mito_genes and ValueError Traceback (most recent call last)

mito_genes = adata.var_names.str.startswith('MT-')
adata.obs['percent_mito'] = np.sum(adata[:, mito_genes].X, axis=1).A1 / np.sum(adata.X, axis=1).A1
adata.obs['n_counts'] = adata.X.sum(axis=1).A1
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-31-4b64d0e9fd7f> in <module>
      2 # for each cell compute fraction of counts in mito genes vs. all genes
      3 # the `.A1` is only necessary as X is sparse (to transform to a dense array after summing)
----> 4 adata.obs['percent_mito'] = np.sum(adata[:, mito_genes].X, axis=1).A1 / np.sum(adata.X, axis=1).A1
      5 # add the total counts per cell as observations-annotation to adata
      6 adata.obs['n_counts'] = adata.X.sum(axis=1).A1

c:\users\gsy\miniconda3\second\lib\site-packages\anndata\base.py in __getitem__(self, index)
   1297     def __getitem__(self, index: Index) -> 'AnnData':
   1298         """Returns a sliced view of the object."""
-> 1299         return self._getitem_view(index)
   1300 
   1301     def _getitem_view(self, index: Index) -> 'AnnData':

c:\users\gsy\miniconda3\second\lib\site-packages\anndata\base.py in _getitem_view(self, index)
   1300 
   1301     def _getitem_view(self, index: Index) -> 'AnnData':
-> 1302         oidx, vidx = self._normalize_indices(index)
   1303         return AnnData(self, oidx=oidx, vidx=vidx, asview=True)
   1304 

c:\users\gsy\miniconda3\second\lib\site-packages\anndata\base.py in _normalize_indices(self, index)
   1277         obs, var = super()._unpack_index(index)
   1278         obs = _normalize_index(obs, self.obs_names)
-> 1279         var = _normalize_index(var, self.var_names)
   1280         return obs, var
   1281 

c:\users\gsy\miniconda3\second\lib\site-packages\anndata\base.py in _normalize_index(index, names)
    264         # incredibly faster one
    265         positions = pd.Series(index=names, data=range(len(names)))
--> 266         positions = positions[index]
    267         if positions.isnull().values.any():
    268             raise KeyError(

c:\users\gsy\miniconda3\second\lib\site-packages\pandas\core\series.py in __getitem__(self, key)
    906             key = list(key)
    907 
--> 908         if com.is_bool_indexer(key):
    909             key = check_bool_indexer(self.index, key)
    910 

c:\users\gsy\miniconda3\second\lib\site-packages\pandas\core\common.py in is_bool_indexer(key)
    122             if not lib.is_bool_array(key):
    123                 if isna(key).any():
--> 124                     raise ValueError(na_msg)
    125                 return False
    126             return True

ValueError: cannot index with vector containing NA / NaN values

Reproduce the notebook expression shown in the report and start at anndata/base.py in _normalize_indices and _normalize_index, where the traceback reaches pandas Series indexing. Check the reported boolean mask and its variable names for the source of the failure; done should include a confirmed cause and a regression test or documented resolution, though the issue does not specify the expected behavior.