error that converts nan to non-nan float value via groupby and nunique
#### Code Sample, a copy-pastable example if possible

```python
import pandas as pd
import numpy as np
print(pd.__version__)
>> '1.0.1'
df = pd.DataFrame({'a':[1,2,3], 'b':[np.nan, np.nan, np.nan], 'c':['d', 'e', 'f']}, index=[0, 1, 2])
print(df)
print(df.loc[1].b)
# >> nan
df.groupby('a').nunique()
print(df)
#    a             b  c
# 0  1 -9.223372e+18  d
# 1  2 -9.223372e+18  e
# 2  3 -9.223372e+18  f
print(df.c.unique())
print(df)
# print(df.groupby('a').nunique().c.unique())
# >> array([1])
print(df.loc[1].b)
# >> -9.223372036854776e+18
```
#### Problem description

When a `groupby` operation followed by an `nunique` operation, nans are converted to non-nan float values. According to the documentation, the [`nunique`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.nunique.html) function should return a series but should not update the original dataframe. Also according to the documentation you can ignore nans, however this seems to still change the value nans to a non-nan number.

This does not happen if `nunique` is applied without the `groupby` function.

#### Expected Output
The expected output is that nan values should not be converted to any other value based on an aggregrate operation on the dataframe.

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

<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.6.10.final.0
python-bits      : 64
OS               : Linux
OS-release       : 4.15.0-45-generic
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.0.1
numpy            : 1.18.1
pytz             : 2019.3
dateutil         : 2.8.1
pip              : 20.0.2
setuptools       : 45.2.0.post20200210
Cython           : 0.29.15
pytest           : 5.3.5
hypothesis       : 5.4.1
sphinx           : 2.4.0
blosc            : None
feather          : None
xlsxwriter       : 1.2.7
lxml.etree       : 4.5.0
html5lib         : 1.0.1
pymysql          : None
psycopg2         : None
jinja2           : 2.11.1
IPython          : 7.12.0
pandas_datareader: None
bs4              : 4.8.2
bottleneck       : 1.3.1
fastparquet      : None
gcsfs            : None
lxml.etree       : 4.5.0
matplotlib       : 3.1.3
numexpr          : 2.7.1
odfpy            : None
openpyxl         : 3.0.3
pandas_gbq       : None
pyarrow          : None
pytables         : None
pytest           : 5.3.5
pyxlsb           : None
s3fs             : None
scipy            : 1.4.1
sqlalchemy       : 1.3.13
tables           : 3.6.1
tabulate         : None
xarray           : None
xlrd             : 1.2.0
xlwt             : 1.3.0
xlsxwriter       : 1.2.7
numba            : 0.48.0
</details>
