> Dear all,
>
> I have a CSV file with the first column with timestamps:
>
> 0:00:00 01/01/2007, 0.000, 10, 0.000, 10,
> 0.000, 10:
> 00:00:00 02/01/2007, 0.000, 10, 0.000, 10,
> 0.000, 10
> 00:00:00 03/01/2007, 0.000, 10, 0.000, 10,
> 0.000, 10
> ...
> 00:00:00 29/12/2009, 0.000, 10, 0.000, 10,
> 0.000, 10
> 00:00:00 30/12/2009, 0.000, 10, 0.000, 10,
> 0.000, 10
> 00:00:00 31/12/2009, 0.000, 10, 0.000, 10,
> 0.000, 10
>
> As you can see, the format is hour:minute:second (nor relevant, always
> 00) day/month/year.
>
> When loaded with mlab.csv2rec, it automatically detects them as dates
> and creates datetime objects, but it is not consistent with the
> interpretation of the dates. When the day is < 13, it interprets it as
> month/day/year. It's loaded correctly otherwise (as day/month/year). I
> could pre-process the files and change the dates format, but imho it's
> not very elegant. Any suggestion about how to address this issue?
>
> Regards,
> Sergi
You could use numpy.genfromtxt together with its `converters` parameter:
converters : variable, optional
The set of functions that convert the data of a column to a value.
The converters can also be used to provide a default value
for missing data: ``converters = {3: lambda s: float(s or 0)}``.
Cheers,
A.
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