BUG: any() and all() behavior on string series is different from python
- [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.

- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.

---

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

```python
pd.Series(["kkkk", "llll"]).any() # "kkkk"
any(["kkkk", "llll"]) # True

pd.Series(["kkkk", "llll"]).all() # "llll"
all(["kkkk", "llll"]) # True
```

#### Problem description

Python returns boolean not the value. So we should follow that.
https://stackoverflow.com/questions/10180344/why-does-python-any-return-a-bool-instead-of-the-value

#### Expected Output

The expected behavior is to match `any` and `all` built-in functions.

https://docs.python.org/3/library/functions.html#any
```python
def any(iterable):
    for element in iterable:
        if element:
            return True
    return False
```
https://docs.python.org/3/library/functions.html#all
```python
def all(iterable):
    for element in iterable:
        if not element:
            return False
    return True
```

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

<details>

INSTALLED VERSIONS
------------------
commit           : 2a7d3326dee660824a8433ffd01065f8ac37f7d6
python           : 3.7.8.final.0
python-bits      : 64
OS               : Linux
OS-release       : 4.19.112+
Version          : #⁠1 SMP Fri Sep 4 12:06:06 PDT 2020
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : en_US.UTF-8
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.1.2
numpy            : 1.19.1
pytz             : 2020.1
dateutil         : 2.8.1
pip              : 20.1.1
setuptools       : 49.2.0.post20200712
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.16.1
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : 3.1.3
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
pyxlsb           : None
s3fs             : None
scipy            : 1.5.2
sqlalchemy       : 1.3.18
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : None
</details>
