Jupyter Notebook displays Series VERY slowly
#### Code Sample

```python
import pandas as pd
from IPython.display import display
df = pd.DataFrame(
    pd.np.random.random((10000000, 1)), 
    columns=['a'], 
    index=pd.date_range(start='2001-01-01', freq='min', periods=10000000)
)
display(df.a)
```

```
import pandas as pd
from IPython.display import display

# read some data for size 200,000 x 4

display(data.loc[:, ['reading']])  #25ms
display(data.reading.to_frame())  #25ms
display(data.reading) #3.53s
s = data.reading
display(s) #3.32s possibly cached
print(data.reading) #9ms
print(data.loc[:, ['reading']]) # 15ms
```
#### Problem description

In the Jupyter notebook, displaying a `pd.Series` is VERY slow. It is displays quicker when kept as a `pd.DataFrame` but is of course more verbose.

#### Expected Output

A pd.Series display/print out at reasonable speeds.

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

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.5.4.final.0
python-bits: 64
OS: Windows
OS-release: 7
machine: AMD64
processor: Intel64 Family 6 Model 60 Stepping 3, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.21.0
pytest: 3.2.1
pip: 9.0.1
setuptools: 36.2.4
Cython: 0.26
numpy: 1.13.3
scipy: 0.19.1
pyarrow: None
xarray: None
IPython: 5.3.0
sphinx: 1.6.3
patsy: 0.4.1
dateutil: 2.6.1
pytz: 2017.3
blosc: None
bottleneck: 1.2.1
tables: 3.4.2
numexpr: 2.6.2
feather: None
matplotlib: 2.0.0
openpyxl: 2.5.0a2
xlrd: 1.0.0
xlwt: 1.2.0
xlsxwriter: 0.9.8
lxml: 3.8.0
bs4: 4.6.0
html5lib: 0.9999999
sqlalchemy: 1.1.13
pymysql: 0.7.9.None
psycopg2: None
jinja2: 2.9.6
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: 0.4.0

</details>
