OK, build passed so I'm merging. Thanks!

Looks good. Unfortunately there was a merge conflict with the quantile PR so you need to merge master again.

Actually, if you want to write that now I think we can squeeze this in. We are still a day or two away from the release.

On Mon, Jan 23, 2017 at 9:52 AM mangecoeur notifications@github.com wrote:

Note - waiting for 0.9.0 to be released before updating whats new, don't want to end up with conflicts in docs

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This looks great to me. I'll merge this shortly after releasing 0.9.0 -- could you please add a brief release note in a new section for 0.9.1? (It won't be a long wait.)

I believe Dataset.transpose already skips variables that don't need to be transposed. On Sat, Dec 24, 2016 at 5:40 AM mangecoeur notifications@github.com wrote:

@mangecoeur commented on this pull request.

In xarray/core/dataset.py https://github.com/pydata/xarray/pull/1162:

• coord_dim = var.dims[0] # should just be one?
• selection = take(var, indexers_dict[coord_dim]) +
• sel_coords[c] = (dim, selection)
• else:
• sel_coords[c] = self.coords[c] +
• variables = OrderedDict() +
• for name in data_vars:
• var = self.variables[name]

• Transpose the var to ensure that the indexed dims come first

• These dims will be collapsed in the output.

• To avoid edge cases in numpy want to transpose to ensure the indexed dimensions are first

• However transpose is not lazy, so want to avoid using it for dask case (??)

• var = var.transpose(*(list(d for d in indexer_dims if d in var.dims) +

I did that originally but then I thought that if there are variables that are not indexed at all we can skip applying transpose to them this way (and triggering a data load on them too). Does that make sense?

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The development version of xarray includes a change that makes indexes optional. So if you use the Dataset/DataArray constructor it no longer adds new coordinates for each dimension by default.