df.head() and .tail() weirdness
I am data wrangling some Excel data into a dataframe.

At some point it has an Index like so:

``` python
Index([u'(K)', -440.0, -439.0, -438.0, -437.0, -436.0, -435.0, -434.0, -433.0, -432.0], dtype='object')
```

Naturally, I want to drop the "u'(K)'" index. Interestingly, after doing so the head() and tail() calculation totally goes haywire, and that irrespective of using this Index with dtype object or after converting it to the new Float64Index.:

``` python
<class 'pandas.core.frame.DataFrame'>
Float64Index: 446 entries, -440.0 to 5.0
Data columns (total 7 columns):
Channel 3 (A3)    446  non-null values
Channel 4 (A4)    446  non-null values
Channel 5 (A5)    446  non-null values
Channel 6 (A6)    446  non-null values
Channel 7 (B1)    446  non-null values
Channel 8 (B2)    446  non-null values
Channel 9 (B3)    446  non-null values
dtypes: float64(7)
```

or before, with dtypes still as 'object':

``` python
<class 'pandas.core.frame.DataFrame'>
Float64Index: 446 entries, -440.0 to 5.0
Data columns (total 7 columns):
Channel 3 (A3)    446  non-null values
Channel 4 (A4)    446  non-null values
Channel 5 (A5)    446  non-null values
Channel 6 (A6)    446  non-null values
Channel 7 (B1)    446  non-null values
Channel 8 (B2)    446  non-null values
Channel 9 (B3)    446  non-null values
dtypes: object(7)
```

I think I can see what's happening here: The head calculation somehow picks up the 5.0 value in the Index and choses to display the dataframe until then. Which now makes me question: Did the API of head() change and I didn't notice? My apologies if this actually is a case of PEBKAC.

The process of my data wrangling can be seen here:
http://nbviewer.ipython.org/7208717

pandas version: '0.12.0-1000-gea97682'
