BUG: setting raw=True in the Dataframe.apply function causes a ValueError
- [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.

---

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

```python
import numpy as np
import pandas as pd
df = pd.DataFrame({"a": [100, 300], "b": [200, 400]})

def parse_node_row(row, index):
    def unpack_bitmask(val):
        return [np.bitwise_and(np.right_shift(val, i * 16), 0xFFFF) for i in range(4)]

    arr = np.concatenate(np.apply_along_axis(unpack_bitmask, 0, row)).ravel()

    return pd.Series(arr, index=index)

iterables = [df.columns, ["gpu{}".format(i) for i in range(4)]]
midx = pd.MultiIndex.from_product(iterables, names=['node', 'gpu'])

ndf = df.apply(parse_node_row, axis="columns", result_type="expand", args=(midx,))
```

#### Problem description

I am working on a dataset where values are bitmaskes, each 64bit integer is actually 4x16 (one per GPU per node). The format of the dataset is out of my control.
So, I wrote the code above to create a new dataframe that created a multi index with the data split.

It works fine and all, but as I am solely using numpy functions in `parse_node_row`, I added `parse=True` in the `apply` call. However, this causes my script to crash! The minimal reproducible example above shows 

```
ValueError: Shape of passed values is (2, 8), indices imply (2, 2)

```
But runs just fine when `raw=False`. What gives?
There is no mention in [the docs](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.apply.html) of any side-effects of using raw=True besides you getting a numpy array in your apply function, which is completely fine for me.

#### Expected Output
More performance!

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

<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.7.4.final.0
python-bits      : 64
OS               : Windows
OS-release       : 10
machine          : AMD64
processor        : Intel64 Family 6 Model 158 Stepping 10, GenuineIntel
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : None.None

pandas           : 1.0.4
numpy            : 1.18.5
pytz             : 2020.1
dateutil         : 2.8.1
pip              : 20.1.1
setuptools       : 47.1.1
Cython           : 0.29.20
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : 4.5.1
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.9.0
pandas_datareader: None
bs4              : None
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : 4.5.1
matplotlib       : 3.2.0
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : 0.17.1
pytables         : None
pytest           : None
pyxlsb           : None
s3fs             : None
scipy            : 1.4.1
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
xlsxwriter       : None
numba            : None


</details>
