Cannot use apply on Series with Timestamp values
#### Code Sample, a copy-pastable example if possible

```python
import pandas as pd

ts = pd.Series([pd.Timestamp('2017-07-31 20:08:46.110998-04:00'), 
                pd.Timestamp('2017-08-01 20:08:46.110998-04:00'), 
                pd.Timestamp('2017-08-02 20:08:46.110998-04:00')])

def func(elem):
    print(type(elem))
    return elem
print(type(ts))
print(type(ts[0]))

ts.apply(func);

# Prints out:
# <class 'pandas.core.series.Series'>
# <class 'pandas._libs.tslib.Timestamp'>
# <class 'pandas.core.indexes.datetimes.DatetimeIndex'>

```
#### Problem description

I have a Series with Timestamps as values rather than the index. I expect the apply method to be called on each element, but it is not, rather it gets called on a DatetimeIndex.

#### Expected Output

<class 'pandas.core.series.Series'>
<class 'pandas._libs.tslib.Timestamp'>
<class 'pandas._libs.tslib.Timestamp'>
<class 'pandas._libs.tslib.Timestamp'>
<class 'pandas._libs.tslib.Timestamp'>

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

<details>
INSTALLED VERSIONS
------------------
commit: None
python: 3.6.0.final.0
python-bits: 64
OS: Darwin
OS-release: 16.7.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_CA.UTF-8
LOCALE: en_CA.UTF-8

pandas: 0.20.2
pytest: 3.0.5
pip: 9.0.1
setuptools: 35.0.1
Cython: None
numpy: 1.13.0
scipy: 0.19.1
xarray: 0.9.6
IPython: 6.0.0
sphinx: 1.5.3
patsy: None
dateutil: 2.6.0
pytz: 2016.10
blosc: None
bottleneck: 1.2.0
tables: None
numexpr: None
feather: None
matplotlib: 2.0.0
openpyxl: 2.4.8
xlrd: 1.0.0
xlwt: None
xlsxwriter: 0.9.8
lxml: None
bs4: None
html5lib: 0.999
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.9.5
s3fs: None
pandas_gbq: None
pandas_datareader: None
</details>