Pandas BUG: Inconsistent .values NA/NaN

Pandas version checks

• [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.

• [x] I have confirmed this bug exists on the main branch of pandas.

Reproducible Example

import pandas as pd

ser = pd.Series([1, pd.NA], dtype=pd.Float64Dtype())
df = pd.DataFrame({"A": ser, "B": ["foo", "bar"]})

>>> df[["A"]].values[1,0]
np.float64(nan)

>>> df.values[1,0]
<NA>

Issue Description

When another column forces .values to be object dtype we retain pd.NA, otherwise we cast to NaN.
Same behavior with Int64Dtype.

Expected Behavior

This should be consistent.

Installed Versions

Replace this line with the output of pd.show_versions()

Comment From: skonda29

Hi! Is anyone working on this issue? I'd like to take it up if it's available.

Comment From: jbrockmendel

This is not ready to be worked on. We suggest looking for an issue with the "good first issue" label