issues

Table actions

1 row where state = "open" and user = 6866371 sorted by updated_at descending

✎ View and edit SQL

This data as json, CSV (advanced)

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

type 1

state 1

  • open · 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
436669736 MDU6SXNzdWU0MzY2Njk3MzY= 2916 xr.open_dataset no groups info ThetomekK 6866371 open 0     7 2019-04-24T12:32:15Z 2019-07-13T21:42:34Z   NONE      

Code Sample, a copy-pastable example if possible

I have to write some data to disk using xr.to_netcdf() method. The data must be structured in groups so i use the group key word. Reading the .nc file from disk leads to empty data variables if group not supplied. Here some samples ```python data_ds.to_netcdf(path=savepath,mode='w',format='NETCDF4',group='Audio',engine='netcdf4')

datafromdisk = xr.open_dataset(savepath) datafromdisk

<xarray.Dataset> Dimensions: () Data variables: empty

datafromdisk = xr.open_dataset(savepath,group='Audio')

<xarray.Dataset> Dimensions: (time: 15360000) Coordinates: * time (time) datetime64[ns] 2017-05-30T07:40:00 ... 2017-05-30T07:49:59.992280938 Data variables: audio (time) float32 ... Attributes: unit: Pa

```

Problem description

Actually this is not a real problem, if you keep in mind what data groups are strored in a .nc file. At the moment, i work arround with netCDF4 to get infos about possible groups within a .nc file.

```python

from netCDF4 import Dataset rootgrp = Dataset(savepath) rootgrp

<class 'netCDF4._netCDF4.Dataset'> root group (NETCDF4 data model, file format HDF5): dimensions(sizes): variables(dimensions): groups: Audio

or

rootgrp.groups

OrderedDict([('Audio', <class 'netCDF4._netCDF4.Group'> group /Audio: unit: Pa dimensions(sizes): time(15360000) variables(dimensions): float32 audio(time), float64 time(time) groups: )]) ```

Expected Output

Well, at least something like this i would appreciate: ```python datafromdisk = xr.open_dataset(savepath) datafromdisk

<class 'netCDF4._netCDF4.Dataset'> root group (NETCDF4 data model, file format HDF5): dimensions(sizes): variables(dimensions): groups: Audio ```

Output of xr.show_versions()

INSTALLED VERSIONS ------------------ commit: None python: 3.7.1 | packaged by conda-forge | (default, Mar 13 2019, 13:32:59) [MSC v.1900 64 bit (AMD64)] python-bits: 64 OS: Windows OS-release: 7 machine: AMD64 processor: Intel64 Family 6 Model 60 Stepping 3, GenuineIntel byteorder: little LC_ALL: None LANG: en LOCALE: None.None libhdf5: 1.10.4 libnetcdf: 4.6.2 xarray: 0.12.1 pandas: 0.24.2 numpy: 1.16.2 scipy: 1.2.1 netCDF4: 1.5.0.1 pydap: None h5netcdf: None h5py: None Nio: None zarr: None cftime: 1.0.3.4 nc_time_axis: None PseudonetCDF: None rasterio: None cfgrib: None iris: None bottleneck: 1.2.1 dask: 1.2.0 distributed: 1.27.0 matplotlib: 3.0.3 cartopy: None seaborn: None setuptools: 41.0.0 pip: 19.0.3 conda: None pytest: None IPython: 7.4.0 sphinx: 2.0.1 
{
    "url": "https://api.github.com/repos/pydata/xarray/issues/2916/reactions",
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
     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]);