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  • max-sixty · 1 ✖

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  • Invisible differences between arrays using IntervalIndex · 1 ✖

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id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
726281700 https://github.com/pydata/xarray/issues/4579#issuecomment-726281700 https://api.github.com/repos/pydata/xarray/issues/4579 MDEyOklzc3VlQ29tbWVudDcyNjI4MTcwMA== max-sixty 5635139 2020-11-12T19:12:32Z 2020-11-12T19:12:32Z MEMBER

Thanks for the clear issue @gerritholl . I agree — it's confusing if those two look the same.

Currently, one way of discriminating them:

```python In [6]: da1.indexes['x'] Out[6]: IntervalIndex([(0.0, 0.6666666666666666], (0.6666666666666666, 1.3333333333333333], (1.3333333333333333, 2.0]], closed='right', name='x', dtype='interval[float64]')

In [7]: da2.indexes['x'] Out[7]: Index([ (0.0, 0.6666666666666666], (0.6666666666666666, 1.3333333333333333], (1.3333333333333333, 2.0]], dtype='object', name='x') ```

One option is to push the dtype — 'interval[float64] vs object — or the Index type — IntervalIndex vs Index — values into the repr of the array: python In [8]: da1 Out[8]: <xarray.DataArray (x: 3)> array([0, 1, 2]) Coordinates: * x (x) object (0.0, 0.6666666666666666] ... (1.3333333333333333, 2.0]

Could be: python * x (x) interval[float64] (0.0, 0.6666666666666666] ... (1.3333333333333333, 2.0]

What are others thoughts?

And ref https://github.com/pydata/xarray/projects/1

 
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   Invisible differences between arrays using IntervalIndex 741806260

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