Unspecific error message when setting singular index with np dtype
#### Code Sample, a copy-pastable example if possible

```python
some_np_array = np.array([43, 56])

# unspecific error message 'TypeError: len() of unsized object':
pd.DataFrame([4324, 345], index=some_np_array[0])
pd.Series([4324, 345], index=some_np_array[0])

# specific error message 'TypeError: Index(...) must be called with a collection of some kind, 5 was passed':
pd.DataFrame([4324, 345], index=5)
pd.Series([4324, 345], index=5)
```
#### Problem description

When passing a non-collection type as an index, pandas typically raises a quite helpful error message of the following form:
`TypeError: Index(...) must be called with a collection of some kind, 5 was passed`

Whereas when passing a non-standard type non-collection item as an index, pandas seems to raise some unspecific and misleading error:
`TypeError: len() of unsized object`

#### Expected Output
Specific error message, even when using np.float64, np.int64 etc. as type of singular values.

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

<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.7.7.final.0
python-bits      : 64
OS               : Windows
OS-release       : 7
machine          : AMD64
processor        : Intel64 Family 6 Model 58 Stepping 9, GenuineIntel
byteorder        : little
LC_ALL           : None
LANG             : en
LOCALE           : None.None

pandas           : 1.0.3
numpy            : 1.18.1
pytz             : 2019.3
dateutil         : 2.8.1
pip              : 20.0.2
setuptools       : 46.1.1.post20200323
Cython           : 0.29.15
pytest           : 5.4.1
hypothesis       : 5.5.4
sphinx           : 2.4.0
blosc            : None
feather          : None
xlsxwriter       : 1.2.8
lxml.etree       : 4.5.0
html5lib         : 1.0.1
pymysql          : None
psycopg2         : None
jinja2           : 2.11.1
IPython          : 7.13.0
pandas_datareader: None
bs4              : 4.8.2
bottleneck       : 1.3.2
fastparquet      : None
gcsfs            : None
lxml.etree       : 4.5.0
matplotlib       : 3.1.3
numexpr          : 2.7.1
odfpy            : None
openpyxl         : 3.0.3
pandas_gbq       : None
pyarrow          : None
pytables         : None
pytest           : 5.4.1
pyxlsb           : None
s3fs             : None
scipy            : 1.4.1
sqlalchemy       : 1.3.15
tables           : 3.6.1
tabulate         : None
xarray           : None
xlrd             : 1.2.0
xlwt             : 1.3.0
xlsxwriter       : 1.2.8
numba            : 0.48.0

</details>
