BUG: Constructing a df using 2D numpy arrays raises misleading error
- [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
>>> a = [[1], [2]]
>>> pd.DataFrame({'a': np.array(a), 'b': np.array(a)}) 
ValueError: If using all scalar values, you must pass an index
```

#### Problem description

Hey all! Thanks for the library, I use pandas on a daily basis.

When attempting to create a DataFrame with a 2-dimensional numpy array as input, a misleading `ValueError: If using all scalar values, you must pass an index` is raised instead of raising an expected `ValueError: Data must be 1-dimensional`.

This behaviour changes slightly if there is more than one array:
```python
>>> import pandas as pd
>>> import numpy as np
>>> a = [[1], [2]]
>>> pd.DataFrame({'a': a, 'b': a})   # No error, both nested lists pass validation and index is extracted
     a    b
0  [1]  [1]
1  [2]  [2]
>>> pd.DataFrame({'a': np.array(a), 'b': a})   # Expected behaviour, the nested list passes the check at pd.core.internals.construction._extract_index
ValueError: Data must be 1-dimensional
>>> pd.DataFrame({'a': np.array(a), 'b': np.array(a)}) 
ValueError: If using all scalar values, you must pass an index
```

I suspect this may have something to do with the check at https://github.com/pandas-dev/pandas/blob/386bad4c900ed09c1b664a341e3081851694ddbc/pandas/core/internals/construction.py#L620 
not being exhaustive and/or that the shape validation only happens after this index creation step.

#### Expected Output

```python
>>> pd.DataFrame({'a': np.array(a), 'b': np.array(a)}) 
ValueError: Data must be 1-dimensional
```

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

<details>

INSTALLED VERSIONS
------------------
commit           : f00ed8f47020034e752baf0250483053340971b0
python           : 3.7.10.final.0
python-bits      : 64
OS               : Linux
OS-release       : 5.4.104+
Version          : #1 SMP Sat Jun 5 09:50:34 PDT 2021
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.3.0
numpy            : 1.19.5
pytz             : 2018.9
dateutil         : 2.8.1
pip              : 19.3.1
setuptools       : 57.0.0
Cython           : 0.29.23
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           : 2.11.3
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          : 2.7.3
odfpy            : None
openpyxl         : 2.5.9
pandas_gbq       : 0.13.3
pyarrow          : 3.0.0
pyxlsb           : None
s3fs             : None
scipy            : 1.4.1
sqlalchemy       : 1.4.20
tables           : 3.4.4
tabulate         : 0.8.9
xarray           : 0.18.2
xlrd             : 1.1.0
xlwt             : 1.3.0
numba            : 0.51.2

</details>
