pandas.Series.dt.total_seconds() documentation confusing
#### Code Sample, a copy-pastable example if possible

```python
import pandas as pd

series = pd.Series(pd.datetime(2017, 10, 30))

# Try with regular datetime Series (will fail)
series.dt.total_seconds()
```
```
Output: 
AttributeError: 'DatetimeProperties' object has no attribute 'total_seconds'
```
```python
# Try with TimeDelta Series (intended use)
series.sub(pd.datetime(2017, 10, 29)).dt.total_seconds()
```
```
Output:
0    86400.0
dtype: float64
```
#### Problem description

The documentation for [`pd.Series.dt.total_seconds()`](http://pandas.pydata.org/pandas-docs/version/0.21.0/generated/pandas.Series.dt.total_seconds.html#pandas.Series.dt.total_seconds) is a bit confusing. Reading it, one would expect that this method should work on any `Series` with the `dt` accessor. This is incorrect; looking at the [API reference for datetimeline properties](http://pandas.pydata.org/pandas-docs/version/0.21.0/api.html#datetimelike-properties), it's made clear that this attribute is only available on timedelta `Series`.

It might be helpful to make it more clear in the documentation for `pd.Series.dt.total_seconds()` that the method is only available on timedelta `Series`. Most people will get to the page by googling "Pandas total_seconds" or something similar; they won't often see where it falls in the API reference.

Is there any precedence for these kinds of heads-ups? I'm happy to make the documentation change and would like to make sure I follow any existing conventions (if they exist).

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

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.6.3.final.0
python-bits: 64
OS: Darwin
OS-release: 16.7.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.21.0
pytest: None
pip: 9.0.1
setuptools: 36.6.0
Cython: None
numpy: 1.13.3
scipy: 1.0.0
pyarrow: None
xarray: None
IPython: 6.2.1
sphinx: None
patsy: 0.4.1
dateutil: 2.6.1
pytz: 2017.3
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: 2.1.0
openpyxl: None
xlrd: 1.1.0
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: 1.0b10
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.9.6
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None

</details>
