BUG: Groupby.any(skipna=True)
- [x] I have checked that this issue has not already been reported.

- [x] I have confirmed this bug exists on the latest version of pandas.

- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.

---

**Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your bug.

#### Code Sample, a copy-pastable example

```python
import pandas as pd


def test_groupby_any():
    df = pd.DataFrame(
        {
            "ids": ["id1", "id1", "id2", "id2"],
            "A": [True, False, pd.NA, True]
        }
    ).astype({"ids": pd.StringDtype(),
              "A": pd.BooleanDtype()})

    result = df.groupby("ids").any(skipna=True)

    expected = pd.DataFrame(
        {
            "A": [True, True]
        }, index=pd.Series(["id1", "id2"], name="ids")
    )

    pd.testing.assert_frame_equal(expected, result)

```

#### Problem description

When running df.groupby(field_to_group_on).any(skipna=True) it should be expected that pd.NA values are neglected for the .any() method. However the output is this:

self = <BooleanArray>
[True, False, <NA>, True]
Length: 4, dtype: boolean
dtype = dtype('bool'), copy = True

    def astype(self, dtype, copy: bool = True) -> ArrayLike:
        """
        Cast to a NumPy array or ExtensionArray with 'dtype'.
    
        Parameters
        ----------
        dtype : str or dtype
            Typecode or data-type to which the array is cast.
        copy : bool, default True
            Whether to copy the data, even if not necessary. If False,
            a copy is made only if the old dtype does not match the
            new dtype.
    
        Returns
        -------
        ndarray or ExtensionArray
            NumPy ndarray, BooleanArray or IntegerArray with 'dtype' for its dtype.
    
        Raises
        ------
        TypeError
            if incompatible type with an BooleanDtype, equivalent of same_kind
            casting
        """
        from pandas.core.arrays.string_ import StringDtype
    
        dtype = pandas_dtype(dtype)
    
        if isinstance(dtype, BooleanDtype):
            values, mask = coerce_to_array(self, copy=copy)
            if not copy:
                return self
            else:
                return BooleanArray(values, mask, copy=False)
        elif isinstance(dtype, StringDtype):
            return dtype.construct_array_type()._from_sequence(self, copy=False)
    
        if is_bool_dtype(dtype):
            # astype_nansafe converts np.nan to True
            if self._hasna:
>               raise ValueError("cannot convert float NaN to bool")
E               ValueError: cannot convert float NaN to bool

#### Expected Output

```
    expected = pd.DataFrame(
        {
            "A": [True, True]
        }, index=pd.Series(["id1", "id2"], name="ids")
    )
```
#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit           : f2c8480af2f25efdbd803218b9d87980f416563e
python           : 3.9.1.final.0
python-bits      : 64
OS               : Windows
OS-release       : 10
Version          : 10.0.19041
machine          : AMD64
processor        : Intel64 Family 6 Model 85 Stepping 4, GenuineIntel
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : English_United States.1252
pandas           : 1.2.3
numpy            : 1.20.1
pytz             : 2021.1
dateutil         : 2.8.1
pip              : 21.0.1
setuptools       : 52.0.0
Cython           : None
pytest           : 6.2.2
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.3
IPython          : None
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : None
numexpr          : None
odfpy            : None
openpyxl         : 3.0.7
pandas_gbq       : None
pyarrow          : None
pyxlsb           : None
s3fs             : None
scipy            : 1.6.1
sqlalchemy       : 1.4.2
tables           : None
tabulate         : None
xarray           : None
xlrd             : 1.2.0
xlwt             : None
numba            : None

</details>
