BUG: groupby apply inconsistent output
- [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 pandas as pd
import numpy as np

df1 = pd.DataFrame({'group_col': [0.0, np.nan, 0.0, 0.0], 'value_col': [2,2,2,2]})
df2 = pd.DataFrame({'group_col': [np.nan, 0.0, 0.0, 0.0], 'value_col': [2,2,2,2]})
```
groupby apply on `df1` gives multi-index output

```python
df1.groupby('group_col').value_col.apply(lambda x: x.value_counts().reindex(index=[1,2,3]))

group_col   
0.0        1    NaN
           2    3.0
           3    NaN
Name: value_col, dtype: float64
```
groupby apply on `df2` gives a single level index output:

```python
df2.groupby('group_col').value_col.apply(lambda x: x.value_counts().reindex(index=[1,2,3]))

0    NaN
1    NaN
2    3.0
3    NaN
Name: value_col, dtype: float64
```

#### Problem description

groupby apply on `df1` and `df2` produce different outputs. They should produce the same output. 

#### Expected Output
The output of both the above mentioned examples should be this:
```python3
group_col   
0.0        1    NaN
           2    3.0
           3    NaN
Name: value_col, dtype: float64
```
#### 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 94 Stepping 3, GenuineIntel
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : None.None

pandas           : 1.0.3
numpy            : 1.18.3
pytz             : 2019.3
dateutil         : 2.8.1
pip              : 20.1.1
setuptools       : 46.1.3
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.13.0
pandas_datareader: None
bs4              : None
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : None
matplotlib       : 3.2.1
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
pytest           : None
pyxlsb           : None
s3fs             : None
scipy            : 1.4.1
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : 1.2.0
xlwt             : None
xlsxwriter       : None
numba            : None

</details>
