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37 rows where labels_id = 792601028

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Link labels_id issues_id
285294506,792601028 needs mcve 792601028 Couldn't change values for on-disk datasets opened by open_mfdataset() (xarray > 0.8.2) 285294506
361016974,792601028 needs mcve 792601028 Limiting threads/cores used by xarray(/dask?) 361016974
376370028,792601028 needs mcve 792601028 to_dataframe() excessive memory usage 376370028
377947810,792601028 needs mcve 792601028 How do I copy my array forwards in time? 377947810
405487803,792601028 needs mcve 792601028 Unable to construct indexVariable. 405487803
408010761,792601028 needs mcve 792601028 rolling count not working 408010761
417666040,792601028 needs mcve 792601028 Error when oppening netcdf file with open_mfdataset 417666040
423742774,792601028 needs mcve 792601028 Dataset.copy(deep=True) does not deepcopy .attrs 423742774
576337745,792601028 needs mcve 792601028 Errors using to_zarr for an s3 store 576337745
642452713,792601028 needs mcve 792601028 Memory Error  642452713
646130205,792601028 needs mcve 792601028 Keep single-value coordinates as dimensions 646130205
809853736,792601028 needs mcve 792601028 memoryview is too large saving 1.77GB Array 809853736
910844095,792601028 needs mcve 792601028 xarray.open_rasterio 910844095
1050082137,792601028 needs mcve 792601028 `to_zarr(append_dim="time")` appends incorrect datetimes 1050082137
1098241812,792601028 needs mcve 792601028 [Bug]: `numpy` `DeprecationWarning` with `DType` and `xr.testing.assert_all_close()` + Dask 1098241812
1136315478,792601028 needs mcve 792601028 ds.to_netcdf() changes values of variable 1136315478
1191575489,792601028 needs mcve 792601028 Possible race condition writing to zarr store with dask distributed and region kwarg 1191575489
1192449540,792601028 needs mcve 792601028 Unstacking the diagonals of a sequence of matrices raises ValueError: IndexVariable objects must be 1-dimensional 1192449540
1197117301,792601028 needs mcve 792601028 Writing a a dataset to .zarr in a loop makes all the data NaNs 1197117301
1206496679,792601028 needs mcve 792601028 NotImplementedError: Don't yet support nd fancy indexing 1206496679
1221809615,792601028 needs mcve 792601028 these two should equals ,but not , latitude was wrong 1221809615
1222066968,792601028 needs mcve 792601028 processing errror when using xr.dataset[:,::-10,::10] 1222066968
1384226112,792601028 needs mcve 792601028 Convert xarray dataset to pandas dataframe is much slower in newest xarray version 1384226112
1437481995,792601028 needs mcve 792601028 🐛 NetCDF4 RuntimeWarning if xarray is imported before netCDF4 1437481995
1609090149,792601028 needs mcve 792601028 `np.multiply` and `dask.array.multiply` trigger graph computation vs using `+` and `*` operators. 1609090149
1848041822,792601028 needs mcve 792601028 problem plotting my own ROMS model output 1848041822
1876388137,792601028 needs mcve 792601028 Can't Open GRIB file in Google CoLab 1876388137
1888573893,792601028 needs mcve 792601028 groupby bug 1888573893
1975845455,792601028 needs mcve 792601028 Segmentation fault 139 (SIGSEGV) 1975845455
1976092931,792601028 needs mcve 792601028 FileNotFoundError when accessing same file from multiple processes 1976092931
2021679408,792601028 needs mcve 792601028 `ValueError` when writing `NCZarr` datasets using `netcdf4` engine 2021679408
2037869483,792601028 needs mcve 792601028 Reading netcdf file with string coordinates makes IPython kernel crash (netcdf4 engine) 2037869483
2118308210,792601028 needs mcve 792601028 Weird interaction between aggregation and multiprocessing on DaskArrays 2118308210
2188557281,792601028 needs mcve 792601028 Opening zarr dataset with poor connection leads to NaN chunks 2188557281
2228373305,792601028 needs mcve 792601028 Weird behavior of DataSet.where(... , drop=True) 2228373305
2229440952,792601028 needs mcve 792601028 from_array() got an unexpected keyword argument 'inline_array' 2229440952
2230680765,792601028 needs mcve 792601028 Using the xarray.Dataset.where() function takes up a lot of memory 2230680765

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CREATE TABLE [issues_labels] (
   [labels_id] INTEGER REFERENCES [labels]([id]),
   [issues_id] INTEGER REFERENCES [issues]([id]),
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CREATE INDEX [idx_issues_labels_labels_id]
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