Truncated floating point formatting with DataFrame output
The display output of a DataFrame may truncate floats, for example:

``` python
from pandas import DataFrame
import numpy as np
dat_dtype = {
    'names' : ('column_one', 'col_two'),
    'formats' : ('i', 'd')}
dat = np.zeros(4, dat_dtype)
dat['column_one'] = 10**(np.arange(4))
dat['col_two'] = 10**(-np.arange(4, dtype='d') - 4)
print(DataFrame(dat))
```

shows

```
    column_one   col_two
0           1  0.000100
1          10  0.000010
2         100  0.000001
3        1000  0.000000
```

The last number in `col_two` has been truncated from `0.0000001` to `0.000000`. I consider this formatting deceptive and unacceptable.

---

As a side note, here is tabular output for the same data from different programs.

Using [prettytable](https://code.google.com/p/prettytable/wiki/Tutorial):

``` python
from prettytable import PrettyTable
x = PrettyTable(dat.dtype.names)
for row in dat:
    x.add_row(row)
    x.align = 'r'
print(x)
```

showing

```
+------------+---------+
| column_one | col_two |
+------------+---------+
|          1 |  0.0001 |
|         10 |   1e-05 |
|        100 |   1e-06 |
|       1000 |   1e-07 |
+------------+---------+
```

PostgreSQL is similar:

```
postgres=# select * from dat;
 column_one | col_two
------------+---------
          1 |  0.0001
         10 |  1e-005
        100 |  1e-006
       1000 |  1e-007
(4 rows)
```

R formats the whole column using scientific exponential formatting:

```
> dat
> dat <- data.frame(column_one=10**(0:4), col_two=10**(0:-4 - 4))
  column_one col_two
1          1   1e-04
2         10   1e-05
3        100   1e-06
4       1000   1e-07
5      10000   1e-08
```
