scoreateprecentile return wrong value
scoreatprecentile of a series returns the wrong value

```
In [1341]: a = np.random.rand(100)

In [1342]: b = pd.Series(a)

In [1343]: a[:10]

Out[1343]: 
array([ 0.6131142 ,  0.65266141,  0.24583156,  0.70179786,  0.33361506,
        0.65042728,  0.70192276,  0.02727854,  0.65948894,  0.44326182])

In [1348]: scoreatpercentile(a,1) 
Out[1348]: 0.010388922650144839 #correct value

In [1349]: scoreatpercentile(b,1) 
Out[1349]: 0.65226593993834392 #incorrect value

In [1350]: scoreatpercentile(a,2)
Out[1350]: 0.011971896338709577 #correct value

In [1351]: scoreatpercentile(b,2)
Out[1351]: 0.25396815348880808 #incorrect value



```

I'm not sure if this is a pandas issue or scipy issue, and I am aware of the quantile method, but I still wonder if it is possible to fix that.
