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  • Indexing not properly working with object dtype element ? · 4 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
795639606 https://github.com/pydata/xarray/issues/2414#issuecomment-795639606 https://api.github.com/repos/pydata/xarray/issues/2414 MDEyOklzc3VlQ29tbWVudDc5NTYzOTYwNg== keewis 14808389 2021-03-10T15:51:47Z 2021-03-10T15:58:18Z MEMBER

~I agree, this has either been fixed a long time ago (before we removed the references to pandas.Panel) or by a dependency (numpy, most likely, but the fix is included in the env generated by bare-minimum)~ #2625 was the fix.

We still want a test like the one suggested in #2415 to make sure we don't regress, though.

 
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   Indexing not properly working with object dtype element ? 359679690
792294554 https://github.com/pydata/xarray/issues/2414#issuecomment-792294554 https://api.github.com/repos/pydata/xarray/issues/2414 MDEyOklzc3VlQ29tbWVudDc5MjI5NDU1NA== andersy005 13301940 2021-03-07T15:13:34Z 2021-03-07T15:13:34Z MEMBER

Unless I am missing something, this appears to have been addressed:

```python In [1]: import xarray as xr import numpy as np

In [2]: import numpy as np

In [3]: er = xr.DataArray(np.array((np.arange(3), np.arange(6)))) <ipython-input-3-64075f0108e0>:3: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray. er = xr.DataArray(np.array((np.arange(3), np.arange(6))))

In [4]: er Out[4]: <xarray.DataArray (dim_0: 2)> array([array([0, 1, 2]), array([0, 1, 2, 3, 4, 5])], dtype=object) Dimensions without coordinates: dim_0 ```

```python In [6]: er.data[0] Out[6]: array([0, 1, 2])

In [7]: er[0] Out[7]: <xarray.DataArray ()> array(array([0, 1, 2]), dtype=object)

In [8]: er[1] Out[8]: <xarray.DataArray ()> array(array([0, 1, 2, 3, 4, 5]), dtype=object)

In [9]: xr.version Out[9]: '0.17.0'

In [10]: np.version Out[10]: '1.20.1' ```

 
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   Indexing not properly working with object dtype element ? 359679690
674340541 https://github.com/pydata/xarray/issues/2414#issuecomment-674340541 https://api.github.com/repos/pydata/xarray/issues/2414 MDEyOklzc3VlQ29tbWVudDY3NDM0MDU0MQ== stale[bot] 26384082 2020-08-15T03:15:51Z 2020-08-15T03:15:51Z NONE

In order to maintain a list of currently relevant issues, we mark issues as stale after a period of inactivity

If this issue remains relevant, please comment here or remove the stale label; otherwise it will be marked as closed automatically

 
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   Indexing not properly working with object dtype element ? 359679690
420827114 https://github.com/pydata/xarray/issues/2414#issuecomment-420827114 https://api.github.com/repos/pydata/xarray/issues/2414 MDEyOklzc3VlQ29tbWVudDQyMDgyNzExNA== shoyer 1217238 2018-09-12T23:05:11Z 2018-09-12T23:05:11Z MEMBER

For reference, here is the error/traceback with xarray 0.10.8:

```python-traceback --------------------------------------------------------------------------- ValueError Traceback (most recent call last) <ipython-input-2-a722ff347d1b> in <module>() 3 er = xr.DataArray(np.array((np.arange(3), np.arange(6)))) # dtype=object because two different vector size 4 print(er.data[0]) # Does work ----> 5 print(er[0]) # Does not work (ValueError) /usr/local/lib/python3.6/dist-packages/xarray/core/dataarray.py in __getitem__(self, key) 472 else: 473 # xarray-style array indexing --> 474 return self.isel(indexers=self._item_key_to_dict(key)) 475 476 def __setitem__(self, key, value): /usr/local/lib/python3.6/dist-packages/xarray/core/dataarray.py in isel(self, indexers, drop, **indexers_kwargs) 754 """ 755 indexers = either_dict_or_kwargs(indexers, indexers_kwargs, 'isel') --> 756 ds = self._to_temp_dataset().isel(drop=drop, indexers=indexers) 757 return self._from_temp_dataset(ds) 758 /usr/local/lib/python3.6/dist-packages/xarray/core/dataset.py in isel(self, indexers, drop, **indexers_kwargs) 1425 for name, var in iteritems(self._variables): 1426 var_indexers = {k: v for k, v in indexers_list if k in var.dims} -> 1427 new_var = var.isel(indexers=var_indexers) 1428 if not (drop and name in var_indexers): 1429 variables[name] = new_var /usr/local/lib/python3.6/dist-packages/xarray/core/variable.py in isel(self, indexers, drop, **indexers_kwargs) 852 if dim in indexers: 853 key[i] = indexers[dim] --> 854 return self[tuple(key)] 855 856 def squeeze(self, dim=None): /usr/local/lib/python3.6/dist-packages/xarray/core/variable.py in __getitem__(self, key) 622 if new_order: 623 data = np.moveaxis(data, range(len(new_order)), new_order) --> 624 return self._finalize_indexing_result(dims, data) 625 626 def _finalize_indexing_result(self, dims, data): /usr/local/lib/python3.6/dist-packages/xarray/core/variable.py in _finalize_indexing_result(self, dims, data) 628 """ 629 return type(self)(dims, data, self._attrs, self._encoding, --> 630 fastpath=True) 631 632 def _getitem_with_mask(self, key, fill_value=dtypes.NA): /usr/local/lib/python3.6/dist-packages/xarray/core/variable.py in __init__(self, dims, data, attrs, encoding, fastpath) 261 """ 262 self._data = as_compatible_data(data, fastpath=fastpath) --> 263 self._dims = self._parse_dimensions(dims) 264 self._attrs = None 265 self._encoding = None /usr/local/lib/python3.6/dist-packages/xarray/core/variable.py in _parse_dimensions(self, dims) 422 raise ValueError('dimensions %s must have the same length as the ' 423 'number of data dimensions, ndim=%s' --> 424 % (dims, self.ndim)) 425 return dims 426 ValueError: dimensions () must have the same length as the number of data dimensions, ndim=1 ```

The bottom line issue is that indexing the 1D object array returns a scalar value: ```

er.data array([array([0, 1, 2]), array([0, 1, 2, 3, 4, 5])], dtype=object) er.data[0] array([0, 1, 2]) ``` In this case, the scalar value is another 1D array, which in turn triggers the error about inconsistent dimensions.

I agree that this is a bug. We actually currently have some logic to fix another manifestation of this issue: https://github.com/pydata/xarray/blob/4de8dbc3b1de461c0c9d3b002e55d60b46d2e6d2/xarray/core/indexing.py#L1145-L1175

This seems to be the wrong check. Instead of checking not isinstance(value, np.ndarray), we should be checking to see if the array has object dtype and the indexing operation would result in a scalar (which I think can only happen if the unwrapped key is a tuple of integers).

Any interest in putting together a pull request? :)

 
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   Indexing not properly working with object dtype element ? 359679690

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