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  • mangecoeur · 1 ✖

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  • to_dataframe fails if dataarray has dimension 1 · 1 ✖

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  • CONTRIBUTOR · 1 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
583488834 https://github.com/pydata/xarray/issues/3761#issuecomment-583488834 https://api.github.com/repos/pydata/xarray/issues/3761 MDEyOklzc3VlQ29tbWVudDU4MzQ4ODgzNA== mangecoeur 743508 2020-02-07T16:37:05Z 2020-02-07T16:37:05Z CONTRIBUTOR

I think it makes sense to support the conversion. Perhaps a better example is with a dataset:

```python x = np.arange(10) y = np.arange(10)

data = np.zeros((len(x), len(y)))

ds = xr.Dataset({k: xr.DataArray(data, coords=[x, y], dims=['x', 'y']) for k in ['a', 'b', 'c']}) ds.sel(x=1,y=1)

<xarray.Dataset> Dimensions: () Coordinates: x int64 1 y int64 1 Data variables: a float64 0.0 b float64 0.0 c float64 0.0 ```

The output is a dataset of scalars, which converts fairly intuitively to a single row dataframe. But the folloiwing throws the same error.

python ds.sel(x=1,y=1).to_dataframe()

Or think of it another way - isn't it very un-intuitive that converting a single-item dataset to a dataframe works only if the item was selected using a length-1 list? To me that seems like a very arbitrary restriction. Following that logic, it also makes sense to have consistent behaviour between Datasets and DataArrays (even if you end up producing a single-element table).

 
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   to_dataframe fails if dataarray has dimension 1 561539035

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