issue_comments

Table actions

1 row where issue = 352999600 and user = 1217238 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

  • shoyer · 1 ✖

issue 1

  • Comparing scalar xarray with ma.masked fails with ValueError: assignment destination is read-only · 1 ✖

author_association 1

id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
415074188 https://github.com/pydata/xarray/issues/2377#issuecomment-415074188 https://api.github.com/repos/pydata/xarray/issues/2377 MDEyOklzc3VlQ29tbWVudDQxNTA3NDE4OA== shoyer 1217238 2018-08-22T15:29:38Z 2018-08-22T15:29:38Z MEMBER

An simpler example: ```python-traceback In [7]: xarray.DataArray(numpy.ma.masked)

ValueError Traceback (most recent call last) <ipython-input-7-485c0cd3cbd8> in <module>() ----> 1 xarray.DataArray(numpy.ma.masked)

~/dev/xarray/xarray/core/dataarray.py in init(self, data, coords, dims, name, attrs, encoding, fastpath) 224 encoding = getattr(data, 'encoding', None) 225 --> 226 data = as_compatible_data(data) 227 coords, dims = _infer_coords_and_dims(data.shape, coords, dims) 228 variable = Variable(dims, data, attrs, encoding, fastpath=True)

~/dev/xarray/xarray/core/variable.py in as_compatible_data(data, fastpath) 180 dtype, fill_value = dtypes.maybe_promote(data.dtype) 181 data = np.asarray(data, dtype=dtype) --> 182 data[mask] = fill_value 183 else: 184 data = np.asarray(data)

ValueError: assignment destination is read-only ```

I think we could fix this by using xarray.core.duck_array_ops.where_method(data, ~mask) in as_compatible_data(), which should handle scalars properly.

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Comparing scalar xarray with ma.masked fails with ValueError: assignment destination is read-only 352999600

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]);