DataFrame.describe(percentiles=[]) still returns 50% percentile.
The DataFrame.describe() method docs seem to indicate that you can pass percentiles=None to not compute any percentiles, however by default it still computes 25%, 50% and 75%. The best I can do is pass an empty list  to only compute the 50% percentile. I would think that passing an empty list would return no percentile computations. 

Should we allow passing an empty list to not compute any percentiles?

pandas 0.17.1

``` python
In [1]: import pandas as pd

In [2]: import numpy as np

In [3]: df = pd.DataFrame(np.random.randn(10,5))

In [4]: df.describe(percentiles=None)
Out[4]:
               0          1          2          3          4          5  
count  10.000000  10.000000  10.000000  10.000000  10.000000  10.000000
mean   -0.116736  -0.160728   0.066763  -0.068867  -0.242050   0.390091
std     0.771704   0.837520   0.875747   0.955985   1.093919   0.923464
min    -1.347786  -1.140541  -1.297533  -1.347824  -2.085290  -0.825807
25%    -0.580527  -0.613640  -0.558291  -0.538433  -0.836046  -0.275567
50%    -0.261526  -0.395307   0.007595  -0.248025   0.000515   0.314278
75%     0.329780   0.154053   0.708768   0.407732   0.366278   1.192338
max     1.285276   1.649528   1.485076   1.697162   1.551388   1.762939

In [15]: df.describe(percentiles=[])
Out[15]:
               0          1          2          3          4          5  
count  10.000000  10.000000  10.000000  10.000000  10.000000  10.000000
mean   -0.116736  -0.160728   0.066763  -0.068867  -0.242050   0.390091
std     0.771704   0.837520   0.875747   0.955985   1.093919   0.923464
min    -1.347786  -1.140541  -1.297533  -1.347824  -2.085290  -0.825807
50%    -0.261526  -0.395307   0.007595  -0.248025   0.000515   0.314278
max     1.285276   1.649528   1.485076   1.697162   1.551388   1.762939

```
