BUG: apply for series of numpy arrays falis with np functions
- [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.

---

**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

df = pd.DataFrame({"col": [np.array([.1, .2], dtype=float)]})
np.sin(df['col'].iloc[0])   # This works fine
df["col"].apply(np.sin)     # This breaks
```
Raises:

```python
AttributeError: 'numpy.ndarray' object has no attribute 'sin'

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "~/main.py", line 6, in <module>
    df["col"].apply(np.sin)
  File "~/anaconda3/envs/pandas-issue/lib/python3.7/site-packages/pandas/core/series.py", line 3840, in apply
    return f(self)
  File "~/anaconda3/envs/pandas-issue/lib/python3.7/site-packages/pandas/core/series.py", line 679, in __array_ufunc__
    result = getattr(ufunc, method)(*inputs, **kwargs)
TypeError: loop of ufunc does not support argument 0 of type numpy.ndarray which has no callable sin method
```

#### Problem description

When I have a pd.Series where each row is a numerical numpy array, I can't apply numpy functions to them, I tried np.sin, np.cos, np.exp, but I think it's a general problem. I can apply them to individual rows manually and it works fine.

Moreover, If I import tqdm with tqdm.pandas and use progress_apply instead of apply it also works just fine!

#### Expected Output
```
0    [0.09983341664682815, 0.19866933079506122]
Name: col, dtype: object
```

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

<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.7.6.final.0
python-bits      : 64
OS               : Linux
OS-release       : 5.3.0-46-generic
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.0.3
numpy            : 1.18.1
pytz             : 2019.3
dateutil         : 2.8.1
pip              : 20.0.2
setuptools       : 46.1.3.post20200325
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : None
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           : None
s3fs             : None
scipy            : None
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
xlsxwriter       : None
numba            : None

</details>
