Backport PR #43150 on branch 1.3.x (BUG: GroupBy.quantile fails with pd.NA)
Backport PR #43150
@jreback @simonjayhawkins 
There is a difference in what's happening with the index when df has nullable dtypes in 1.3.x vs. master (comparison below).

So I think there are two options 
1. backport the PR which changes this behaviour (I was not able to find the PR though).
2. hardcode the test to pass (which I don't think we should do).

```
In [60]: pd.__version__
Out[60]: '1.3.2+16.g6a54ac4a0a'

In [61]: df = DataFrame({"x": [1, 1], "y": [0.2, np.nan]})

In [62]: df.dtypes
Out[62]: 
x      int64
y    float64
dtype: object

In [63]: df.groupby("x")["y"].quantile(0.5).index
Out[63]: Int64Index([1], dtype='int64', name='x')

In [64]: df=df.astype({"x":"Int64"})

In [65]: df.dtypes
Out[65]: 
x      Int64
y    float64
dtype: object

In [66]: df.groupby("x")["y"].quantile(0.5).index
Out[66]: Index([1], dtype='object', name='x')
```

```In [13]: pd.__version__
Out[13]: '1.4.0.dev0+598.g35d52ff2d5'

In [14]: df = DataFrame({"x": [1, 1], "y": [0.2, np.nan]})

In [15]: df.dtypes
Out[15]: 
x      int64
y    float64
dtype: object

In [16]: df.groupby("x")["y"].quantile(0.5).index
Out[16]: Int64Index([1], dtype='int64', name='x')

In [17]: df=df.astype({"x":"Int64"})

In [18]: df.dtypes
Out[18]: 
x      Int64
y    float64
dtype: object

In [19]: df.groupby("x")["y"].quantile(0.5).index
Out[19]: Int64Index([1], dtype='int64', name='x')
 thanks @debnathshoham 