.plot() method slow compared to Matplotlib
When plotting large datasets, pandas.plot() is much slower than the direct use of Matplotlib:

``` python
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

df = pd.DataFrame(data=np.random.normal(0, 1, (1, 1000)))

%timeit df.plot()
1 loops, best of 3: 11.2 s per loop

%timeit plt.plot(df.index, df.values)
1 loops, best of 3: 2.1 s per loop
```
## INSTALLED VERSIONS

commit: None
python: 3.4.1.final.0
python-bits: 32
OS: Windows
OS-release: 8
machine: x86
processor: x86 Family 6 Model 55 Stepping 3, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None

pandas: 0.15.0
nose: 1.3.4
Cython: 0.21
numpy: 1.9.1
scipy: 0.15.1
statsmodels: 0.6.1
IPython: 2.4.1
sphinx: 1.2.3
patsy: 0.3.0
dateutil: 2.1
pytz: 2014.9
bottleneck: None
tables: 3.1.1
numexpr: 2.3.1
matplotlib: 1.4.2
openpyxl: 1.8.5
xlrd: 0.9.3
xlwt: None
xlsxwriter: 0.5.7
lxml: 3.4.0
bs4: 4.3.2
html5lib: None
httplib2: None
apiclient: None
rpy2: None
sqlalchemy: 0.9.7
pymysql: None
psycopg2: None
