df.sample() much slower than df.iloc[randint]
It seems like the Dataframe sample function is much slower than directly selecting a randomly indexed row:

import pandas as pd
import numpy as np
from time import time

> > > test_df = pd.DataFrame(np.random.randint(0, 100, size = (400, 600)))
> > > def f():
> > > ...  start = time()
> > > ...  for _ in range(100):
> > > ...   test_df.sample()
> > > ...  print(time() - start)
> > > ... 
> > > def g():
> > > ...  start = time()
> > > ...  for _ in range(100):
> > > ...   test_df.iloc[np.random.randint(0, test_df.shape[0])]
> > > ...  print(time() - start)
> > > ... 
> > > f()
> > > 0.571173906326
> > > g()
> > > 0.0156011581421
