BUG: Creating a Series from a Series results in all NaN values
- [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.

---

**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 numpy as np
import pandas as pd

pd.Series(pd.Series(np.random.randn(100)),index=pd.date_range("1980-1-1",periods=100,freq="D"))
```

output

```
1980-01-01   NaN
1980-01-02   NaN
1980-01-03   NaN
...
```

#### Problem description

Series accepts array-like, and Series is array-like.

#### Expected Output
A Series with the same values and my new index.
#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.7.7.final.0
python-bits      : 64
OS               : Windows
OS-release       : 10
machine          : AMD64
processor        : AMD64 Family 23 Model 113 Stepping 0, AuthenticAMD
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : None.None
pandas           : 1.0.5
numpy            : 1.18.5
pytz             : 2020.1
dateutil         : 2.8.1
pip              : 20.1.1
setuptools       : 49.2.0.post20200714
Cython           : 0.29.21
pytest           : 5.4.3
hypothesis       : None
sphinx           : 3.1.2
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : 4.5.1
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.16.1
pandas_datareader: v0.10.0dev0+6.g642bd7b
bs4              : 4.9.1
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : 4.5.1
matplotlib       : 3.2.2
numexpr          : 2.7.1
odfpy            : None
openpyxl         : 3.0.4
pandas_gbq       : None
pyarrow          : None
pytables         : None
pytest           : 5.4.3
pyxlsb           : None
s3fs             : None
scipy            : 1.5.0
sqlalchemy       : None
tables           : 3.6.1
tabulate         : 0.8.7
xarray           : None
xlrd             : 1.2.0
xlwt             : 1.3.0
xlsxwriter       : None
numba            : 0.50.1


</details>
