BUG: Series.equals fails when comparing numpy arrays to scalars
- [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.

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**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

arr = np.array([1, 2])
s1 = pd.Series([arr, arr])
s2 = s1.copy()

s1[1] = 9
s1.equals(s2) # This throws a ValueError

ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

```

#### Problem description

Series.equals operation fails when comparing two Series that at the same position respectively have a single value and a list. Pandas then throws a ValueError since it cannot compare a single value to a list.

Related issues #20676 and #35237 
 
#### Expected Output
False, since the two series are not equal


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

<details>

INSTALLED VERSIONS
------------------
commit           : 9827ce00f95927ddf6a0565450bc175879454d4e
python           : 3.8.3.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 19.5.0
Version          : Darwin Kernel Version 19.5.0: Tue May 26 20:41:44 PDT 2020; root:xnu-6153.121.2~2/RELEASE_X86_64
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : None.UTF-8

pandas           : 1.1.0.dev0+2088.g9827ce00f
numpy            : 1.18.5
pytz             : 2020.1
dateutil         : 2.8.1
pip              : 20.1.1
setuptools       : 49.2.0.post20200712
Cython           : 0.29.21
pytest           : 5.4.3
hypothesis       : 5.19.1
sphinx           : 3.1.1
blosc            : None
feather          : None
xlsxwriter       : 1.2.9
lxml.etree       : 4.5.2
html5lib         : 1.1
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.16.1
pandas_datareader: None
bs4              : 4.9.1
bottleneck       : 1.3.2
fsspec           : 0.7.4
fastparquet      : 0.4.0
gcsfs            : 0.6.2
matplotlib       : 3.2.2
numexpr          : 2.7.1
odfpy            : None
openpyxl         : 3.0.4
pandas_gbq       : None
pyarrow          : 0.17.1
pytables         : None
pyxlsb           : None
s3fs             : 0.4.2
scipy            : 1.5.0
sqlalchemy       : 1.3.18
tables           : 3.6.1
tabulate         : 0.8.7
xarray           : 0.16.0
xlrd             : 1.2.0
xlwt             : 1.3.0
numba            : 0.50.1

</details>
