DataFrame produces NaNs
Here is how to reproduce it:

``` python
In [1]: import urllib2

In [2]: open("N_06_area.txt", "w").write(urllib2.urlopen("ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/Jun/N_06_area.txt").read())

In [3]: from pandas import read_table, DataFrame

In [4]: data = read_table("data/N_06_area.txt", skipfooter=16, sep="\s+")

In [5]: avg = data[2:32].extent.mean()

In [6]: anomaly = (data.extent - avg) / avg

In [7]: DataFrame({"anomaly": anomaly}).head()
Out[7]: 
    anomaly
0  0.058843
1  0.035295
2  0.057161
3  0.067254
4  0.039500

In [8]: DataFrame({"anomaly": anomaly}, index=data.year).head()
Out[8]: 
      anomaly
year         
1979      NaN
1980      NaN
1981      NaN
1982      NaN
1983      NaN

In [9]: import pandas

In [10]: pandas.__version__
Out[10]: '0.11.0'
```

As you can see, [7] is correct, but when I try to assign years as the index in [8], I get NaN.

I hit this problem in this notebook: [Sea Ice Index.ipynb](http://nbviewer.ipython.org/urls/raw.github.com/certik/climate/4056bcc8318ab81a1fe6029f1597a35798f17cce/Sea%2520Ice%2520Index.ipynb)
