da.repr_html())

File ~/Scratch/.conda/envs/tessa-1/lib/python3.10/site-packages/xarray/core/common.py:167, in AbstractArray.repr_html(self) 165 if OPTIONS["display_style"] == "text": 166 return f"

{escape(repr(self))}

File ~/Scratch/.conda/envs/tessa-1/lib/python3.10/site-packages/xarray/core/formatting_html.py:311, in array_repr(arr) 303 arr_name = f"'{arr.name}'" if getattr(arr, "name", None) else "" 305 header_components = [ 306 f"

File ~/Scratch/.conda/envs/tessa-1/lib/python3.10/site-packages/xarray/core/formatting_html.py:219, in array_section(obj) 213 collapsed = ( 214 "checked" 215 if _get_boolean_with_default("display_expand_data", default=True) 216 else "" 217 ) 218 variable = getattr(obj, "variable", obj) --> 219 preview = escape(inline_variable_array_repr(variable, max_width=70)) 220 data_repr = short_data_repr_html(obj) 221 data_icon = _icon("icon-database")

File ~/Scratch/.conda/envs/tessa-1/lib/python3.10/site-packages/xarray/core/formatting.py:274, in inline_variable_array_repr(var, max_width) 272 return var.data._repr_inline(max_width) 273 if var._in_memory: --> 274 return format_array_flat(var, max_width) 275 dask_array_type = array_type("dask") 276 if isinstance(var._data, dask_array_type):

File ~/Scratch/.conda/envs/tessa-1/lib/python3.10/site-packages/xarray/core/formatting.py:191, in format_array_flat(array, max_width) 188 # every item will take up at least two characters, but we always want to 189 # print at least first and last items 190 max_possibly_relevant = min(max(array.size, 1), max(math.ceil(max_width / 2.0), 2)) --> 191 relevant_front_items = format_items( 192 first_n_items(array, (max_possibly_relevant + 1) // 2) 193 ) 194 relevant_back_items = format_items(last_n_items(array, max_possibly_relevant // 2)) 195 # interleave relevant front and back items: 196 # [a, b, c] and [y, z] -> [a, z, b, y, c]

File ~/Scratch/.conda/envs/tessa-1/lib/python3.10/site-packages/xarray/core/formatting.py:180, in format_items(x) 177 elif np.logical_not(time_needed).all(): 178 timedelta_format = "date" --> 180 formatted = [format_item(xi, timedelta_format) for xi in x] 181 return formatted

File ~/Scratch/.conda/envs/tessa-1/lib/python3.10/site-packages/xarray/core/formatting.py:180, in <listcomp>(.0) 177 elif np.logical_not(time_needed).all(): 178 timedelta_format = "date" --> 180 formatted = [format_item(xi, timedelta_format) for xi in x] 181 return formatted

File ~/Scratch/.conda/envs/tessa-1/lib/python3.10/site-packages/xarray/core/formatting.py:161, in format_item(x, timedelta_format, quote_strings) 159 return repr(x) if quote_strings else x 160 elif hasattr(x, "dtype") and np.issubdtype(x.dtype, np.floating): --> 161 return f"{x.item():.4}" 162 else: 163 return str(x)

File ~/Scratch/.conda/envs/tessa-1/lib/python3.10/site-packages/scipy/sparse/_base.py:771, in spmatrix.getattr(self, attr) 769 return self.getnnz() 770 else: --> 771 raise AttributeError(attr + " not found")

AttributeError: item not found ```

Anything else we need to know?

No response

Environment

The to_dataframe method fails with ValueError if the dataarray has only value

MCVE Code Sample

```python

Your code here

x = np.arange(10) y = np.arange(10)

data = np.zeros((len(x), len(y)))

da = xr.DataArray(data, coords=[x, y], dims=['x', 'y'])

da.sel(x=1,y=1).to_dataframe(name='test') ```

Expected Output

Expect a dataframe with one row

Problem Description

This happened when selecting a single value out of a gridded dataset - in cases where there was only one value output the to_dataframe failed.

Output of xr.show_versions()

CF conventions code supports: {'microseconds': 'us', 'milliseconds': 'ms', 'seconds': 's', 'minutes': 'm', 'hours': 'h', 'days': 'D'}, but not 'years'. See example file https://www.dropbox.com/s/34dcpliko928yaj/histsoc_population_0.5deg_1861-2005.nc4?dl=0