As of xarray-0.10-rc1:

Works: ``` import xarray import scipy.stats a = xarray.DataArray([1,2], dims=['x'])

xarray.apply_ufunc(scipy.stats.norm.cdf, a, 0, 1)

<xarray.DataArray (x: 2)> array([ 0.841345, 0.97725 ]) Dimensions without coordinates: x ```

Broken: ``` xarray.apply_ufunc( scipy.stats.norm.cdf, a.chunk(), 0, 1, dask='parallelized', output_dtypes=[a.dtype] ).compute()

IndexError Traceback (most recent call last) <ipython-input-35-1d4025e1ebdb> in <module>() ----> 1 xarray.apply_ufunc(scipy.stats.norm.cdf, a.chunk(), 0, 1, dask='parallelized', output_dtypes=[a.dtype]).compute()

~/anaconda3/lib/python3.6/site-packages/xarray/core/computation.py in apply_ufunc(func, args, kwargs) 913 join=join, 914 exclude_dims=exclude_dims, --> 915 keep_attrs=keep_attrs) 916 elif any(isinstance(a, Variable) for a in args): 917 return variables_ufunc(args)

~/anaconda3/lib/python3.6/site-packages/xarray/core/computation.py in apply_dataarray_ufunc(func, args, kwargs) 210 211 data_vars = [getattr(a, 'variable', a) for a in args] --> 212 result_var = func(data_vars) 213 214 if signature.num_outputs > 1:

~/anaconda3/lib/python3.6/site-packages/xarray/core/computation.py in apply_variable_ufunc(func, args, kwargs) 561 raise ValueError('unknown setting for dask array handling in ' 562 'apply_ufunc: {}'.format(dask)) --> 563 result_data = func(input_data) 564 565 if signature.num_outputs > 1:

~/anaconda3/lib/python3.6/site-packages/xarray/core/computation.py in <lambda>(arrays) 555 func = lambda arrays: _apply_with_dask_atop( 556 numpy_func, arrays, input_dims, output_dims, signature, --> 557 output_dtypes, output_sizes) 558 elif dask == 'allowed': 559 pass

~/anaconda3/lib/python3.6/site-packages/xarray/core/computation.py in _apply_with_dask_atop(func, args, input_dims, output_dims, signature, output_dtypes, output_sizes) 624 for element in (arg, dims[-getattr(arg, 'ndim', 0):])] 625 return da.atop(func, out_ind, *atop_args, dtype=dtype, concatenate=True, --> 626 new_axes=output_sizes) 627 628

~/anaconda3/lib/python3.6/site-packages/dask/array/core.py in atop(func, out_ind, args, kwargs) 2231 raise ValueError("Must specify dtype of output array") 2232 -> 2233 chunkss, arrays = unify_chunks(args) 2234 for k, v in new_axes.items(): 2235 chunkss[k] = (v,)

~/anaconda3/lib/python3.6/site-packages/dask/array/core.py in unify_chunks(args, *kwargs) 2117 chunks = tuple(chunkss[j] if a.shape[n] > 1 else a.shape[n] 2118 if not np.isnan(sum(chunkss[j])) else None -> 2119 for n, j in enumerate(i)) 2120 if chunks != a.chunks and all(a.chunks): 2121 arrays.append(a.rechunk(chunks))

~/anaconda3/lib/python3.6/site-packages/dask/array/core.py in <genexpr>(.0) 2117 chunks = tuple(chunkss[j] if a.shape[n] > 1 else a.shape[n] 2118 if not np.isnan(sum(chunkss[j])) else None -> 2119 for n, j in enumerate(i)) 2120 if chunks != a.chunks and all(a.chunks): 2121 arrays.append(a.rechunk(chunks))

IndexError: tuple index out of range ```

Workaround: ``` xarray.apply_ufunc( scipy.stats.norm.cdf, a, kwargs={'loc': 0, 'scale': 1}, dask='parallelized', output_dtypes=[a.dtype]).compute()

<xarray.DataArray (x: 2)> array([ 0.841345, 0.97725 ]) Dimensions without coordinates: x ```

Code Sample, a copy-pastable example if possible

```python import numpy as np import xarray as xr

a = np.random.randn(4, 3) a[1, 1] = np.NaN da = xr.DataArray(a, dims=('y', 'x'), coords={'y':np.arange(4), 'x':np.arange(3)}) da.to_netcdf('test.nc')

with xr.open_dataarray('test.nc') as da: da.dropna(dim='x', how='any')

ValueError Traceback (most recent call last) <ipython-input-37-8d137cf3a813> in <module>() 8 9 with xr.open_dataarray('test.nc') as da: ---> 10 da.dropna(dim='x', how='any')

~/.pyvirtualenvs/py3/lib/python3.5/site-packages/xarray/core/dataarray.py in dropna(self, dim, how, thresh) 1158 DataArray 1159 """ -> 1160 ds = self._to_temp_dataset().dropna(dim, how=how, thresh=thresh) 1161 return self._from_temp_dataset(ds) 1162

~/.pyvirtualenvs/py3/lib/python3.5/site-packages/xarray/core/dataset.py in dropna(self, dim, how, thresh, subset) 2292 raise TypeError('must specify how or thresh') 2293 -> 2294 return self.isel(**{dim: mask}) 2295 2296 def fillna(self, value):

~/.pyvirtualenvs/py3/lib/python3.5/site-packages/xarray/core/dataset.py in isel(self, drop, **indexers) 1291 coord_names = set(variables).intersection(self._coord_names) 1292 selected = self._replace_vars_and_dims(variables, -> 1293 coord_names=coord_names) 1294 1295 # Extract coordinates from indexers

~/.pyvirtualenvs/py3/lib/python3.5/site-packages/xarray/core/dataset.py in _replace_vars_and_dims(self, variables, coord_names, dims, attrs, inplace) 598 """ 599 if dims is None: --> 600 dims = calculate_dimensions(variables) 601 if inplace: 602 self._dims = dims

~/.pyvirtualenvs/py3/lib/python3.5/site-packages/xarray/core/dataset.py in calculate_dimensions(variables) 111 raise ValueError('conflicting sizes for dimension %r: ' 112 'length %s on %r and length %s on %r' % --> 113 (dim, size, k, dims[dim], last_used[dim])) 114 return dims 115

ValueError: conflicting sizes for dimension 'y': length 2 on <this-array> and length 4 on 'y' ```

Problem description

See above. Note that the code runs when: - data is previously read into memory with load() - the DataArray is stored without coordinates (this is strange) - dropna is applied to 'y' instead of 'x'

Expected Output

This used to work in v0.9.6

Output of xr.show_versions()

I think this is a regression in the current 0.10.0rc1:

Code Sample

```python import xarray as xr ds = xr.open_dataset('cesm_data.nc', decode_cf=False) ds.temp.isel(time=ds.time < 274383) # throws an error

NotImplementedError Traceback (most recent call last) <ipython-input-18-a5c4179cd02d> in <module>() ----> 1 ds.temp.isel(time=ds.time < 274383)

~/.pyvirtualenvs/py3/lib/python3.5/site-packages/xarray/core/dataarray.py in isel(self, drop, indexers) 717 DataArray.sel 718 """ --> 719 ds = self._to_temp_dataset().isel(drop=drop, indexers) 720 return self._from_temp_dataset(ds) 721

~/.pyvirtualenvs/py3/lib/python3.5/site-packages/xarray/core/dataset.py in isel(self, drop, indexers) 1278 for name, var in iteritems(self._variables): 1279 var_indexers = {k: v for k, v in indexers_list if k in var.dims} -> 1280 new_var = var.isel(var_indexers) 1281 if not (drop and name in var_indexers): 1282 variables[name] = new_var

~/.pyvirtualenvs/py3/lib/python3.5/site-packages/xarray/core/variable.py in isel(self, **indexers) 771 if dim in indexers: 772 key[i] = indexers[dim] --> 773 return self[tuple(key)] 774 775 def squeeze(self, dim=None):

~/.pyvirtualenvs/py3/lib/python3.5/site-packages/xarray/core/variable.py in getitem(self, key) 595 """ 596 dims, index_tuple, new_order = self._broadcast_indexes(key) --> 597 data = self._indexable_data[index_tuple] 598 if new_order: 599 data = np.moveaxis(data, range(len(new_order)), new_order)

~/.pyvirtualenvs/py3/lib/python3.5/site-packages/xarray/core/indexing.py in getitem(self, key) 414 415 def getitem(self, key): --> 416 return type(self)(_wrap_numpy_scalars(self.array[key])) 417 418 def setitem(self, key, value):

~/.pyvirtualenvs/py3/lib/python3.5/site-packages/xarray/core/indexing.py in getitem(self, key) 394 395 def getitem(self, key): --> 396 return type(self)(_wrap_numpy_scalars(self.array[key])) 397 398 def setitem(self, key, value):

~/.pyvirtualenvs/py3/lib/python3.5/site-packages/xarray/core/indexing.py in getitem(self, key) 361 362 def getitem(self, key): --> 363 return type(self)(self.array, self._updated_key(key)) 364 365 def setitem(self, key, value):

~/.pyvirtualenvs/py3/lib/python3.5/site-packages/xarray/core/indexing.py in _updated_key(self, new_key) 336 raise NotImplementedError( 337 'Vectorized indexing for {} is not implemented. Load your ' --> 338 'data first with .load() or .compute().'.format(type(self))) 339 new_key = iter(expanded_indexer(new_key, self.ndim)) 340 key = []

NotImplementedError: Vectorized indexing for <class 'xarray.core.indexing.LazilyIndexedArray'> is not implemented. Load your data first with .load() or .compute().

``` Here is the file: cesm_data.nc.zip

Expected Output

This used to work in v0.9

Output of xr.show_versions()

Code Sample, a copy-pastable example if possible

```python

Your code here

import xarray as xr ds = xr.Dataset({'a': ('x', [0, 1, 2])}) ds. -> press 'Tab' ```

Problem description

IPython autocomplete raises a deprecation warning, introducing in #1643. ipython /home/keisukefujii/anaconda3/envs/tensorflow/lib/python3.5/site-packages/jedi/e. getattr(obj, name) /home/keisukefujii/anaconda3/envs/tensorflow/lib/python3.5/site-packages/jedi/e. obj = getattr(obj, name) In [3]: ds.

Expected Output

None

Output of xr.show_versions()

Currently, we strip labels from DataArray arguments to [] / .loc[] / .sel()/ .isel(). But this will break when we finally add indexing with alignment (https://github.com/pydata/xarray/issues/974).

We could start raising deprecation warnings now so users can stop relying on this functionality that will change.

We currently have 7 failing tests when run against the pandas development code (travis).

Question for @shoyer - can you take a look at these and see if we should try to get a fix in place prior to v.0.10.0? It looks like Pandas.0.21 is slated for release on Sept. 30.

We need pandas >= 0.18 because dataframe.rolling is supported after 0.18. But requirements in our setup.py says we need pandas >= 0.15.

Additionally, I noticed that in travis's CONDA_ENV=py27-min setup, our unit tests run with pandas == 0.20, though it might be intended to run with pandas == 0.15.

By conda remove scipy, pandas.0.15 is removed. (Here is the travis log) ``` if [[ "$CONDA_ENV" == "py27-min" ]]; then conda remove scipy; fi Fetching package metadata ......... Solving package specifications: .

Package plan for package removal in environment /home/travis/miniconda/envs/test_env:

The following packages will be REMOVED:

pandas: 0.15.0-np19py27_0 defaults
scipy:  0.17.1-np19py27_1 defaults

then in `python setup.py install`, pandas==0.20.3 is installed. Searching for pandas>=0.15.0 Reading https://pypi.python.org/simple/pandas/ Downloading https://pypi.python.org/packages/ee/aa/90c06f249cf4408fa75135ad0df7d64c09cf74c9870733862491ed5f3a50/pandas-0.20.3.tar.gz#md5=4df858f28b4bf4fa07d9fbb7f2568173 Best match: pandas 0.20.3 ```