issue_comments: 591452330

This seems to happen because MultiIndex.from_product is being passed an index and a MultiIndex, and doesn't handle this well.

The pandas error isn't great but I think it's mostly on us)

```python

/home/mroos/.local/lib/python3.7/site-packages/xarray/core/coordinates.py(111)to_index() 109 indexes = [self._data.get_index(k) for k in ordered_dims] # type: ignore 110 names = list(ordered_dims) --> 111 return pd.MultiIndex.from_product(indexes, names=names) 112 113 def update(self, other: Mapping[Hashable, Any]) -> None:

ipdb> indexes [Index(['0', '1', '2', '3'], dtype='object', name='n'), MultiIndex([( 18671, '1995-03-31'), ( 18671, '1995-06-30'), ( 18671, '1995-09-30'), ( 18671, '1995-12-31'), ( 18671, '1996-03-31'), ( 18671, '1996-06-30'), ( 18671, '1996-09-30'), ( 18671, '1996-12-31'), ( 18671, '1997-03-31'), ( 18671, '1997-06-30'), ... (634127183, '2012-09-30'), (634127183, '2012-12-31'), (634127183, '2013-03-31'), (634127183, '2013-06-30'), (634127183, '2013-09-30'), (634127183, '2013-12-31'), (634127183, '2014-03-31'), (634127183, '2014-06-30'), (634127183, '2014-09-30'), (634127183, '2014-12-31')], names=['c', 'date'], length=201040)] ```

Here's the whole stack trace for reference:

```python

---

NotImplementedError Traceback (most recent call last) <ipython-input-698-952a54d66d1c> in <module> ----> 1 observations.assign_coords(n=['0','1','2','3']).to_dataframe()

~/.local/lib/python3.7/site-packages/xarray/core/dataset.py in to_dataframe(self) 4463 this dataset's indices. 4464 """ -> 4465 return self._to_dataframe(self.dims) 4466 4467 def _set_sparse_data_from_dataframe(

~/.local/lib/python3.7/site-packages/xarray/core/dataset.py in _to_dataframe(self, ordered_dims) 4453 for k in columns 4454 ] -> 4455 index = self.coords.to_index(ordered_dims) 4456 return pd.DataFrame(dict(zip(columns, data)), index=index) 4457

~/.local/lib/python3.7/site-packages/xarray/core/coordinates.py in to_index(self, ordered_dims) 109 indexes = [self._data.get_index(k) for k in ordered_dims] # type: ignore 110 names = list(ordered_dims) --> 111 return pd.MultiIndex.from_product(indexes, names=names) 112 113 def update(self, other: Mapping[Hashable, Any]) -> None:

/j/office/app/research-python/conda/envs/2019.10/lib/python3.7/site-packages/pandas/core/indexes/multi.py in from_product(cls, iterables, sortorder, names) 536 iterables = list(iterables) 537 --> 538 codes, levels = _factorize_from_iterables(iterables) 539 codes = cartesian_product(codes) 540 return MultiIndex(levels, codes, sortorder=sortorder, names=names)

/j/office/app/research-python/conda/envs/2019.10/lib/python3.7/site-packages/pandas/core/arrays/categorical.py in _factorize_from_iterables(iterables) 2814 # For consistency, it should return a list of 2 lists. 2815 return [[], []] -> 2816 return map(list, zip(*(_factorize_from_iterable(it) for it in iterables)))

/j/office/app/research-python/conda/envs/2019.10/lib/python3.7/site-packages/pandas/core/arrays/categorical.py in <genexpr>(.0) 2814 # For consistency, it should return a list of 2 lists. 2815 return [[], []] -> 2816 return map(list, zip(*(_factorize_from_iterable(it) for it in iterables)))

/j/office/app/research-python/conda/envs/2019.10/lib/python3.7/site-packages/pandas/core/arrays/categorical.py in _factorize_from_iterable(values) 2786 # but only the resulting categories, the order of which is independent 2787 # from ordered. Set ordered to False as default. See GH #15457 -> 2788 cat = Categorical(values, ordered=False) 2789 categories = cat.categories 2790 codes = cat.codes

/j/office/app/research-python/conda/envs/2019.10/lib/python3.7/site-packages/pandas/core/arrays/categorical.py in init(self, values, categories, ordered, dtype, fastpath) 401 402 # we're inferring from values --> 403 dtype = CategoricalDtype(categories, dtype._ordered) 404 405 elif is_categorical_dtype(values):

/j/office/app/research-python/conda/envs/2019.10/lib/python3.7/site-packages/pandas/core/dtypes/dtypes.py in init(self, categories, ordered) 224 225 def init(self, categories=None, ordered: OrderedType = ordered_sentinel): --> 226 self._finalize(categories, ordered, fastpath=False) 227 228 @classmethod

/j/office/app/research-python/conda/envs/2019.10/lib/python3.7/site-packages/pandas/core/dtypes/dtypes.py in _finalize(self, categories, ordered, fastpath) 345 346 if categories is not None: --> 347 categories = self.validate_categories(categories, fastpath=fastpath) 348 349 self._categories = categories

/j/office/app/research-python/conda/envs/2019.10/lib/python3.7/site-packages/pandas/core/dtypes/dtypes.py in validate_categories(categories, fastpath) 521 if not fastpath: 522 --> 523 if categories.hasnans: 524 raise ValueError("Categorial categories cannot be null") 525

pandas/_libs/properties.pyx in pandas._libs.properties.CachedProperty.get()

/j/office/app/research-python/conda/envs/2019.10/lib/python3.7/site-packages/pandas/core/indexes/base.py in hasnans(self) 1958 """ 1959 if self._can_hold_na: -> 1960 return bool(self._isnan.any()) 1961 else: 1962 return False

pandas/_libs/properties.pyx in pandas._libs.properties.CachedProperty.get()

/j/office/app/research-python/conda/envs/2019.10/lib/python3.7/site-packages/pandas/core/indexes/base.py in _isnan(self) 1937 """ 1938 if self._can_hold_na: -> 1939 return isna(self) 1940 else: 1941 # shouldn't reach to this condition by checking hasnans beforehand

/j/office/app/research-python/conda/envs/2019.10/lib/python3.7/site-packages/pandas/core/dtypes/missing.py in isna(obj) 120 Name: 1, dtype: bool 121 """ --> 122 return _isna(obj) 123 124

/j/office/app/research-python/conda/envs/2019.10/lib/python3.7/site-packages/pandas/core/dtypes/missing.py in _isna_new(obj) 131 # hack (for now) because MI registers as ndarray 132 elif isinstance(obj, ABCMultiIndex): --> 133 raise NotImplementedError("isna is not defined for MultiIndex") 134 elif isinstance(obj, type): 135 return False

NotImplementedError: isna is not defined for MultiIndex ```