High memory usage pivot_table 
Hi all,

I observed now several times that `pivot_table()` requires a lot of memory when I wanted to reshape a `Data.Frame` in table format (id, name, value) into matrix format (index=id, columns=name, values=value):

``` python
print(d) 
# id  sample  value
    1           A        1
    2           A        2
    1           B       10
    2           B       20
..... (many rows)
e = pd.pivot_table(d, index='id', columns='sample', values='value')
print(e)
        A          B
1      1           2
2     10         20
```

Is this a known issue? Is there a workaround?
For data maintenance, it's often times better to store large data in table format, and convert them to matrix format on demand. The R `reshape` and `gather` functions  (http://goo.gl/isx1bv) from the dplyr package seem to be faster and require less memory than `pivot_table` and `melt`.

Cheers,
Christof
