BUG: Series(DTI/TDI) loses the frequency information from original DTI/TDI
#### Code Sample, a copy-pastable example if possible
DTI example below, same general behavior occurs for TDI:
```python
In [2]: dti = pd.date_range('20180101', periods=3, freq='B')

In [3]: dti.freq
Out[3]: <BusinessDay>

In [4]: s = pd.Series(dti)

In [5]: s.dt.freq
Out[5]: 'D'
```

This appears to be caused by the `dt` accessor overriding the `freq` definition, which was done for perf reasons in #17210:

https://github.com/pandas-dev/pandas/blob/b02c69ac7309ccf63a17471b25475bf0c0ebe3c3/pandas/core/indexes/accessors.py#L174-L176

If I remove the code above, the resulting frequency of the `Series` is `None`.  This is consistent with one of the error messages displayed when trying to add an integer to the `Series`, which works at the DTI/TDI level when a frequency is present:
```python
In [6]: dti + 4
Out[6]: DatetimeIndex(['2018-01-05', '2018-01-08', '2018-01-09'], dtype='datetime64[ns]', freq='B')

In [7]: s + 4
---------------------------------------------------------------------------
NullFrequencyError: Cannot shift with no freq

During handling of the above exception, another exception occurred:

TypeError: incompatible type for a datetime/timedelta operation [add]
```
#### Problem description
`Series` ignores the original frequency, and subsequent frequency dependent operations do not work.

#### Expected Output
I'd expect frequency to be retained, and frequency dependent operations to work when one is set.

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

<details>

INSTALLED VERSIONS
------------------
commit: b02c69ac7309ccf63a17471b25475bf0c0ebe3c3
python: 3.6.1.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 78 Stepping 3, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.23.0rc2
pytest: 3.1.2
pip: 9.0.1
setuptools: 39.0.1
Cython: 0.28.2
numpy: 1.13.3
scipy: 1.0.0
pyarrow: 0.6.0
xarray: 0.9.6
IPython: 6.1.0
sphinx: 1.5.6
patsy: 0.4.1
dateutil: 2.6.0
pytz: 2017.2
blosc: None
bottleneck: 1.2.1
tables: 3.4.2
numexpr: 2.6.4
feather: 0.4.0
matplotlib: 2.0.2
openpyxl: 2.4.8
xlrd: 1.1.0
xlwt: 1.3.0
xlsxwriter: 0.9.8
lxml: 3.8.0
bs4: None
html5lib: 0.999
sqlalchemy: 1.1.13
pymysql: None
psycopg2: None
jinja2: 2.9.6
s3fs: None
fastparquet: 0.1.5
pandas_gbq: None
pandas_datareader: None

</details>
