What happened?

The html repr of a cftime array wants to display the "calendar", which it cannot if it is empty.

What did you expect to happen?

No error.

Minimal Complete Verifiable Example

```Python import numpy as np import xarray as xr

data_obs = np.random.randn(3) time_obs = xr.date_range("2000-01-01", periods=3, freq="YS", calendar="noleap")

obs = xr.DataArray(data_obs, coords={"time": time_obs})

o = obs[:0]

xr.core.formatting_html.array_repr(o) ```

MVCE confirmation

• [ ] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
• [ ] Complete example — the example is self-contained, including all data and the text of any traceback.
• [ ] Verifiable example — the example copy & pastes into an IPython prompt or Binder notebook, returning the result.
• [ ] New issue — a search of GitHub Issues suggests this is not a duplicate.

Relevant log output

```Python ValueError Traceback (most recent call last) Input In [1], in <cell line: 12>() 8 obs = xr.DataArray(data_obs, coords={"time": time_obs}) 10 o = obs[:0] ---> 12 xr.core.formatting_html.array_repr(o)

File ~/code/xarray/xarray/core/formatting_html.py:318, in array_repr(arr) 316 if hasattr(arr, "xindexes"): 317 indexes = _get_indexes_dict(arr.xindexes) --> 318 sections.append(index_section(indexes)) 320 sections.append(attr_section(arr.attrs)) 322 return _obj_repr(arr, header_components, sections)

File ~/code/xarray/xarray/core/formatting_html.py:195, in _mapping_section(mapping, name, details_func, max_items_collapse, expand_option_name, enabled) 188 expanded = _get_boolean_with_default( 189 expand_option_name, n_items < max_items_collapse 190 ) 191 collapsed = not expanded 193 return collapsible_section( 194 name, --> 195 details=details_func(mapping), 196 n_items=n_items, 197 enabled=enabled, 198 collapsed=collapsed, 199 )

File ~/code/xarray/xarray/core/formatting_html.py:155, in summarize_indexes(indexes) 154 def summarize_indexes(indexes): --> 155 indexes_li = "".join( 156 f"

{summarize_index(v, i)}

" 157 for v, i in indexes.items() 158 ) 159 return f"

{indexes_li}

"

File ~/code/xarray/xarray/core/formatting_html.py:156, in <genexpr>(.0) 154 def summarize_indexes(indexes): 155 indexes_li = "".join( --> 156 f"

{summarize_index(v, i)}

" 157 for v, i in indexes.items() 158 ) 159 return f"

{indexes_li}

"

File ~/code/xarray/xarray/core/formatting_html.py:140, in summarize_index(coord_names, index) 138 index_id = f"index-{uuid.uuid4()}" 139 preview = escape(inline_index_repr(index)) --> 140 details = short_index_repr_html(index) 142 data_icon = _icon("icon-database") 144 return ( 145 f"

" 146 f"" (...) 150 f"" 151 )

File ~/code/xarray/xarray/core/formatting_html.py:132, in short_index_repr_html(index) 129 if hasattr(index, "repr_html"): 130 return index.repr_html() --> 132 return f"

{escape(repr(index))}

"

File ~/code/xarray/xarray/core/indexes.py:547, in PandasIndex.repr(self) 546 def repr(self): --> 547 return f"PandasIndex({repr(self.index)})"

File ~/code/xarray/xarray/coding/cftimeindex.py:353, in CFTimeIndex.repr(self) 345 end_str = format_times( 346 self.values[-REPR_ELLIPSIS_SHOW_ITEMS_FRONT_END:], 347 display_width, 348 offset=offset, 349 first_row_offset=offset, 350 ) 351 datastr = "\n".join([front_str, f"{' '*offset}...", end_str]) --> 353 attrs_str = format_attrs(self) 354 # oneliner only if smaller than display_width 355 full_repr_str = f"{klass_name}([{datastr}], {attrs_str})"

File ~/code/xarray/xarray/coding/cftimeindex.py:272, in format_attrs(index, separator) 267 def format_attrs(index, separator=", "): 268 """Format attributes of CFTimeIndex for repr.""" 269 attrs = { 270 "dtype": f"'{index.dtype}'", 271 "length": f"{len(index)}", --> 272 "calendar": f"'{index.calendar}'", 273 "freq": f"'{index.freq}'" if len(index) >= 3 else None, 274 } 276 attrs_str = [f"{k}={v}" for k, v in attrs.items()] 277 attrs_str = f"{separator}".join(attrs_str)

File ~/code/xarray/xarray/coding/cftimeindex.py:698, in CFTimeIndex.calendar(self) 695 """The calendar used by the datetimes in the index.""" 696 from .times import infer_calendar_name --> 698 return infer_calendar_name(self)

File ~/code/xarray/xarray/coding/times.py:374, in infer_calendar_name(dates) 371 return sample.calendar 373 # Error raise if dtype is neither datetime or "O", if cftime is not importable, and if element of 'O' dtype is not cftime. --> 374 raise ValueError("Array does not contain datetime objects.")

ValueError: Array does not contain datetime objects. ```

Anything else we need to know?

Bisected to 7379923de756a2bcc59044d548f8ab7a68b91d4e use _repr_inline_ for indexes that define it.

Environment

What happened?

da.xindexes or da.indexes raises an error when trying to generate the repr if there are no coords (indexes)

What did you expect to happen?

Displaying an empty Mappable?

Minimal Complete Verifiable Example

Python xr.DataArray([3, 5]).indexes xr.DataArray([3, 5]).xindexes

MVCE confirmation

• [x] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
• [x] Complete example — the example is self-contained, including all data and the text of any traceback.
• [x] Verifiable example — the example copy & pastes into an IPython prompt or Binder notebook, returning the result.
• [x] New issue — a search of GitHub Issues suggests this is not a duplicate.
• [x] Recent environment — the issue occurs with the latest version of xarray and its dependencies.

Relevant log output

```Python Out[9]: --------------------------------------------------------------------------- ValueError Traceback (most recent call last) File ~/.conda/envs/xarray_dev/lib/python3.10/site-packages/IPython/core/formatters.py:708, in PlainTextFormatter.call(self, obj) 701 stream = StringIO() 702 printer = pretty.RepresentationPrinter(stream, self.verbose, 703 self.max_width, self.newline, 704 max_seq_length=self.max_seq_length, 705 singleton_pprinters=self.singleton_printers, 706 type_pprinters=self.type_printers, 707 deferred_pprinters=self.deferred_printers) --> 708 printer.pretty(obj) 709 printer.flush() 710 return stream.getvalue()

File ~/.conda/envs/xarray_dev/lib/python3.10/site-packages/IPython/lib/pretty.py:410, in RepresentationPrinter.pretty(self, obj) 407 return meth(obj, self, cycle) 408 if cls is not object \ 409 and callable(cls.dict.get('repr')): --> 410 return _repr_pprint(obj, self, cycle) 412 return _default_pprint(obj, self, cycle) 413 finally:

File ~/.conda/envs/xarray_dev/lib/python3.10/site-packages/IPython/lib/pretty.py:778, in repr_pprint(obj, p, cycle) 776 """A pprint that just redirects to the normal repr function.""" 777 # Find newlines and replace them with p.break() --> 778 output = repr(obj) 779 lines = output.splitlines() 780 with p.group():

File ~/code/xarray/xarray/core/indexes.py:1659, in Indexes.repr(self) 1657 def repr(self): 1658 indexes = formatting._get_indexes_dict(self) -> 1659 return formatting.indexes_repr(indexes)

File ~/code/xarray/xarray/core/formatting.py:474, in indexes_repr(indexes, max_rows) 473 def indexes_repr(indexes, max_rows: int | None = None) -> str: --> 474 col_width = _calculate_col_width(chain.from_iterable(indexes)) 476 return _mapping_repr( 477 indexes, 478 "Indexes", (...) 482 max_rows=max_rows, 483 )

File ~/code/xarray/xarray/core/formatting.py:341, in _calculate_col_width(col_items) 340 def _calculate_col_width(col_items): --> 341 max_name_length = max(len(str(s)) for s in col_items) if col_items else 0 342 col_width = max(max_name_length, 7) + 6 343 return col_width

ValueError: max() arg is an empty sequence ```

Anything else we need to know?

No response

Environment

INSTALLED VERSIONS ------------------ commit: ccc8f9987b553809fb6a40c52fa1a8a8095c8c5f python: 3.10.12 | packaged by conda-forge | (main, Jun 23 2023, 22:40:32) [GCC 12.3.0] python-bits: 64 OS: Linux OS-release: 6.2.0-35-generic machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_US.UTF-8 LOCALE: ('en_US', 'UTF-8') libhdf5: 1.14.2 libnetcdf: 4.9.2 xarray: 2023.9.1.dev8+gf6d69a1f pandas: 2.1.1 numpy: 1.24.4 scipy: 1.11.3 netCDF4: 1.6.4 pydap: installed h5netcdf: 1.2.0 h5py: 3.9.0 Nio: None zarr: 2.16.1 cftime: 1.6.2 nc_time_axis: 1.4.1 PseudoNetCDF: 3.2.2 iris: 3.7.0 bottleneck: 1.3.7 dask: 2023.9.2 distributed: None matplotlib: 3.8.0 cartopy: 0.22.0 seaborn: 0.12.2 numbagg: 0.2.2 fsspec: 2023.9.2 cupy: None pint: 0.20.1 sparse: 0.14.0 flox: 0.7.2 numpy_groupies: 0.10.1 setuptools: 68.2.2 pip: 23.2.1 conda: None pytest: 7.4.2 mypy: 1.5.1 IPython: 8.15.0 sphinx: None

What is your issue?

Applying e.g. ds.weighted(weights).mean() applies the operation over all DataArray objects - even if they don't have the dimensions over which it is applied (or is a scalar variable). I don't think this is wanted.

```python import xarray as xr

air = xr.tutorial.open_dataset("air_temperature") air.attrs = {}

add variable without dims

air["foo"] = 5

print("resample") print(air.resample(time="MS").mean(dim="time").foo.dims)

print("groupby") print(air.groupby("time.year").mean(dim="time").foo.dims)

print("weighted") print(air.weighted(weights=air.time.dt.year).mean("lat").foo.dims)

print("where") print(air.where(air.air > 5).foo.dims) ```

Results resample ('time',) groupby ('year',) weighted ('time',)

Related #6952 - I am sure there are other issues, but couldn't find them quickly...

rolling and coarsen don't seem to do this.

polyfit currently only allows to fit along a dimension and not along a non-dimension coordinate (or a virtual coordinate)

Example: ```python da = xr.DataArray( [1, 3, 2], dims=["x"], coords=dict(x=["a", "b", "c"], y=("x", [0, 1, 2])) )

print(da)

da.polyfit("y", 1) Output:python <xarray.DataArray (x: 3)> array([1, 3, 2]) Coordinates: * x (x) <U1 'a' 'b' 'c' y (x) int64 0 1 2

---

KeyError Traceback (most recent call last) <ipython-input-80-9bb2dacf50f7> in <module> 5 print(da) 6 ----> 7 da.polyfit("y", 1)

~/.conda/envs/ipcc_ar6/lib/python3.7/site-packages/xarray/core/dataarray.py in polyfit(self, dim, deg, skipna, rcond, w, full, cov) 3507 """ 3508 return self._to_temp_dataset().polyfit( -> 3509 dim, deg, skipna=skipna, rcond=rcond, w=w, full=full, cov=cov 3510 ) 3511

~/.conda/envs/ipcc_ar6/lib/python3.7/site-packages/xarray/core/dataset.py in polyfit(self, dim, deg, skipna, rcond, w, full, cov) 6005 skipna_da = skipna 6006 -> 6007 x = get_clean_interp_index(self, dim, strict=False) 6008 xname = "{}_".format(self[dim].name) 6009 order = int(deg) + 1

~/.conda/envs/ipcc_ar6/lib/python3.7/site-packages/xarray/core/missing.py in get_clean_interp_index(arr, dim, use_coordinate, strict) 246 247 if use_coordinate is True: --> 248 index = arr.get_index(dim) 249 250 else: # string

~/.conda/envs/ipcc_ar6/lib/python3.7/site-packages/xarray/core/common.py in get_index(self, key) 378 """ 379 if key not in self.dims: --> 380 raise KeyError(key) 381 382 try:

KeyError: 'y' ```

Describe the solution you'd like

Would be nice if that worked.

Describe alternatives you've considered

One could just set the non-dimension coordinate as index, e.g.: da = da.set_index(x="y")

Additional context

Allowing this may be as easy as replacing

https://github.com/pydata/xarray/blob/9c85dd5f792805bea319f01f08ee51b83bde0f3b/xarray/core/missing.py#L248

by index = arr[dim] but I might be missing something. Or probably a use_coordinate must be threaded through to get_clean_interp_index (although I am a bit confused by this argument).

Is your feature request related to a problem?

xr.broadcast always does an outer join:

https://github.com/pydata/xarray/blob/de965f342e1c9c5de92ab135fbc4062e21e72453/xarray/core/alignment.py#L702

https://github.com/pydata/xarray/blob/de965f342e1c9c5de92ab135fbc4062e21e72453/xarray/core/alignment.py#L768

This is not how the (default) broadcasting (arithmetic join) works, e.g. the following first does an inner join and then broadcasts:

```python import xarray as xr

da1 = xr.DataArray([[0, 1, 2]], dims=("y", "x"), coords={"x": [0, 1, 2]}) da2 = xr.DataArray([0, 1, 2, 3, 4], dims="x", coords={"x": [0, 1, 2, 3, 4]}) da1 + da2 ```

<xarray.DataArray (y: 1, x: 3)> array([[0, 2, 4]]) Coordinates: * x (x) int64 0 1 2 Dimensions without coordinates: y

Describe the solution you'd like

Add a join argument to xr.broadcast. I would propose to leave the default as is

python def broadcast(*args, exclude=None, join="outer"): args = align(*args, join=join, copy=False, exclude=exclude)

Describe alternatives you've considered

• We could make broadcast respect options -> arithmetic_join but that would be a breaking change and I am not sure how the deprecation should/ would be handled...
• We could leave it as is.

Additional context

• xr.broadcast should not be used often because this is should happen automatically in most cases
• in #6059 I use broadcast because I couldn't get it to work otherwise (maybe there is a better way?). However, the "outer elements" are immediately discarded again - so it's kind of pointless to do an outer join.

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

da = xr.DataArray(np.arange(6).reshape(3, 2), coords={"dim_0": [0, 1, 2]}) w = xr.DataArray([1, 1, 1, 1, 1, 1], coords={"dim_0": [0, 1, 2, 4, 5, 6]}) da.weighted(w).quantile(0.5) ```

We currently pin netCDF4 to version 1.5. However, I think netCDF4 does not really follow semantic versioning, e.g. python 2 support was dropped in version 1.5.6. So they may actually be doing something like 1.major.minor[.patch] - I asked about their versioning scheme in Unidata/netcdf4-python#1090.

So I wonder if we would need to pin netCDF to version to version 1.5.4.

The last 5 days our Upstream CI failed silently with a timeout after 6h:

https://github.com/pydata/xarray/actions/workflows/upstream-dev-ci.yaml?query=branch%3Amaster+event%3Aschedule

This was probably caused by #4934. As mentioned in dask/dask#4934 this is probably dask/dask#6738 which was merged 5 days ago.

The Linux py36-bare-minimum will likely fail with a TypeError: 'NoneType' object is not callable due to python/importlib_metadata#270

This could be fixed by adding typing_extensions to the CI or maybe they fix that upstream.

Our upstream tests fail due to a change in dask. The likely culprit is dask/dask#6680 - dask.array.zeros_like does now take the meta keyword and thus it tries to coerce str to a bool which fails (and it didn't do before). The following should trigger the error:

```python import xarray as xr import dask

da = xr.DataArray(dask.array.array("")) xr.zeros_like(da, dtype=bool) `` Note thatzeros_likeis called inisnull` (which triggered the test failures):

https://github.com/pydata/xarray/blob/080caf4246fe2f4d6aa0c5dcb65a99b376fa669b/xarray/core/duck_array_ops.py#L100-L102

What happened:

```python /home/vsts/work/1/s/xarray/tests/test_duck_array_ops.py:499:

---

/home/vsts/work/1/s/xarray/testing.py:139: in compat_variable return a.dims == b.dims and (a._data is b._data or equiv(a.data, b.data)) /home/vsts/work/1/s/xarray/testing.py:36: in _data_allclose_or_equiv return duck_array_ops.array_equiv(arr1, arr2) /home/vsts/work/1/s/xarray/core/duck_array_ops.py:246: in array_equiv flag_array = (arr1 == arr2) | (isnull(arr1) & isnull(arr2)) /home/vsts/work/1/s/xarray/core/duck_array_ops.py:104: in isnull return zeros_like(data, dtype=bool) /home/vsts/work/1/s/xarray/core/duck_array_ops.py:56: in f return wrapped(args, *kwargs) /usr/share/miniconda/envs/xarray-tests/lib/python3.8/site-packages/dask/array/creation.py:174: in zeros_like return zeros( /usr/share/miniconda/envs/xarray-tests/lib/python3.8/site-packages/dask/array/wrap.py:78: in wrap_func_shape_as_first_arg return Array(dsk, name, chunks, dtype=dtype, meta=kwargs.get("meta", None)) /usr/share/miniconda/envs/xarray-tests/lib/python3.8/site-packages/dask/array/core.py:1083: in new meta = meta_from_array(meta, dtype=dtype)

---

x = array('', dtype='<U1'), ndim = 0, dtype = dtype('bool')

def meta_from_array(x, ndim=None, dtype=None):
    """Normalize an array to appropriate meta object

    Parameters
    ----------
    x: array-like, callable
        Either an object that looks sufficiently like a Numpy array,
        or a callable that accepts shape and dtype keywords

    if dtype and meta.dtype != dtype:

      meta = meta.astype(dtype)

E ValueError: invalid literal for int() with base 10: ''

```

What happened: da.sum(min_count=1) returns a TypeError if da has an integer dtype. Of course min_count is not necessary for integer data as it cannot contain NaN.

What you expected to happen: min_count should be ignored

Minimal Complete Verifiable Example:

python import xarray as xr da = xr.DataArray([[1, 2, 3], [4, 5, 6]]) da.sum(min_count=1)

Anything else we need to know?:

Full traceback

```python In [37]: da.sum(min_count=1) --------------------------------------------------------------------------- TypeError Traceback (most recent call last) <ipython-input-37-817bfdfe2211> in <module> ----> 1 da.sum(min_count=1) ~/code/xarray/xarray/core/common.py in wrapped_func(self, dim, axis, skipna, **kwargs) 44 45 def wrapped_func(self, dim=None, axis=None, skipna=None, **kwargs): ---> 46 return self.reduce(func, dim, axis, skipna=skipna, **kwargs) 47 48 else: ~/code/xarray/xarray/core/dataarray.py in reduce(self, func, dim, axis, keep_attrs, keepdims, **kwargs) 2336 """ 2337 -> 2338 var = self.variable.reduce(func, dim, axis, keep_attrs, keepdims, **kwargs) 2339 return self._replace_maybe_drop_dims(var) 2340 ~/code/xarray/xarray/core/variable.py in reduce(self, func, dim, axis, keep_attrs, keepdims, allow_lazy, **kwargs) 1591 data = func(input_data, axis=axis, **kwargs) 1592 else: -> 1593 data = func(input_data, **kwargs) 1594 1595 if getattr(data, "shape", ()) == self.shape: ~/code/xarray/xarray/core/duck_array_ops.py in f(values, axis, skipna, **kwargs) 310 311 try: --> 312 return func(values, axis=axis, **kwargs) 313 except AttributeError: 314 if not isinstance(values, dask_array_type): ~/code/xarray/xarray/core/duck_array_ops.py in f(*args, **kwargs) 46 else: 47 wrapped = getattr(eager_module, name) ---> 48 return wrapped(*args, **kwargs) 49 50 else: <__array_function__ internals> in sum(*args, **kwargs) TypeError: _sum_dispatcher() got an unexpected keyword argument 'min_count' ```

Environment:

Output of <tt>xr.show_versions()</tt>

INSTALLED VERSIONS ------------------ commit: a7fb5a9fa1a2b829181ea9e4986b959f315350dd python: 3.7.3 | packaged by conda-forge | (default, Jul 1 2019, 21:52:21) [GCC 7.3.0] python-bits: 64 OS: Linux OS-release: 5.4.0-42-generic machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_US.UTF-8 LOCALE: en_US.UTF-8 libhdf5: 1.10.6 libnetcdf: 4.7.4 xarray: 0.15.2.dev64+g2542a63f pandas: 0.25.3 numpy: 1.17.3 scipy: 1.3.1 netCDF4: 1.5.4 pydap: installed h5netcdf: 0.7.4 h5py: 2.10.0 Nio: None zarr: 2.3.2 cftime: 1.0.4.2 nc_time_axis: None PseudoNetCDF: installed rasterio: 1.1.0 cfgrib: 0.9.5.4 iris: None bottleneck: 1.2.1 dask: 2.6.0 distributed: 2.6.0 matplotlib: 3.3.1 cartopy: 0.18.0 seaborn: 0.9.0 numbagg: None pint: None setuptools: 49.6.0.post20200814 pip: 19.3.1 conda: None pytest: 5.2.2 IPython: 7.17.0 sphinx: None

It would be nice to be able to use a level of a MultiIndex for plotting.

MCVE Code Sample

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

da = xr.DataArray( np.random.randn(10), dims="x", coords=dict( a=("x", np.arange(10, 20)), b=("x", np.arange(1, 11)) ) )

da = da.set_index(x=["a", "b"]) da This creates the following DataArraypython <xarray.DataArray (x: 10)> array([-1.34516338, 0.97644817, -0.24032189, -0.70112418, -0.8686898 , -0.55607078, 0.56618151, 1.62847463, 0.84947296, -0.5775504 ]) Coordinates: * x (x) MultiIndex - a (x) int64 10 11 12 13 14 15 16 17 18 19 - b (x) int64 1 2 3 4 5 6 7 8 9 10 ```

Is there a way to plot a line using one of the levels of the MultiIindex? python da.plot(x="a") returns python ValueError: x must be either None or one of ('x')

python da.plot() returns

python TypeError: Plotting requires coordinates to be numeric or dates of type np.datetime64, datetime.datetime, cftime.datetime or pd.Interval. (which makes sense). If da is a 2D Variable the error is python ValueError: x and y must be coordinate variables

Expected Output

A line plot

Versions

Output of `xr.show_versions()`

INSTALLED VERSIONS ------------------ commit: b3bafeefbd6e6d70bce505ae1f0d9d5a2b015089 python: 3.7.3 | packaged by conda-forge | (default, Jul 1 2019, 21:52:21) [GCC 7.3.0] python-bits: 64 OS: Linux OS-release: 4.15.0-91-generic machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_US.UTF-8 LOCALE: en_US.UTF-8 libhdf5: 1.10.5 libnetcdf: 4.7.1 xarray: 0.11.1+335.gb0c336f6 pandas: 0.25.3 numpy: 1.17.3 scipy: 1.3.1 netCDF4: 1.5.3 pydap: installed h5netcdf: 0.7.4 h5py: 2.10.0 Nio: None zarr: 2.3.2 cftime: 1.0.4.2 nc_time_axis: None PseudoNetCDF: installed rasterio: 1.1.0 cfgrib: 0.9.5.4 iris: None bottleneck: 1.2.1 dask: 2.6.0 distributed: 2.6.0 matplotlib: 3.1.2 cartopy: 0.17.0 seaborn: 0.9.0 numbagg: None pint: None setuptools: 41.6.0.post20191101 pip: 19.3.1 conda: None pytest: 5.2.2 IPython: 7.9.0 sphinx: None

MCVE Code Sample

```python import xarray as xr da = xr.DataArray([0, 1, 2]) da.quantile(q=50)

ValueError: Percentiles must be in the range [0, 100] ```

Expected Output

python ValueError: Quantiles must be in the range [0, 1]

Problem Description

By wrapping np.nanpercentile (xref: #3559) we also get the numpy error. However, the error message is wrong as xarray needs it to be in 0..1.

BTW: thanks for #3559, makes my life easier!

Output of xr.show_versions()

---

Edit: uses nanpercentile internally.

INSTALLED VERSIONS ------------------ commit: None python: 3.7.3 | packaged by conda-forge | (default, Jul 1 2019, 21:52:21) [GCC 7.3.0] python-bits: 64 OS: Linux OS-release: 4.12.14-lp151.28.36-default machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_GB.UTF-8 LOCALE: en_US.UTF-8 libhdf5: 1.10.5 libnetcdf: 4.7.1 xarray: 0.14.1+28.gf2b2f9f6 (current master) pandas: 0.25.2 numpy: 1.17.3 scipy: 1.3.1 netCDF4: 1.5.3 pydap: None h5netcdf: 0.7.4 h5py: 2.10.0 Nio: None zarr: None cftime: 1.0.4.2 nc_time_axis: 1.2.0 PseudoNetCDF: None rasterio: 1.1.1 cfgrib: None iris: None bottleneck: 1.2.1 dask: 2.6.0 distributed: 2.6.0 matplotlib: 3.1.2 cartopy: 0.17.0 seaborn: 0.9.0 numbagg: None setuptools: 41.4.0 pip: 19.3.1 conda: None pytest: 5.2.2 IPython: 7.9.0 sphinx: 2.2.1

MCVE Code Sample

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

airtemps = xr.tutorial.load_dataset('air_temperature')

air = airtemps.air.isel(time=0)

levels = np.arange(225, 301, 25)

colors = ['#ffffb2', '#fecc5c', '#fd8d3c', '#e31a1c']

this does not work for me

air.plot.pcolormesh(levels=levels, colors=colors)

```

Expected Output

Should create a plot with the specified colors. According to the the docstring this should work. Or maybe I am doing something wrong here?

Problem Description

Instead I get the following error: ```python /usr/local/Miniconda3-envs/envs/2019/envs/iacpy3_2019/lib/python3.7/site-packages/xarray/plot/utils.py in _process_cmap_cbar_kwargs(func, kwargs, data) 683 # colors is only valid when levels is supplied or the plot is of type 684 # contour or contourf --> 685 if colors and (('contour' not in func.name) and (not levels)): 686 raise ValueError("Can only specify colors with contour or levels") 687

ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all() ```

Instead I use the following, which works:

python air.plot.pcolormesh(levels=levels, cmap=colors)

Output of xr.show_versions()

INSTALLED VERSIONS ------------------ commit: None python: 3.7.1 | packaged by conda-forge | (default, Feb 18 2019, 01:42:00) [GCC 7.3.0] python-bits: 64 OS: Linux OS-release: 4.12.14-lp151.28.13-default machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_GB.UTF-8 LOCALE: en_US.UTF-8 libhdf5: 1.10.4 libnetcdf: 4.6.2 xarray: 0.12.1 pandas: 0.24.2 numpy: 1.16.2 scipy: 1.2.1 netCDF4: 1.5.0.1 pydap: installed h5netcdf: 0.7.1 h5py: 2.9.0 Nio: None zarr: 2.3.1 cftime: 1.0.3.4 nc_time_axis: 1.2.0 PseudonetCDF: None rasterio: 1.0.22 cfgrib: 0.9.7 iris: 2.2.0 bottleneck: 1.2.1 dask: 1.1.5 distributed: 1.26.1 matplotlib: 3.0.3 cartopy: 0.17.0 seaborn: 0.9.0 setuptools: 41.0.0 pip: 19.0.3 conda: None pytest: 4.4.0 IPython: 7.4.0 sphinx: 2.0.1

Virtual variables such as time.date can not be accessed by dot notation.

``` In [81]: ts.time.date

---

AttributeError Traceback (most recent call last) <ipython-input-81-4206b510e310> in <module>() ----> 1 ts.time.date

/home/mathause/.local/lib/python2.7/site-packages/xray/core/common.pyc in getattr(self, name) 115 pass 116 raise AttributeError("%r object has no attribute %r" % --> 117 (type(self).name, name)) 118 119 def dir(self):

AttributeError: 'DataArray' object has no attribute 'date' ```

Compare

ts.__getattr__('time.date')

So maybe time.date is not a useful name. time_date? Or don't show these attributes to the user?