BUG: numexpr / ops with boolean and conversion
these cases should give the same results. Somehow the ops order is being reversed or something with numexpr.

numpy 1.8.1, numexpr 2.4, pandas 0.14rc1
Can be worked around like:

```
In [39]: df = DataFrame(dict(A=np.random.randn(25000)))

In [40]: df.iloc[0:5] = np.nan

In [41]: (1-np.isnan(df)).iloc[0:25]
Out[41]: 
       A
0      0
1      0
2      0
3      0
4      0
5     -1
6     -1
7     -1
8     -1
9     -1
10    -1
11    -1
12    -1
13    -1
14    -1
15    -1
16    -1
17    -1
18    -1
19    -1
20    -1
21    -1
22    -1
23    -1
24    -1
25    -1
```

```
In [43]: df = DataFrame(dict(A=np.random.randn(25)))

In [44]: df.iloc[0:5] = np.nan

In [45]: (1-np.isnan(df)).iloc[0:25] 
Out[45]: 
    A
0   0
1   0
2   0
3   0
4   0
5   1
6   1
7   1
8   1
9   1
10  1
11  1
12  1
13  1
14  1
15  1
16  1
17  1
18  1
19  1
20  1
21  1
22  1
23  1
24  1
```
