Inconsistency with .loc DatetimeIndex type conversion
#### Code Sample, a copy-pastable example if possible

```python
dates = pd.date_range('20180101', periods=2, freq='D')
df = pd.DataFrame([1, 2], index=dates)

# 1. (runs fine)
df.loc[pd.Timestamp('20180101')]
# 2. (runs fine)
df.loc['20180101']
# 3. (runs fine)
df.loc[[pd.Timestamp('20180101')]]
# 4. (KeyError: u"None of [['20180101']] are in the [index]")
df.loc[['20180101']]

```
#### Problem description

I'm new to using Pandas, but in playing around with the loc accessor, I noticed what seems to be inconsistent behavior with type conversion.  A string is allowed for accessing the date index in the 2nd example above, but a similar query throws a KeyError when placed inside a list.  Is this working as intended or should these have more consistent behavior?

#### Expected Output
```
		0
2018-01-01	1
```

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

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 2.7.6.final.0
python-bits: 64
OS: Linux
OS-release: 4.3.5-smp-815.10.0.0
machine: x86_64
processor: 
byteorder: little
LC_ALL: en_US.UTF-8
LANG: None
LOCALE: None.None

pandas: 0.22.0
numpy: 1.13.3
</details>
