BUG: ValueError when assigning list in a single-row object dataframe  
- [ X ] I have checked that this issue has not already been reported. #15490 looks kind of similar, but seems like it was fixed. #17256 is also similar but it uses deprecated methods.

- [ X ] I have confirmed this bug exists on the latest version of pandas.

---

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

```python
import pandas as pd

df = pd.DataFrame([['a', '1', '2.0']], columns=['a', 'b', 'c'], dtype=object)
df['c'].iloc[0] = [df['c'].iloc[0]]         
```

#### Problem description

The current behaviour raises a ValueError, even though the assignment happened. Stack trace:


<details>

```python
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-1-12824bd17b66> in <module>()
      2 
      3 df = pd.DataFrame([['a', '1', '2.0']], columns=['a', 'b', 'c'], dtype=object)
----> 4 df['c'].iloc[0] = [df['c'].iloc[0]]

4 frames
/usr/local/lib/python3.6/dist-packages/pandas/core/indexing.py in __setitem__(self, key, value)
    668 
    669         iloc = self if self.name == "iloc" else self.obj.iloc
--> 670         iloc._setitem_with_indexer(indexer, value)
    671 
    672     def _validate_key(self, key, axis: int):

/usr/local/lib/python3.6/dist-packages/pandas/core/indexing.py in _setitem_with_indexer(self, indexer, value)
   1800             # actually do the set
   1801             self.obj._consolidate_inplace()
-> 1802             self.obj._mgr = self.obj._mgr.setitem(indexer=indexer, value=value)
   1803             self.obj._maybe_update_cacher(clear=True)
   1804 

/usr/local/lib/python3.6/dist-packages/pandas/core/internals/managers.py in setitem(self, indexer, value)
    532 
    533     def setitem(self, indexer, value) -> "BlockManager":
--> 534         return self.apply("setitem", indexer=indexer, value=value)
    535 
    536     def putmask(

/usr/local/lib/python3.6/dist-packages/pandas/core/internals/managers.py in apply(self, f, align_keys, **kwargs)
    404                 applied = b.apply(f, **kwargs)
    405             else:
--> 406                 applied = getattr(b, f)(**kwargs)
    407             result_blocks = _extend_blocks(applied, result_blocks)
    408 

/usr/local/lib/python3.6/dist-packages/pandas/core/internals/blocks.py in setitem(self, indexer, value)
    885             values[indexer] = value
    886 
--> 887             values = values.astype(arr_value.dtype, copy=False)
    888 
    889         # set

ValueError: setting an array element with a sequence
```

</details>


#### Expected Output

As the `dtype` is `object`, I would have expected this assignment to happen without raising a ValueError. If the dataframe has more than one row:

```python
df = pd.DataFrame([['a', '1', '2.0']]*2, columns=['a', 'b', 'c'])
df['c'].iloc[0] = [df['c'].iloc[0]]
```

Then the exception is not thrown.

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

<details>

INSTALLED VERSIONS
------------------
commit           : db08276bc116c438d3fdee492026f8223584c477
python           : 3.6.9.final.0
python-bits      : 64
OS               : Linux
OS-release       : 4.19.112+
Version          : #1 SMP Thu Jul 23 08:00:38 PDT 2020
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.1.3
numpy            : 1.18.5
pytz             : 2018.9
dateutil         : 2.8.1
pip              : 19.3.1
setuptools       : 50.3.0
Cython           : 0.29.21
pytest           : 3.6.4
hypothesis       : None
sphinx           : 1.8.5
blosc            : None
feather          : 0.4.1
xlsxwriter       : None
lxml.etree       : 4.2.6
html5lib         : 1.0.1
pymysql          : None
psycopg2         : 2.7.6.1 (dt dec pq3 ext lo64)
jinja2           : 2.11.2
IPython          : 5.5.0
pandas_datareader: 0.9.0
bs4              : 4.6.3
bottleneck       : 1.3.2
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : 3.2.2
numexpr          : 2.7.1
odfpy            : None
openpyxl         : 2.5.9
pandas_gbq       : 0.13.3
pyarrow          : 0.14.1
pytables         : None
pyxlsb           : None
s3fs             : None
scipy            : 1.4.1
sqlalchemy       : 1.3.20
tables           : 3.4.4
tabulate         : 0.8.7
xarray           : 0.15.1
xlrd             : 1.1.0
xlwt             : 1.3.0
numba            : 0.48.0

</details>
