Plotting 128Hz timeseries crashes
#### Code Sample

```python
import numpy as np
import pandas as pd

start = 0
freq = 128
samples = freq * 10  # 10 seconds
data = np.random.random(samples)
index = pd.date_range(start, periods=samples, freq='{}S'.format(1/freq))
ts = pd.Series(data=data, index=index, name='High freq')
ts.plot()
```
#### Problem description

Plotting a 10 second, 128Hz timeseries uses up all my RAM then crashes. 100Hz works fine, 128/150Hz (6666666N) crashes.

![screen shot 2018-04-02 at 1 43 25 pm](https://user-images.githubusercontent.com/1332954/38184721-2f7d2ed8-367c-11e8-87e5-f34eaf6b4294.png)

#### Expected Output

Ideally, a plot of my data. I wouldn't expect plotting 1280 points to require > 100GB of RAM! 😄 

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

<details>
INSTALLED VERSIONS
------------------
commit: None
python: 3.6.4.final.0
python-bits: 64
OS: Darwin
OS-release: 17.4.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: en_US.UTF-8
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.22.0
pytest: None
pip: 9.0.3
setuptools: 39.0.1
Cython: None
numpy: 1.14.0
scipy: 1.0.1
pyarrow: None
xarray: None
IPython: 6.2.1
matplotlib: 2.2.2
</details>
