Series near-zero subtraction loss of precision
Unless I am unaware of some preset precision in pandas, I've discovered a bug in what I believe to be some part of the Series subtraction operation in pandas 0.10.1, numpy 1.6.2. I haven't tested in other versions.

Data set:

```
a = [49105.962326,
49106.062271,
49106.112167,
49106.222305,
49106.332290]
s = pd.Series(a)
```

A simple slice to calculate deltas:

```
dt = s[1:] - s[:-1]
```

results in:

```
0   NaN
1     0
2     0
3     0
4   NaN
```

The resultant values (i.e., values stored at `dt[1:3]`) are exactly zero and of type `numpy.float64`. These zeros and the final null value are not correct, which can be shown with conversion to a numpy array and performing the same operation:

```
npa = np.array(s)
npa[1:] - npa[:-1]
```

results in the expected (and correct) values:

```
array([ 0.099945,  0.049896,  0.110138,  0.109985])
```

A little digging didn't reveal that this issue had been already mentioned, but may be related to Issues #2697 and/or #2069?
