pydata / xarray / 4967 / 4
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coverage: 94.351%. Remained the same
CONDA_ENV=py35

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shoyer 
<a href="https://github.com/pydata/xarray/commit/<a class=hub.com/pydata/xarray/commit/a5f7d6ac60e8e5682e2be739dd520b7a3bbd0fc7">a5f7d6ac6<a href="https://github.com/pydata/xarray/commit/a5f7d6ac60e8e5682e2be739dd520b7a3bbd0fc7">&quot;&gt;Isin (#2031)

* gitignore testmon

* initial isin implementation

* gitignore

* dask

* numpy version check not needed

* numpy version check for isin

* move to common

* rename data_set to ds

* Revert &amp;quot;rename data_set to ds&quot;

This reverts commit </a><a class="double-link" href="https://github.com/pydata/xarray/commit/<a class="double-link" href="https://github.com/pydata/xarray/commit/75493c2e9e1eb9b39a2222a19a7725afe1f009be">75493c2e9</a>">75493c2e9</a><a href="https://github.com/pydata/xarray/commit/a5f7d6ac60e8e5682e2be739dd520b7a3bbd0fc7">.

* &#39;expect&#39; test for dataset

* unneeded import

* formatting

* docs

* Raise an informative error message when converting Dataset -&gt; np.ndarray

Makes `np.asarray(dataset)` issue an informative error. Currently,
`np.asarray(xr.Dataset({&#39;x&#39;: 0}))` raises `KeyError: 0`, which makes no sense.

* normal tests are better than a weird middle ground

* dask test

* grammar

* try changing skip decorator ordering

* just use has_dask

* another noqa?

* flake for py3.4

* flake

21464 of 22749 relevant lines covered (94.35%)

0.94 hits per line

Source Files on job 4967.4 (CONDA_ENV=py35)
Coverage ∆ File Lines Relevant Covered Missed Hits/Line