Resampling irregular timeseries
I have some depth data from an echo-sounder in the following format

Date Time Depth
2013-00-28 00:00:38.652 2798.09
2013-00-28 00:00:48.632 2795.90
2013-00-28 00:00:58.388 2783.43
2013-00-28 00:01:08.160 2793.54
2013-00-28 00:01:17.517 2784.77
2013-00-28 00:01:27.289 2784.89
2013-00-28 00:01:37.860 2786.27
2013-00-28 00:01:47.631 2775.23
2013-00-28 00:01:57.388 2783.54
2013-00-28 00:02:07.367 2786.70
2013-00-28 00:02:17.123 2780.25
...

It is irregularly sampled in time, with time intervals varying between about 8 and 15 s. I would like to resample it to 20s intervals.Can I do this with pandas.DataFrame.resample?

I've tried reading it in with:
  dtz = pandas.read_csv(infile,sep=' ',parse_dates=[[0,1]])
And resampling using:
 dtz['Depth'].resample('20S',fill_method='pad',limit=6)

But I get the following error:
 raise TypeError('Only valid with DatetimeIndex or PeriodIndex') 
 TypeError: Only valid with DatetimeIndex or PeriodIndex

Any comments on what I'm doing wrong?
I also tried to get the date time info into an index:
   dtz = pd.read_csv(infile,sep=' ',index_col=0,parse_dates=[[0,1]])
To no avail
