BUG: series max aggregate function throws a TypeError.
- [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

series = pd.Series(['2018-01-01', None])
print(series.max())

```

#### Problem description

The max function skipna parameter defaults to true, which means that the current series only has ["2018-01-01"] when the comparison is actually done, so the max should be 2018-01-01, but an exception is thrown here.

The main error messages: `TypeError: '>=' not supported between instances of 'str' and 'float'`

I debugged the source code and found that the line `nanmax = _nanminmax("max", fill_value_typ="-inf")` converts None to inf by default, which ends up comparing the type types

#### Expected Output
2018-01-01

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

<details>

INSTALLED VERSIONS
------------------
commit           : 821f90c23e88561d6741714428b24c8cd3a21b25
python           : 3.8.6.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 19.6.0
Version          : Darwin Kernel Version 19.6.0: Mon Aug 31 22:12:52 PDT 2020; root:xnu-6153.141.2~1/RELEASE_X86_64
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : en_US.UTF-8
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.2.0.dev0+1025.g821f90c23
numpy            : 1.19.2
pytz             : 2020.1
dateutil         : 2.8.1
pip              : 20.2.1
setuptools       : 49.2.1
Cython           : 0.29.21
pytest           : 6.1.1
hypothesis       : 5.37.4
sphinx           : 3.2.1
blosc            : 1.9.2
feather          : None
xlsxwriter       : 1.3.7
lxml.etree       : 4.6.1
html5lib         : 1.1
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.18.1
pandas_datareader: None
bs4              : 4.9.3
bottleneck       : 1.3.2
fsspec           : 0.8.4
fastparquet      : 0.4.1
gcsfs            : 0.7.1
matplotlib       : 3.3.2
numexpr          : 2.7.1
odfpy            : None
openpyxl         : 3.0.5
pandas_gbq       : None
pyarrow          : 2.0.0
pyxlsb           : None
s3fs             : 0.5.1
scipy            : 1.5.3
sqlalchemy       : 1.3.20
tables           : 3.6.1
tabulate         : 0.8.7
xarray           : 0.16.1
xlrd             : 1.2.0
xlwt             : 1.3.0
numba            : 0.51.2
</details>
