Applying groupby and aggregating with nunique over float column with nulls unexpectedly changes dataframe
#### 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( [[1, 0], [2, np.nan], [3, np.nan]], columns=['a', 'b'] )
print( df )
#   a    b
# 0  1  0.0
# 1  2  NaN
# 2  3  NaN
unused = df.groupby('a').agg({'b': 'nunique'})     # this shouldn't change anything in df, right?
print( df ) # prints out
#   a             b
# 0  1  0.000000e+00
# 1  2 -9.223372e+18
# 2  3 -9.223372e+18
# what happened to my nans?
```
#### Problem description

For some reason the agg, groupby operation is changing the orginal nan values in the b column 
to a special float value. 
In the previous version of pandas I was using, this didn't happen.

### Expected Output
The expected output of the  print should the same as the one of the first print as groupby + agg should never change the input df (right?)

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

<details>
[paste the output of ``pd.show_versions()`` here below this line]

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.7.6.final.0
python-bits      : 64
OS               : Linux
OS-release       : 4.15.0-70-generic
machine          : x86_64
processor        : 
byteorder        : little
LC_ALL           : None
LANG             : sv_SE.UTF-8
LOCALE           : sv_SE.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           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : 2.8.4 (dt dec pq3 ext lo64)
jinja2           : 2.11.1
IPython          : None
pandas_datareader: None
bs4              : None
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : None
matplotlib       : None
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
pytest           : None
pyxlsb           : 1.0.6
s3fs             : None
scipy            : 1.4.1
sqlalchemy       : 1.3.13
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
xlsxwriter       : None
numba            : None
</details>
