inconsistent type returned on single (string) column subsetting
#### Code Sample, a copy-pastable example if possible

As expected:
```python
import pandas as pd
all_cols = list("abcdefg")

informative_cols = ["a","c","g"]
 
dfrandom = pd.DataFrame(pd.np.random.rand(5, len(all_cols)), columns=all_cols)

field = informative_cols[0]
print(field)
print(type(dfrandom[field]))
print(type(dfrandom[informative_cols][field]))
```
returns:
```
a
<class 'pandas.core.series.Series'>
<class 'pandas.core.series.Series'>
```

However, unexpectedly: 
```python
import pandas as pd
all_cols = list("abcdefg")

informative_cols = ["a","c","g"]

dfrandom = pd.DataFrame(pd.np.random.rand(5, len(all_cols)), columns=all_cols)

field = informative_cols[0]
print(field)
print(type(dfrandom[field]))
print(type(dfrandom[informative_cols][field]))
```

returns: 
```
0_AnatomicRegionSequence_CodeMeaning
<class 'pandas.core.series.Series'>
<class 'pandas.core.frame.DataFrame'>
```

#### Problem description

Subsetting one single column with a string must output the same result independent of copying and previous subsetting.
Because expected output is consistent and unexpected is inconsistent

#### Expected Output
```
0_AnatomicRegionSequence_CodeMeaning
<class 'pandas.core.series.Series'>
<class 'pandas.core.series.Series'>
```

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

<details>
INSTALLED VERSIONS
------------------
commit: None
python: 3.6.1.final.0
python-bits: 64
OS: Linux
OS-release: 4.2.0-42-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.20.2
pytest: None
pip: 9.0.1
setuptools: 36.0.1
Cython: None
numpy: 1.13.0
scipy: 0.19.0
xarray: None
IPython: 6.1.0
sphinx: None
patsy: 0.4.1
dateutil: 2.6.0
pytz: 2017.2
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: 2.0.2
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: 0.999999999
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.9.6
s3fs: None
pandas_gbq: None
pandas_datareader: None
</details>
