html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue https://github.com/pydata/xarray/issues/3445#issuecomment-551386159,https://api.github.com/repos/pydata/xarray/issues/3445,551386159,MDEyOklzc3VlQ29tbWVudDU1MTM4NjE1OQ==,1217238,2019-11-08T05:05:01Z,2019-11-08T05:05:01Z,MEMBER,"The missing operation here in sparse is indexing like `x[y, z]` where `y` and `z` are both arrays. For reference, here's the traceback: ``` --------------------------------------------------------------------------- IndexError Traceback (most recent call last) in () 17 'time':time}).to_dataset() 18 ---> 19 dataset1 = xr.merge([data_array1,data_array2]) 9 frames /usr/local/lib/python3.6/dist-packages/xarray/core/merge.py in merge(objects, compat, join, fill_value) 780 dict_like_objects.append(obj) 781 --> 782 merge_result = merge_core(dict_like_objects, compat, join, fill_value=fill_value) 783 merged = Dataset._construct_direct(**merge_result._asdict()) 784 return merged /usr/local/lib/python3.6/dist-packages/xarray/core/merge.py in merge_core(objects, compat, join, priority_arg, explicit_coords, indexes, fill_value) 537 coerced = coerce_pandas_values(objects) 538 aligned = deep_align( --> 539 coerced, join=join, copy=False, indexes=indexes, fill_value=fill_value 540 ) 541 collected = collect_variables_and_indexes(aligned) /usr/local/lib/python3.6/dist-packages/xarray/core/alignment.py in deep_align(objects, join, copy, indexes, exclude, raise_on_invalid, fill_value) 403 indexes=indexes, 404 exclude=exclude, --> 405 fill_value=fill_value 406 ) 407 /usr/local/lib/python3.6/dist-packages/xarray/core/alignment.py in align(join, copy, indexes, exclude, fill_value, *objects) 331 new_obj = obj.copy(deep=copy) 332 else: --> 333 new_obj = obj.reindex(copy=copy, fill_value=fill_value, **valid_indexers) 334 new_obj.encoding = obj.encoding 335 result.append(new_obj) /usr/local/lib/python3.6/dist-packages/xarray/core/dataset.py in reindex(self, indexers, method, tolerance, copy, fill_value, **indexers_kwargs) 2430 tolerance, 2431 copy=copy, -> 2432 fill_value=fill_value, 2433 ) 2434 coord_names = set(self._coord_names) /usr/local/lib/python3.6/dist-packages/xarray/core/alignment.py in reindex_variables(variables, sizes, indexes, indexers, method, tolerance, copy, fill_value) 581 582 if needs_masking: --> 583 new_var = var._getitem_with_mask(key, fill_value=fill_value) 584 elif all(is_full_slice(k) for k in key): 585 # no reindexing necessary /usr/local/lib/python3.6/dist-packages/xarray/core/variable.py in _getitem_with_mask(self, key, fill_value) 724 actual_indexer = indexer 725 --> 726 data = as_indexable(self._data)[actual_indexer] 727 mask = indexing.create_mask(indexer, self.shape, data) 728 data = duck_array_ops.where(mask, fill_value, data) /usr/local/lib/python3.6/dist-packages/xarray/core/indexing.py in __getitem__(self, key) 1260 def __getitem__(self, key): 1261 array, key = self._indexing_array_and_key(key) -> 1262 return array[key] 1263 1264 def __setitem__(self, key, value): /usr/local/lib/python3.6/dist-packages/sparse/_coo/indexing.py in getitem(x, index) 66 67 # Get the mask ---> 68 mask, adv_idx = _mask(x.coords, index, x.shape) 69 70 # Get the length of the mask /usr/local/lib/python3.6/dist-packages/sparse/_coo/indexing.py in _mask(coords, indices, shape) 129 if len(adv_idx) != 0: 130 if len(adv_idx) != 1: --> 131 raise IndexError('Only indices with at most one iterable index are supported.') 132 133 adv_idx = adv_idx[0] IndexError: Only indices with at most one iterable index are supported. ```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,512205079 https://github.com/pydata/xarray/issues/3445#issuecomment-551359502,https://api.github.com/repos/pydata/xarray/issues/3445,551359502,MDEyOklzc3VlQ29tbWVudDU1MTM1OTUwMg==,10554254,2019-11-08T02:41:13Z,2019-11-08T02:41:13Z,NONE,"@El-minadero from the [sparse API](https://sparse.pydata.org/en/latest/generated/sparse.html) page I'm seeing two methods for combining data: ```python import sparse import numpy as np A = sparse.COO.from_numpy(np.array([[1, 2], [3, 4]])) B = sparse.COO.from_numpy(np.array([[5, 9], [6, 8]])) sparse.stack([A,B]).todense() Out[1]: array([[[1, 2], [3, 4]], [[5, 9], [6, 8]]]) sparse.concatenate([A,B]).todense() Out[2]: array([[1, 2], [3, 4], [5, 9], [6, 8]]) ``` Since this is an issue with `sparse` and merging data doesn't seem to be supported at this time, you might consider closing this issue out here and raising it over at [sparse](https://github.com/pydata/sparse/issues). ","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,512205079 https://github.com/pydata/xarray/issues/3445#issuecomment-550516745,https://api.github.com/repos/pydata/xarray/issues/3445,550516745,MDEyOklzc3VlQ29tbWVudDU1MDUxNjc0NQ==,10554254,2019-11-06T21:51:31Z,2019-11-06T21:51:31Z,NONE,"Note that `dataset1 = xr.concat([data_array1,data_array2],dim='source')` or `dim='receiver'` seem to work, however, concat also fails if `time` is specified as the dimension.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,512205079