Observing significant (up to 30x) __get_item__ performance drop between 0.19.2 and 0.20.x
#### Code Sample, a copy-pastable example if possible
```python
# Your code here
#%%
import pandas as pd
import numpy as np


#%%
_M = 10
_N = 1000
tuples = [(i,j) for i in range(_M) for j in range(_N)]
index = pd.MultiIndex.from_tuples(tuples, names=['first', 'second'])
df = pd.DataFrame(np.random.rand(_N*_M,4),columns=['A','B','C','D'],index=index)

#%%
import itertools
for u,v in itertools.combinations(range(_M),2):
    for w in range(_N):
        someval1 = df.A.loc[u,w] - df.A.loc[v,w]
        someval2 = df.B.loc[u,w] - df.B.loc[v,w]
```
#### Problem description 
This is my first ever git post, and so please let me know if I can do anything else to make the issue more clear.

This is the gist of a script that I execute in Spyder.  It is ugly and could be written to be made faster, but since the "for" loop (which is calling __get_item__) only took around 10 seconds to run, I didn't worry about cleaning it up.  The 3x performance degradation between 0.19.2 to 0.20.2 (and a 30x degradation in 0.20.1) is very disconcerting since __get_item__ is such a low level operation.

[this should explain **why** the current behaviour is a problem and why the expected output is a better solution.]

#### Expected Output
The code sample above took around 10 seconds to execute on pandas version 0.19.2.  It took over 5 *minutes* to run in version 0.20.1 and around 30 seconds to run in version 0.20.2.  The runtime difference between 0.19.2 and 0.20.2 is still a 3x degradation.  

Note the profiler output for __get_item__ using pandas versions 0.19.2, 0.20.1 and 0.20.2 respectively:

![image](https://user-images.githubusercontent.com/29292793/26957295-0d275bc6-4c92-11e7-9971-1ea531562f9c.png)
![image](https://user-images.githubusercontent.com/29292793/26957374-9840a0f0-4c92-11e7-95e0-bc03f33f4ab6.png)
![image](https://user-images.githubusercontent.com/29292793/26957386-ad490564-4c92-11e7-9c3b-de33e7421c4c.png)


#### 1 of 4 -- Output of ``pd.show_versions()`` -- VERSION 0.19.2
<details>
# Paste the output here pd.show_versions() here
INSTALLED VERSIONS
------------------
commit: None
python: 3.6.1.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 158 Stepping 9, GenuineIntel
byteorder: little
LC_ALL: None
LANG: en
LOCALE: None.None

pandas: 0.19.2
nose: 1.3.7
pip: 9.0.1
setuptools: 27.2.0
Cython: 0.25.2
numpy: 1.12.1
scipy: 0.19.0
statsmodels: 0.8.0
xarray: None
IPython: 5.3.0
sphinx: 1.5.6
patsy: 0.4.1
dateutil: 2.6.0
pytz: 2017.2
blosc: None
bottleneck: 1.2.1
tables: 3.2.2
numexpr: 2.6.2
matplotlib: 2.0.2
openpyxl: 2.4.7
xlrd: 1.0.0
xlwt: 1.2.0
xlsxwriter: 0.9.6
lxml: 3.7.3
bs4: 4.6.0
html5lib: 0.999
httplib2: None
apiclient: None
sqlalchemy: 1.1.9
pymysql: 0.7.9.None
psycopg2: None
jinja2: 2.9.6
boto: 2.46.1
pandas_datareader: None
</details>

#### 2 of 3 -- Output of ``pd.show_versions()`` -- VERSION 0.20.1
<details>
INSTALLED VERSIONS
------------------
commit: None
python: 3.6.1.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 158 Stepping 9, GenuineIntel
byteorder: little
LC_ALL: None
LANG: en
LOCALE: None.None

pandas: 0.20.1
pytest: 3.0.7
pip: 9.0.1
setuptools: 27.2.0
Cython: 0.25.2
numpy: 1.12.1
scipy: 0.19.0
xarray: None
IPython: 5.3.0
sphinx: 1.5.6
patsy: 0.4.1
dateutil: 2.6.0
pytz: 2017.2
blosc: None
bottleneck: 1.2.1
tables: 3.2.2
numexpr: 2.6.2
feather: None
matplotlib: 2.0.2
openpyxl: 2.4.7
xlrd: 1.0.0
xlwt: 1.2.0
xlsxwriter: 0.9.6
lxml: 3.7.3
bs4: 4.6.0
html5lib: 0.999
sqlalchemy: 1.1.9
pymysql: 0.7.9.None
psycopg2: None
jinja2: 2.9.6
s3fs: None
pandas_gbq: None
pandas_datareader: None
</details>

#### 3 of 3-- Output of ``pd.show_versions()`` -- VERSION 0.20.2
<details>
INSTALLED VERSIONS
------------------
commit: None
python: 3.6.1.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 158 Stepping 9, GenuineIntel
byteorder: little
LC_ALL: None
LANG: en
LOCALE: None.None

pandas: 0.20.2
pytest: 3.0.7
pip: 9.0.1
setuptools: 27.2.0
Cython: 0.25.2
numpy: 1.12.1
scipy: 0.19.0
xarray: None
IPython: 5.3.0
sphinx: 1.5.6
patsy: 0.4.1
dateutil: 2.6.0
pytz: 2017.2
blosc: None
bottleneck: 1.2.1
tables: 3.2.2
numexpr: 2.6.2
feather: None
matplotlib: 2.0.2
openpyxl: 2.4.7
xlrd: 1.0.0
xlwt: 1.2.0
xlsxwriter: 0.9.6
lxml: 3.7.3
bs4: 4.6.0
html5lib: 0.999
sqlalchemy: 1.1.9
pymysql: 0.7.9.None
psycopg2: None
jinja2: 2.9.6
s3fs: None
pandas_gbq: None
pandas_datareader: None
</details>
