resource hog -> .asfreq(DateOffset(seconds=1),method='pad')
```
>>> df2['a']
2010-12-01 00:00:00    1
2010-12-02 00:00:00    2
2010-12-03 00:00:00    3
2010-12-04 00:00:00    4
>>> df2['a'].asfreq(pn.DateOffset(seconds=1),method='pad')

## NOTE: The above one-liner runs for over 20 minutes on a 2Ghz Xeon, python 2.5.2, numpy 1.5.1,
##       & pandas head from 2011-01-05.  It also consumed > 15% (500MB!!!) of available DRAM
##       before I manually killed it
[mpenning@Bucksnort tickdata]$ free
             total       used       free     shared    buffers     cached
Mem:       3894944    3771540     123404          0     192340    2328984
-/+ buffers/cache:    1250216    2644728
Swap:      2830328        596    2829732
[mpenning@Bucksnort tickdata]$ cat /proc/cpuinfo
...
processor       : 3
vendor_id       : GenuineIntel
cpu family      : 15
model           : 2
model name      : Intel(R) Xeon(TM) CPU 2.00GHz
stepping        : 7
cpu MHz         : 1995.840
cache size      : 512 KB
physical id     : 3
siblings        : 2
core id         : 0
cpu cores       : 1
apicid          : 7
initial apicid  : 7
fdiv_bug        : no
hlt_bug         : no
f00f_bug        : no
coma_bug        : no
fpu             : yes
fpu_exception   : yes
cpuid level     : 2
wp              : yes
flags           : fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe pebs bts cid xtpr
bogomips        : 3991.51
clflush size    : 64
power management:

[mpenning@Bucksnort tickdata]$
```
