BUG: Creating DataFrame frome Series with DatetimeIndex results in NaN-filled df
- [x] I have checked that this issue has not already been reported (but not 100% sure either - search returns many tickets).

- [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.

---

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

```python
# Work when creating a df without datetime index.
pd.DataFrame({'a':pd.Series([1,2])})
Out[11]: 
   a
0  1
1  2

# Work when working with a datetime index and only with values of the Series
# (either with 'to_numpy()' or 'values').
pd.DataFrame({'a':pd.Series([1,2]).values},
             index=[pd.Timestamp('2021/01/01 08:00'), pd.Timestamp('2021/01/01 09:00')])
Out[12]: 
                     a
2021-01-01 08:00:00  1
2021-01-01 09:00:00  2

# Does not work when working directly with Series and datetime index.
pd.DataFrame({'a':pd.Series([1,2])},
             index=[pd.Timestamp('2021/01/01 08:00'), pd.Timestamp('2021/01/01 09:00')])
Out[13]: 
                      a
2021-01-01 08:00:00 NaN
2021-01-01 09:00:00 NaN
```

#### Problem description
In my real case problem, I am generating data through dict completion in which are handled pd.Series.
Something like:

```python
var = pd.Series(list(range(1,5)))
data = { n : (var.shift(-n) - var)/var for n in range(1,3)}
df = pd.DataFrame(data, index=pd.date_range(pd.Timestamp('2021/01/01 08:00'), periods=4, freq='1h'))
```
And this results in a df filled with NaN

Is this a bug or a feature?

#### Expected Output
A df not filled with NaN.

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

<details>

INSTALLED VERSIONS
------------------
commit           : 2cb96529396d93b46abab7bbc73a208e708c642e
python           : 3.8.5.final.0
python-bits      : 64
OS               : Linux
OS-release       : 5.8.0-55-generic
Version          : #62~20.04.1-Ubuntu SMP Wed Jun 2 08:55:04 UTC 2021
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : fr_FR.UTF-8
LOCALE           : fr_FR.UTF-8

pandas           : 1.2.4
numpy            : 1.20.1
pytz             : 2021.1
dateutil         : 2.8.1
pip              : 21.1.1
setuptools       : 52.0.0.post20210125
Cython           : 0.29.23
pytest           : 6.2.3
hypothesis       : None
sphinx           : 4.0.1
blosc            : None
feather          : None
xlsxwriter       : 1.3.8
lxml.etree       : 4.6.3
html5lib         : 1.1
pymysql          : None
psycopg2         : None
jinja2           : 3.0.0
IPython          : 7.22.0
pandas_datareader: None
bs4              : 4.9.3
bottleneck       : 1.3.2
fsspec           : 0.9.0
fastparquet      : 0.6.3
gcsfs            : None
matplotlib       : 3.3.4
numexpr          : 2.7.3
odfpy            : None
openpyxl         : 3.0.7
pandas_gbq       : None
pyarrow          : 2.0.0
pyxlsb           : None
s3fs             : None
scipy            : 1.6.2
sqlalchemy       : 1.4.15
tables           : 3.6.1
tabulate         : None
xarray           : None
xlrd             : 2.0.1
xlwt             : 1.3.0
numba            : 0.51.2

</details>
