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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
1128304139 I_kwDOAMm_X85DQI4L 6256 Indexing a RangeIndexed' DataArray with a RangeIndex returns a deprecated Int64Index hrzn 4806678 open 0     2 2022-02-09T09:55:06Z 2022-02-21T21:28:57Z   CONTRIBUTOR      

What happened?

First, apology if this is not actually a bug - I'm not too sure of what the intended behaviour should be. But I find this counter-intuitive.

When indexing a DataArray that is indexed using a RangeIndex, the resulting index is an Int64Index: ```python my_da.get_index('time')

RangeIndex(start=0, stop=100, step=1, name='time')

a = my_da.sel({'time': pd.RangeIndex(0,2)}) a.get_index('time')

Int64Index([0, 1], dtype='int64', name='time') ```

Setting the index to the desired RangeIndex using assign_coords() then works. But I find it a bit problematic that sel() returns an Int64Index even when used with a RangeIndex. Also because Int64Index has been recently deprecated in Pandas 1.4.

What did you expect to happen?

I would have expected the resulting DataArray to be indexed with the same RangeIndex used in sel().

Minimal Complete Verifiable Example

```python import xarray as xr import numpy as np import pandas as pd

my_da = xr.DataArray(np.random.rand(100,), dims=('time'), coords={'time': pd.RangeIndex(0, 100)})

print(my_da.get_index('time')) a = my_da.sel({'time': pd.RangeIndex(0,2)}) print(a.get_index('time')) ```

Relevant log output

python RangeIndex(start=0, stop=100, step=1, name='time') Int64Index([0, 1], dtype='int64', name='time')

Anything else we need to know?

No response

Environment

INSTALLED VERSIONS

commit: None python: 3.8.5 (default, Sep 4 2020, 02:22:02) [Clang 10.0.0 ] python-bits: 64 OS: Darwin OS-release: 20.6.0 machine: x86_64 processor: i386 byteorder: little LC_ALL: None LANG: None LOCALE: (None, 'UTF-8') libhdf5: None libnetcdf: None

xarray: 0.20.2 pandas: 1.4.0 numpy: 1.22.1 scipy: 1.7.3 netCDF4: None pydap: None h5netcdf: None h5py: None Nio: None zarr: None cftime: None nc_time_axis: None PseudoNetCDF: None rasterio: None cfgrib: None iris: None bottleneck: None dask: None distributed: None matplotlib: 3.5.1 cartopy: None seaborn: None numbagg: None fsspec: 2021.11.1 cupy: None pint: None sparse: None setuptools: 59.5.0 pip: 21.3.1 conda: None pytest: 6.2.5 IPython: 8.0.1 sphinx: 4.3.2

 
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     xarray 13221727 issue
919798222 MDU6SXNzdWU5MTk3OTgyMjI= 5466 `DataArray.sortby()` discards `freq` component of `DatetimeIndex` hrzn 4806678 open 0     0 2021-06-13T13:22:04Z 2021-06-13T13:22:20Z   CONTRIBUTOR      

What happened:

Calling sortby() on a DataArray indexed with a pd.DatetimeIndex discards the underlying freq component of the pd.DatetimeIndex.

What you expected to happen:

The freq component should probably be kept.

Minimal Complete Verifiable Example:

```python import xarray as xr import numpy as np import pandas as pd

ar = xr.DataArray(np.random.randn(4, 2), dims=('time', 'component'), coords={'time': pd.date_range('20130101', '20130104'), 'component': ['a', 'b']})

print(ar.get_index('time'))

ar_sorted = ar.sortby('time')

print(ar_sorted.get_index('time')) ```

Output for the above snippet (note how the freq becomes None): DatetimeIndex(['2013-01-01', '2013-01-02', '2013-01-03', '2013-01-04'], dtype='datetime64[ns]', name='time', freq='D') DatetimeIndex(['2013-01-01', '2013-01-02', '2013-01-03', '2013-01-04'], dtype='datetime64[ns]', name='time', freq=None)

Anything else we need to know?:

Environment:

Output of <tt>xr.show_versions()</tt> INSTALLED VERSIONS ------------------ commit: None python: 3.8.10 (default, May 19 2021, 11:01:55) [Clang 10.0.0 ] python-bits: 64 OS: Darwin OS-release: 20.3.0 machine: x86_64 processor: i386 byteorder: little LC_ALL: None LANG: None LOCALE: (None, 'UTF-8') libhdf5: 1.10.6 libnetcdf: 4.7.4 xarray: 0.18.2 pandas: 1.2.3 numpy: 1.19.5 scipy: 1.6.2 netCDF4: 1.5.6 pydap: None h5netcdf: None h5py: None Nio: None zarr: None cftime: 1.5.0 nc_time_axis: None PseudoNetCDF: None rasterio: None cfgrib: None iris: None bottleneck: 1.3.2 dask: 2021.05.1 distributed: 2021.05.1 matplotlib: 3.4.1 cartopy: None seaborn: None numbagg: None pint: None setuptools: 52.0.0.post20210125 pip: 21.1.1 conda: None pytest: None IPython: 7.22.0 sphinx: None 
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     xarray 13221727 issue

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