Why not read in just the date and ID columns to start with, then do a
numpy.unique() or python set() on theses, then query based on the unique
values? Seems like it might be faster
Be Well
Anthony
On Mon, Jul 2, 2012 at 5:16 PM, Aquil H. Abdullah
wrote:
> Hello All,
>
> I have a table that
Hello All,
I have a table that is indexed by two keys, and I would like to search for
duplicate keys. So here is my naive slow implementation: (code I posted on
stackoverflow)
import tables
h5f = tables.openFile('filename.h5')
tbl = h5f.getNode('/data','data_table') # assumes group data and tabl
