Keep the flattened data array others suggested, and then just split it like this: *(replace `example_data`, `_array`, and `columns`)*
>>> example_data = range(15) >>> split_array = lambda _array, colums: \ . . . [_array[i:i + colums] for i in \ . . . xrange(0, len(_array), colums)] >>> print split_array(example_data, 5) [[0, 1, 2, 3, 4], [5, 6, 7, 8, 9], [10, 11, 12, 13, 14]] Gist <https://gist.github.com/anonymous/f9064e4c8790ae037ec6> What do you guys think? On Fri, Apr 12, 2013 at 12:46 PM, Dave Angel <da...@davea.name> wrote: > On 04/12/2013 01:29 PM, Ana Dionísio wrote: > >> That only puts the data in one column, I wanted to separate it. >> >> For example: >> data in csv file: >> >> 1 2 3 4 5 >> 7 8 9 10 11 >> a b c d e >> >> I wanted an array where I could pick an element in each position. In the >> case above if I did print array[0][3] it would pick 4 >> >> > I know nothing about numpy. > > How about something like: > import csv > myreader = csv.reader(....) > mylist = list(myreader) > > > Presumably you can fill in the details. Anyway, I think this will give > you a list of lists, and perhaps you can convert that to a numpy array, if > you really need one of those. > > > -- > DaveA > -- > http://mail.python.org/**mailman/listinfo/python-list<http://mail.python.org/mailman/listinfo/python-list> > -- Javier Miranda Mobile: +52 333 129 20 70
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