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 1087160635,I_kwDOAMm_X85AzME7,6103,reindex multidimensional fill_value skipping,1191149,closed,0,,,1,2021-12-22T20:14:00Z,2021-12-22T20:17:39Z,2021-12-22T20:17:38Z,CONTRIBUTOR,,,,"**What happened**: I started with a Dataframe that represented an identity matrix and used reindex with multiple dimensions and a fill_value. The goal was to produce a Dataset from a sparse dataframe and the identity matrix was the simplest example. The `fill_value` in reindex is defined as ""Value to use for newly missing values."" What I found was that fill_values were not applied at coordinates that were in the unique set of the any coord. For a pure identity matrix, that means fill_values were not applied anywhere (all rows are present, all cols are present). When I thin the identity matrix (skipping elements), the error is more obvious. On the rows and columns that have valid input data, the fill_value is not applied. **What you expected to happen**: I expected *all* new nan values to be filled with the fill value. **Minimal Complete Verifiable Example**: ``` import numpy as np import pandas as pd n = 10 thin = 2 df = pd.DataFrame.from_dict([ dict(ROW=v, COL=v, LAND=1) for v in np.arange(0, n, thin) ]).set_index(['ROW', 'COL']) ds = df.to_xarray() rds = ds.reindex(ROW=np.arange(n), COL=np.arange(n), fill_value=0) # p = rds.LAND.plot() # p.axes.set_facecolor('red') # p.axes.figure.savefig('test.png') print(rds.LAND[:]) print(rds.LAND[::thin, ::thin]) ``` Output: ``` array([[ 1., 0., nan, 0., nan, 0., nan, 0., nan, 0.], [ 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], [nan, 0., 1., 0., nan, 0., nan, 0., nan, 0.], [ 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], [nan, 0., nan, 0., 1., 0., nan, 0., nan, 0.], [ 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], [nan, 0., nan, 0., nan, 0., 1., 0., nan, 0.], [ 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], [nan, 0., nan, 0., nan, 0., nan, 0., 1., 0.], [ 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.]]) Coordinates: * ROW (ROW) int64 0 1 2 3 4 5 6 7 8 9 * COL (COL) int64 0 1 2 3 4 5 6 7 8 9 array([[ 1., nan, nan, nan, nan], [nan, 1., nan, nan, nan], [nan, nan, 1., nan, nan], [nan, nan, nan, 1., nan], [nan, nan, nan, nan, 1.]]) Coordinates: * ROW (ROW) int64 0 2 4 6 8 * COL (COL) int64 0 2 4 6 8``` **Anything else we need to know?**: **Environment**:
Output of xr.show_versions() INSTALLED VERSIONS ------------------ commit: None python: 3.7.12 (default, Sep 10 2021, 00:21:48) [GCC 7.5.0] python-bits: 64 OS: Linux OS-release: 5.4.144+ machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_US.UTF-8 LOCALE: ('en_US', 'UTF-8') libhdf5: 1.12.0 libnetcdf: 4.7.4 xarray: 0.18.2 pandas: 1.1.5 numpy: 1.19.5 scipy: 1.4.1 netCDF4: 1.5.8 pydap: None h5netcdf: None h5py: 3.1.0 Nio: None zarr: None cftime: 1.5.1.1 nc_time_axis: None PseudoNetCDF: None rasterio: None cfgrib: None iris: None bottleneck: 1.3.2 dask: 2.12.0 distributed: 1.25.3 matplotlib: 3.2.2 cartopy: None seaborn: 0.11.2 numbagg: None pint: None setuptools: 57.4.0 pip: 21.1.3 conda: None pytest: 3.6.4 IPython: 5.5.0 sphinx: 1.8.6
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6103/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue 517522619,MDExOlB1bGxSZXF1ZXN0MzM2NTc1NzYx,3485,uamiv test using only raw uamiv variables,1191149,closed,0,,,2,2019-11-05T03:07:14Z,2019-11-05T15:42:36Z,2019-11-05T15:42:35Z,CONTRIBUTOR,,0,pydata/xarray/pulls/3485,"Previous test relied on CF generated metadata, but this test is more robust. - [x] Addresses #3409 #3420 #3434 - [x] Tests fixed Development machine is missing python3.6 environment, using azure to check. This should help me get this fix in faster.","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/3485/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 296561316,MDExOlB1bGxSZXF1ZXN0MTY4NzE1OTQy,1905,Added PNC backend to xarray ,1191149,closed,0,,,34,2018-02-12T23:26:36Z,2018-06-01T11:40:58Z,2018-06-01T04:21:44Z,CONTRIBUTOR,,0,pydata/xarray/pulls/1905,"PNC is used for GEOS-Chem, CAMx, CMAQ and other atmospheric data formats including NOAA arl packed bit and HYSPLIT related files. The goal is to provide access to many file types that have their own file formats and meta-data conventions. It can provide a CF compliant netCDF-like interface. - [x] Tests were run using example datasets, but datasets were not added to repository as they are large and diverse. Only files that provide CF compliant structures will successfully open. Confirmed by @bbakernoaa - [x] Tests added (for all bug fixes or enhancements) - [x] Tests passed (for all non-documentation changes) - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API (remove if this change should not be visible to users, e.g., if it is an internal clean-up, or if this is part of a larger project that will be documented later) ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/1905/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 309592370,MDU6SXNzdWUzMDk1OTIzNzA=,2025,dask ImportWarning causes pytest failure,1191149,closed,0,,,2,2018-03-29T02:01:50Z,2018-03-30T03:44:55Z,2018-03-30T03:44:55Z,CONTRIBUTOR,,,,"#### Code Sample, a copy-pastable example if possible ```bash # Your code here pytest -v xarray/tests/test_backends.py::NetCDF4DataTest ``` #### Problem description Instead of passing all tests, this fails on the `test_88_character_filename_segmentation_fault` function. ``` E AssertionError: exception ImportWarning(""can't resolve package from __spec__ or __package__, falling back on __name__ and __path__"",) did not match pattern 'segmentation fault' ``` It oddly doesn't seem to be related to the 88 character issue. I traced this down to xarray/backends/common.py::get_scheduler where an ""ImportWarning"" is not being caught on line 49. #### Expected Output Passes all tests. Adding ImportWarning to the tuple of exceptions in get_scheduler fixes the problem. #### Output of ``xr.show_versions()``
# Paste the output here xr.show_versions() here >>> xr.show_versions() /Users/barronh/anaconda3/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`. from ._conv import register_converters as _register_converters INSTALLED VERSIONS ------------------ commit: None python: 3.6.4.final.0 python-bits: 64 OS: Darwin OS-release: 17.4.0 machine: x86_64 processor: i386 byteorder: little LC_ALL: None LANG: en_US.UTF-8 LOCALE: en_US.UTF-8 xarray: 0.10.2 pandas: 0.22.0 numpy: 1.14.2 scipy: 1.0.0 netCDF4: 1.3.1 h5netcdf: None h5py: 2.7.1 Nio: None zarr: None bottleneck: 1.2.1 cyordereddict: None dask: 0.17.1 distributed: 1.21.3 matplotlib: 2.2.2 cartopy: None seaborn: 0.8.1 setuptools: 38.4.0 pip: 9.0.1 conda: 4.5.0 pytest: 3.4.2 IPython: 6.2.1 sphinx: 1.6.6
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