issue_comments

Table actions

2 rows where author_association = "MEMBER", issue = 374460958 and user = 35968931 sorted by updated_at descending

✎ View and edit SQL

This data as json, CSV (advanced)

Suggested facets: created_at (date), updated_at (date)

user 1

  • TomNicholas · 2 ✖

issue 1

  • Treat accessor dataarrays as members of parent dataset · 2 ✖

author_association 1

  • MEMBER · 2 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
434861750 https://github.com/pydata/xarray/issues/2517#issuecomment-434861750 https://api.github.com/repos/pydata/xarray/issues/2517 MDEyOklzc3VlQ29tbWVudDQzNDg2MTc1MA== TomNicholas 35968931 2018-10-31T21:56:11Z 2018-10-31T21:56:11Z MEMBER

That's true, but unless you start subclassing dataset then isn't that always going to be the case?

You have some quantity which you can only calculate with either a function or an accessor method on the dataset, wouldn't you need to alter the __getitem__ method on the dataset object (or some subclass of it) in order to get the behaviour you're describing?

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Treat accessor dataarrays as members of parent dataset 374460958
434646452 https://github.com/pydata/xarray/issues/2517#issuecomment-434646452 https://api.github.com/repos/pydata/xarray/issues/2517 MDEyOklzc3VlQ29tbWVudDQzNDY0NjQ1Mg== TomNicholas 35968931 2018-10-31T11:05:18Z 2018-10-31T11:05:18Z MEMBER

If you want to return your newly-calculated altitude and also have it be a full data_var in your dataset, one way would be to just alter the original dataset in-place. Something like

```python

import xarray as xr import pandas as pd import xarray.testing as xrt

@xr.register_dataset_accessor('acc') class Accessor(object): def init(self, xarray_ds): self._ds = xarray_ds self._altitude = None

@property
def altitude(self):
    """ An expensive calculation that results in data that not everyone needs. """
    if self._altitude is None:
        self._altitude = xr.DataArray([5, 10, 15, 20, 25],
                                      coords=[('time', self._ds.time)])

        # Here we add the calculated altitude to the dataset as a new data variable
        self._ds['altitude'] = self._altitude

    # Return just the altitude dataarray
    return self._altitude

expected = xr.Dataset({'data': (['time'], [100, 30, 10, 3, 1]), 'altitude': (['time'], [5, 10, 15, 20, 25])}, coords={'time': pd.date_range('2014-09-06', periods=5, freq='1s')})

actual = xr.Dataset({'data': (['time'], [100, 30, 10, 3, 1])}, coords={'time': pd.date_range('2014-09-06', periods=5, freq='1s')})

Return newly-calculated altitude, but also store it in the actual dataset for later

altitude = actual.acc.altitude

Check that worked

xrt.assert_equal(actual, expected) xrt.assert_equal(actual['altitude'], actual.acc.altitude) ```

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Treat accessor dataarrays as members of parent dataset 374460958

Advanced export

JSON shape: default, array, newline-delimited, object

CSV options: 

CREATE TABLE [issue_comments] (
   [html_url] TEXT,
   [issue_url] TEXT,
   [id] INTEGER PRIMARY KEY,
   [node_id] TEXT,
   [user] INTEGER REFERENCES [users]([id]),
   [created_at] TEXT,
   [updated_at] TEXT,
   [author_association] TEXT,
   [body] TEXT,
   [reactions] TEXT,
   [performed_via_github_app] TEXT,
   [issue] INTEGER REFERENCES [issues]([id])
);
CREATE INDEX [idx_issue_comments_issue]
    ON [issue_comments] ([issue]);
CREATE INDEX [idx_issue_comments_user]
    ON [issue_comments] ([user]);