issue_comments: 442680467

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https://github.com/pydata/xarray/issues/1603#issuecomment-442680467 https://api.github.com/repos/pydata/xarray/issues/1603 442680467 MDEyOklzc3VlQ29tbWVudDQ0MjY4MDQ2Nw== 1217238 2018-11-29T02:15:48Z 2018-11-29T02:19:06Z MEMBER

That said, I still don't know how to use public MultiIndex methods for this. Neither index.get_loc_level([1, 2], level=1) nor index.get_loc((slice(None), [1, 2])) work.

The answer is the index.get_locs() method: index.get_locs([slice(None), 1, 2]]) works.

It's painfully slow for large numbers of points due to a Python loop over each point, but presumably that could be optimized: x = np.arange(10000) index = pd.MultiIndex.from_arrays([x]) %timeit index.get_locs((x,)) # 1.31 s per loop %timeit index.levels[0].get_indexer(x) # 93 µs per loop

 
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