Rereading the original post, I am a little confused are your trying to read
the whole table, just a couple of rows that meet some condition, or just
one whole column, or one part of the column.
To request the whole table without looping over each row in Python, index
every element:
f.root.table[:]
To just get certain rows, use where().
To get a single column, use the cols namespace:
f.root.table.cols.my_column[:]
Why is this file elsewhere on the network?
Be Well
Anthony
On Sun, Jul 15, 2012 at 4:08 PM, Juan Manuel Vázquez Tovar <
jmv.to...@gmail.com> wrote:
> Hello Anthony,
>
> I have to loop over the whole set of rows. Does the where method has any
> advantages in that case?
>
> Thank you,
> Juanma
>
> 2012/7/15 Anthony Scopatz <scop...@gmail.com>
>
>> Hello Juan,
>>
>> Try using the where() method [1], It has a lot of nice features under
>> the covers.
>>
>> Be Well
>> Anthony
>>
>> 1.
>> http://pytables.github.com/usersguide/libref.html?highlight=where#tables.Table.where
>>
>> On Sun, Jul 15, 2012 at 4:01 PM, Juan Manuel Vázquez Tovar <
>> jmv.to...@gmail.com> wrote:
>>
>>> Hello,
>>>
>>> I have been using pytables for a few moths. The main structure of my
>>> files has a four column table, two of which have multidimensional cells,
>>> (56,1) and (133,6) respectively. The previous structure had more columns
>>> instead of storing the 56x1 array into the same cell. The largest file has
>>> almost three million rows in the table.
>>> I usually request data from the table looping through the entire table
>>> and getting for each row one specific row of the 133x6 2d array.
>>> Currently, each of the requests can take from 15 sec up to 10 minutes, I
>>> believe that depending on the status of the office network.
>>> Could you please advice about how to improve the reading time?
>>> I have tried to compress the data with zlib, but it takes more or less
>>> the same time.
>>>
>>> Thanks in advance,
>>>
>>> Juan Manuel
>>>
>>>
>>>
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