BUG: .values upcasts dtype in non-mixed-dtype subset of mixed-dtype DataFrames
- [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] (optional) I have confirmed this bug exists on the master branch of pandas.

---

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

```python
import pandas as pd

data = pd.DataFrame({"a": [1], "b": [0.1]})


print(type(data.loc[0, "a"]))  # <class 'numpy.int64'>
print(data.loc[0, ["a"]].values.dtype)  # float64
```

#### Problem description

`.values` seems to upcast dtype to a common dtype even when only a subset of columns (with the same dtype) are exported?

#### Expected Output

int64 for the second print.

#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit           : db08276bc116c438d3fdee492026f8223584c477
python           : 3.8.6.final.0
python-bits      : 64
OS               : Linux
OS-release       : 4.13.0-36-generic
Version          : #40~16.04.1-Ubuntu SMP Fri Feb 16 23:25:58 UTC 2018
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.1.3
numpy            : 1.19.2
pytz             : 2020.1
dateutil         : 2.8.1
pip              : 20.2.1
setuptools       : 49.2.1
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : None
IPython          : 7.18.1
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : 3.3.2
numexpr          : 2.7.1
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
pyxlsb           : None
s3fs             : None
scipy            : 1.5.3
sqlalchemy       : None
tables           : 3.6.1
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : None


</details>
