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  • max-sixty · 3 ✖

issue 1

  • Add drop=True option for where on Dataset and DataArray · 3 ✖

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  • MEMBER · 3 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
204561434 https://github.com/pydata/xarray/pull/815#issuecomment-204561434 https://api.github.com/repos/pydata/xarray/issues/815 MDEyOklzc3VlQ29tbWVudDIwNDU2MTQzNA== max-sixty 5635139 2016-04-01T20:46:56Z 2016-04-01T20:47:21Z MEMBER

FWIW I'm not a fan of the sel_where name, sel is otherwise associated with labels, and this takes bools. Have you thought about including this in where, with a kwarg such as drop?

 
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   Add drop=True option for where on Dataset and DataArray 145243134
204561404 https://github.com/pydata/xarray/pull/815#issuecomment-204561404 https://api.github.com/repos/pydata/xarray/issues/815 MDEyOklzc3VlQ29tbWVudDIwNDU2MTQwNA== max-sixty 5635139 2016-04-01T20:46:49Z 2016-04-01T20:46:49Z MEMBER

Right, I see. I think it's equivalent only to a pandas slice on Series, rather than a DataFrame.

``` python In [71]: series = pd.Series(range(10))

In [72]: series[series>5] Out[72]: 6 6 7 7 8 8 9 9 dtype: int64

...same as sel_where

In [78]: df =pd.DataFrame(pd.np.arange(40).reshape(4,10))

In [79]: df[(df>11) & (df < 28)] Out[79]: 0 1 2 3 4 5 6 7 8 9 0 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 1 NaN NaN 12 13 14 15 16 17 18 19 2 20 21 22 23 24 25 26 27 NaN NaN 3 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN

...same as where

```

 
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   Add drop=True option for where on Dataset and DataArray 145243134
204525759 https://github.com/pydata/xarray/pull/815#issuecomment-204525759 https://api.github.com/repos/pydata/xarray/issues/815 MDEyOklzc3VlQ29tbWVudDIwNDUyNTc1OQ== max-sixty 5635139 2016-04-01T19:02:55Z 2016-04-01T19:02:55Z MEMBER

Forgive me if this is naive - is this equivalent to a pandas slice?

 
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   Add drop=True option for where on Dataset and DataArray 145243134

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