issues
4 rows where state = "closed" and user = 19226431 sorted by updated_at descending
This data as json, CSV (advanced)
Suggested facets: closed_at, created_at (date), updated_at (date), closed_at (date)
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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1331855489 | PR_kwDOAMm_X8480Dc3 | 6889 | Harmonize returned multi-indexed indexes when applying `concat` along new dimension | FabianHofmann 19226431 | closed | 0 | 6 | 2022-08-08T13:12:45Z | 2022-08-25T14:12:55Z | 2022-08-25T11:15:54Z | CONTRIBUTOR | 0 | pydata/xarray/pulls/6889 |
In the current implementation, the It can be fixed by not removing the index name from the list of indexes which should be merged, see https://github.com/pydata/xarray/blob/9050a8b9efc28142b762475c7285603a87b00e83/xarray/core/concat.py#L493. All indexes contained in this list will get a new index object. Currently, this list only contains the levels of a multi-indexed index, not the index name itself. This is removed as it is contained in |
{ "url": "https://api.github.com/repos/pydata/xarray/issues/6889/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
xarray 13221727 | pull | |||||
1330149534 | I_kwDOAMm_X85PSHie | 6881 | Alignment of dataset with MultiIndex fails after applying xr.concat | FabianHofmann 19226431 | closed | 0 | 0 | 2022-08-05T16:42:05Z | 2022-08-25T11:15:55Z | 2022-08-25T11:15:55Z | CONTRIBUTOR | What happened?After applying the The error is raised in the alignment module. It seems that the function What did you expect to happen?I expected the alignment to be functional and that these basic functions work. Minimal Complete Verifiable Example```Python import xarray as xr import pandas as pd index = pd.MultiIndex.from_product([[1,2], ['a', 'b']], names=('level1', 'level2')) index.name = 'dim' var = xr.DataArray(1, coords=[index]) ds = xr.Dataset({"var":var}) new = xr.concat([ds], dim='newdim') xr.Dataset(new) # breaks new.reindex_like(new) # breaks ``` MVCE confirmation
Relevant log output```Python Traceback (most recent call last): File "/tmp/ipykernel_407170/4030736219.py", line 11, in <cell line: 11> xr.Dataset(new) # breaks File "/home/fabian/.miniconda3/lib/python3.10/site-packages/xarray/core/dataset.py", line 599, in init variables, coord_names, dims, indexes, _ = merge_data_and_coords( File "/home/fabian/.miniconda3/lib/python3.10/site-packages/xarray/core/merge.py", line 575, in merge_data_and_coords return merge_core( File "/home/fabian/.miniconda3/lib/python3.10/site-packages/xarray/core/merge.py", line 752, in merge_core aligned = deep_align( File "/home/fabian/.miniconda3/lib/python3.10/site-packages/xarray/core/alignment.py", line 827, in deep_align aligned = align( File "/home/fabian/.miniconda3/lib/python3.10/site-packages/xarray/core/alignment.py", line 764, in align aligner.align() File "/home/fabian/.miniconda3/lib/python3.10/site-packages/xarray/core/alignment.py", line 550, in align self.assert_no_index_conflict() File "/home/fabian/.miniconda3/lib/python3.10/site-packages/xarray/core/alignment.py", line 319, in assert_no_index_conflict raise ValueError( ValueError: cannot re-index or align objects with conflicting indexes found for the following dimensions: 'dim' (2 conflicting indexes) Conflicting indexes may occur when - they relate to different sets of coordinate and/or dimension names - they don't have the same type - they may be used to reindex data along common dimensions ``` Anything else we need to know?No response Environment
INSTALLED VERSIONS
------------------
commit: None
python: 3.10.5 | packaged by conda-forge | (main, Jun 14 2022, 07:04:59) [GCC 10.3.0]
python-bits: 64
OS: Linux
OS-release: 5.15.0-41-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: ('en_US', 'UTF-8')
libhdf5: 1.12.1
libnetcdf: 4.8.1
xarray: 2022.6.0
pandas: 1.4.2
numpy: 1.21.6
scipy: 1.8.1
netCDF4: 1.6.0
pydap: None
h5netcdf: None
h5py: 3.6.0
Nio: None
zarr: None
cftime: 1.5.1.1
nc_time_axis: None
PseudoNetCDF: None
rasterio: 1.2.10
cfgrib: None
iris: None
bottleneck: 1.3.4
dask: 2022.6.1
distributed: 2022.6.1
matplotlib: 3.5.1
cartopy: 0.20.2
seaborn: 0.11.2
numbagg: None
fsspec: 2022.3.0
cupy: None
pint: None
sparse: 0.13.0
flox: None
numpy_groupies: None
setuptools: 61.2.0
pip: 22.1.2
conda: 4.13.0
pytest: 7.1.2
IPython: 7.33.0
sphinx: 5.0.2
/home/fabian/.miniconda3/lib/python3.10/site-packages/_distutils_hack/__init__.py:30: UserWarning: Setuptools is replacing distutils.
warnings.warn("Setuptools is replacing distutils.")
|
{ "url": "https://api.github.com/repos/pydata/xarray/issues/6881/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
completed | xarray 13221727 | issue | ||||||
1052740367 | PR_kwDOAMm_X84ufPFw | 5984 | preserve chunked data when creating DataArray from DataArray | FabianHofmann 19226431 | closed | 0 | 10 | 2021-11-13T18:21:10Z | 2022-01-13T18:10:57Z | 2022-01-13T17:02:47Z | CONTRIBUTOR | 0 | pydata/xarray/pulls/5984 |
|
{ "url": "https://api.github.com/repos/pydata/xarray/issues/5984/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
xarray 13221727 | pull | |||||
1052736383 | I_kwDOAMm_X84-v3t_ | 5983 | preserve chunked data when creating DataArray from itself | FabianHofmann 19226431 | closed | 0 | 4 | 2021-11-13T18:00:24Z | 2022-01-13T17:02:47Z | 2022-01-13T17:02:47Z | CONTRIBUTOR | What happened: When creating a new DataArray from a DataArray with chunked data, the underlying dask array is converted to a numpy array. What you expected to happen: I expected the underlying dask array to be preseved when creating a new DataArray instance. Minimal Complete Verifiable Example: ```python import xarray as xr import numpy as np from dask import array d = np.ones((10, 10)) x = array.from_array(d, chunks=5) da = xr.DataArray(x) # this is chunked xr.DataArray(da) # this is not chunked anymore ``` Anything else we need to know?: Environment: Output of <tt>xr.show_versions()</tt>INSTALLED VERSIONS ------------------ commit: None python: 3.9.7 (default, Sep 16 2021, 13:09:58) [GCC 7.5.0] python-bits: 64 OS: Linux OS-release: 5.11.0-40-generic machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_US.UTF-8 LOCALE: ('en_US', 'UTF-8') libhdf5: 1.10.6 libnetcdf: 4.7.4 xarray: 0.19.0 pandas: 1.3.3 numpy: 1.20.3 scipy: 1.7.1 netCDF4: 1.5.6 pydap: None h5netcdf: 0.11.0 h5py: 3.2.1 Nio: None zarr: 2.10.1 cftime: 1.5.0 nc_time_axis: None PseudoNetCDF: None rasterio: 1.2.6 cfgrib: None iris: None bottleneck: 1.3.2 dask: 2021.09.1 distributed: 2021.09.1 matplotlib: 3.4.3 cartopy: 0.19.0.post1 seaborn: 0.11.2 numbagg: None pint: None setuptools: 58.0.4 pip: 21.2.4 conda: 4.10.3 pytest: 6.2.5 IPython: 7.27.0 sphinx: 4.2.0 |
{ "url": "https://api.github.com/repos/pydata/xarray/issues/5983/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
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]);