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
1374911473,I_kwDOAMm_X85R83vx,7042,Xarray returns duplicate Longitude/Latitude values with sel method ,11867798,closed,1,,,5,2022-09-15T18:18:27Z,2022-09-19T05:56:34Z,2022-09-19T05:56:34Z,NONE,,,,"### What is your issue?

I am trying to select air temperature from Netcdf file and polgon regions from NUTS3 shape file with the aim of masking both to extract the values. However, for some regions, xarray returns a data frame with the same latitude or longitude values which cannot be masked by geopandas. The shape file and the netcdf I am using are zipped here

Here is the code:
import os
import math
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import cartopy.crs as ccrs
import cartopy.feature as cfeature
import seaborn as sn
import geopandas as gpd
import earthpy as et
import xarray as xr
import regionmask
from sultan.api import Sultan
#Plotting options
sn.set(font_scale=1.3)
sn.set_style(""white"")

nc_file = xr.open_mfdataset('year2019.nc') #, chunks = {'time': 10})
shapefile = ""NUTS_RG_60M_2021_4326/NUTS_RG_60M_2021_4326.shp""
countries = gpd.read_file(shapefile)
querry = 3
countries = countries[countries['LEVL_CODE'] == querry]

```#Select the longitude and latitude coordinates of the region of interest in the shape file.```
#These values will be passed to xarray
german_state = countries[countries.NUTS_ID.isin([""DE255""])]
german_state.plot()
boundaries = german_state.total_bounds
print(boundaries)

ger_mask = regionmask.mask_3D_geopandas(german_state, nc_file.longitude, nc_file.latitude, method=""pygeos"")
print(ger_mask)
state_lat = [float(boundaries[1]), float(boundaries[3])]
print(""Boundary Latitude"", state_lat)
state_lon = [float(boundaries[0]), float(boundaries[2])]
print("" Boundary Longitude"", state_lon)
print(state_lat, state_lon)

```#Slice the data by time and spatial extent by passing the values selected from the shape file```
two_months_255 = nc_file[""tg""].sel(
    longitude=[state_lon[0], state_lon[1]],
    latitude=[state_lat[0], state_lat[1]], method=""nearest"")

two_months_255.where(ger_mask)


```python
Error:
File /opt/homebrew/lib/python3.9/site-packages/xarray/core/indexes.py:449, in PandasIndex.reindex_like(self, other, method, tolerance)
    445 def reindex_like(
    446     self, other: PandasIndex, method=None, tolerance=None
    447 ) -> dict[Hashable, Any]:
    448     if not self.index.is_unique:
--> 449         raise ValueError(
    450             f""cannot reindex or align along dimension {self.dim!r} because the ""
    451             ""(pandas) index has duplicate values""
    452         )
    454     return {self.dim: get_indexer_nd(self.index, other.index, method, tolerance)}

ValueError: cannot reindex or align along dimension 'latitude' because the (pandas) index has duplicate values
```

[ask.zip](https://github.com/pydata/xarray/files/9577936/ask.zip)
<img width=""916"" alt=""Screenshot 2022-09-15 at 20 08 18"" src=""https://user-images.githubusercontent.com/11867798/190479789-9104c2e4-04dc-45a6-8993-93a56018cee8.png"">
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