issues

Table actions

2 rows where type = "issue" and user = 1997005 sorted by updated_at descending

✎ View and edit SQL

This data as json, CSV (advanced)

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

type 1

  • issue · 2 ✖

state 1

repo 1

id node_id number title user state locked assignee milestone comments created_at updated_at ▲ closed_at author_association active_lock_reason draft pull_request body reactions performed_via_github_app state_reason repo type
301795163 MDU6SXNzdWUzMDE3OTUxNjM= 1952 xarray.merge exception : invalid type promotion NotSqrt 1997005 closed 0     4 2018-03-02T15:02:43Z 2018-08-20T16:31:16Z 2018-08-20T16:31:16Z CONTRIBUTOR      

Code Sample

```python import xarray import pandas import numpy

array1 = xarray.DataArray( [numpy.timedelta64('NaT')], dims=['time'], coords={'time': pandas.to_datetime(['2018-01-01'])}, name='foo' )

array2 = xarray.DataArray( [numpy.timedelta64(30, 's')], dims=['time'], coords={'time': pandas.to_datetime(['2018-01-02'])}, name='foo' )

xarray.merge([array1, array2]) ```

Problem description

Merging arrays with identical dtypes should work ...

There's some issue with the NaT being interpreted as float64, so that xarray.core.dtypes.result_type thinks that those 2 arrays are not compatible..

It works with xarray==0.10.0 and fails at xarray==0.10.1. I've pin-pointed the issue to commit 2aa5b8a5c0945935.

Work-around in the mean time : python xarray.merge([array1.astype(float), array2.astype(float)]).astype('timedelta64')

Expected Output

```python

expected :

xarray.DataArray( [numpy.timedelta64('NaT'), numpy.timedelta64(30, 's')], dims=['time'], coords={'time': pandas.to_datetime(['2018-01-01', '2018-01-02'])}, name='foo' ) ```

Output of xr.show_versions()

INSTALLED VERSIONS ------------------ commit: None python: 3.6.2.final.0 python-bits: 64 OS: Linux OS-release: 3.13.0-142-generic machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: fr_FR.UTF-8 LOCALE: fr_FR.UTF-8 xarray: 0.10.0+dev60.g2aa5b8a pandas: 0.22.0 numpy: 1.14.0 scipy: None netCDF4: 1.3.1 h5netcdf: None h5py: None Nio: None zarr: None bottleneck: None cyordereddict: None dask: None distributed: None matplotlib: 2.1.1 cartopy: None seaborn: None setuptools: 38.4.0 pip: 9.0.1 conda: None pytest: 3.3.2 IPython: 6.2.1 sphinx: None

Thanks !

 
{
    "url": "https://api.github.com/repos/pydata/xarray/issues/1952/reactions",
    "total_count": 1,
    "+1": 1,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   completed xarray 13221727 issue
220241754 MDU6SXNzdWUyMjAyNDE3NTQ= 1359 Bug: open_dataarray does not pass properly its parameters to open_dataset NotSqrt 1997005 closed 0   v0.9.3 2444330 1 2017-04-07T15:06:50Z 2017-04-12T22:28:35Z 2017-04-12T22:28:35Z CONTRIBUTOR      

Hi,

There's now a autoclose parameter to the open_dataset function. But open_dataarray uses positional arguments only, so now the arguments are no longer at their place, and engine, for instance, can't be specified.

Thanks !

 
{
    "url": "https://api.github.com/repos/pydata/xarray/issues/1359/reactions",
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   completed xarray 13221727 issue

Advanced export

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

CSV options: 

CREATE TABLE [issues] (
   [id] INTEGER PRIMARY KEY,
   [node_id] TEXT,
   [number] INTEGER,
   [title] TEXT,
   [user] INTEGER REFERENCES [users]([id]),
   [state] TEXT,
   [locked] INTEGER,
   [assignee] INTEGER REFERENCES [users]([id]),
   [milestone] INTEGER REFERENCES [milestones]([id]),
   [comments] INTEGER,
   [created_at] TEXT,
   [updated_at] TEXT,
   [closed_at] TEXT,
   [author_association] TEXT,
   [active_lock_reason] TEXT,
   [draft] INTEGER,
   [pull_request] TEXT,
   [body] TEXT,
   [reactions] TEXT,
   [performed_via_github_app] TEXT,
   [state_reason] TEXT,
   [repo] INTEGER REFERENCES [repos]([id]),
   [type] TEXT
);
CREATE INDEX [idx_issues_repo]
    ON [issues] ([repo]);
CREATE INDEX [idx_issues_milestone]
    ON [issues] ([milestone]);
CREATE INDEX [idx_issues_assignee]
    ON [issues] ([assignee]);
CREATE INDEX [idx_issues_user]
    ON [issues] ([user]);