BUG: nunique not ignoring both None and np.nan
- [x] I have checked that this issue has not already been reported.

- [ ] 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
import numpy as np
pd.Series(['yes','yes', None, np.nan]).nunique(dropna = True)

```

#### Problem description
The output was 2.
It seems that nunique can only ignore None or np.nan but not both together. This seems odd to me and I think it 
should either be changed or the docs should reflect this.

#### Expected Output
I expected to get 1 as the result but I got 2.
#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit           : db08276bc116c438d3fdee492026f8223584c477
python           : 3.7.6.final.0
python-bits      : 64
OS               : Linux
OS-release       : 5.4.49+
Version          : #1 SMP Sun Oct 18 19:43:35 PDT 2020
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : C.UTF-8
LANG             : C.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.1.3
numpy            : 1.18.5
pytz             : 2019.3
dateutil         : 2.8.1
pip              : 20.2.4
setuptools       : 46.1.3.post20200325
Cython           : 0.29.21
pytest           : 5.4.1
hypothesis       : 5.10.0
sphinx           : 3.0.2
blosc            : None
feather          : 0.4.1
xlsxwriter       : 1.2.8
lxml.etree       : 4.5.0
html5lib         : 1.0.1
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.13.0
pandas_datareader: 0.9.0
bs4              : 4.9.0
bottleneck       : 1.3.2
fsspec           : 0.8.4
fastparquet      : None
gcsfs            : 0.6.1
matplotlib       : 3.2.1
numexpr          : 2.7.1
odfpy            : None
openpyxl         : 3.0.3
pandas_gbq       : None
pyarrow          : 0.16.0
pytables         : None
pyxlsb           : None
s3fs             : 0.5.1
scipy            : 1.4.1
sqlalchemy       : 1.3.16
tables           : 3.6.1
tabulate         : 0.8.7
xarray           : 0.16.1
xlrd             : 1.2.0
xlwt             : 1.3.0
numba            : 0.48.0

</details>
