BUG: If aggregation function returns NaN the order of the index on the resulting df is not maintained
- [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
df = pd.DataFrame(
             [
                 ("1", 1, 0, 0),
                 ("2", 2, 0, 0),
                 ("3", 3, 0, 0),
                 ("4", 4, 5, 4),
                 ("5", 5, 6, 6),
                 ("6", 6, 7, 7),
             ],
             columns=("item", "att1", "att2", "att3"),
    )

def myagg1(s):
    return s.sum()

def myagg2(s):
       return s.sum() / 2
 
aggs1 = ["sum", myagg1, "count", "min"]    
aggs2 = ["sum", myagg1, "count", "min"]    

df.agg(aggs1) # order of the index is maintained
#          item  att1  att2  att3
# sum     123456    21    18    17
# myagg1  123456    21    18    17
# count        6     6     6     6
# min          1     1     0     0

df.agg(aggs2) # myagg2 returns nan and the result is sent to the last row
#           item  att1  att2  att3
# sum     123456  21.0  18.0  17.0
# count        6   6.0   6.0   6.0
# min          1   1.0   0.0   0.0
# myagg2     NaN  10.5   9.0   8.5

```

#### Problem description
the order of the index on the resulting dataframe should not affected by the result of one of the aggregation functions.
#### Expected Output

```python
df.agg(aggs2) # Regardless of the result the order is maintained
#           item  att1  att2  att3
# sum     123456  21.0  18.0  17.0
# myagg2     NaN  10.5   9.0   8.5
# count        6   6.0   6.0   6.0
# min          1   1.0   0.0   0.0
```

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

<details>

```
INSTALLED VERSIONS
------------------
commit           : None
python           : 3.8.1.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 19.0.0
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : None
LANG             : de_DE.UTF-8
LOCALE           : de_DE.UTF-8

pandas           : 1.0.3
numpy            : 1.18.1
pytz             : 2019.3
dateutil         : 2.8.1
pip              : 20.0.2
setuptools       : 45.2.0.post20200210
Cython           : None
pytest           : 5.4.1
hypothesis       : 5.8.0
sphinx           : 2.4.4
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.1
IPython          : 7.12.0
pandas_datareader: None
bs4              : None
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : None
matplotlib       : None
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
pytest           : 5.4.1
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>
