Newbie - converting csv files to arrays in NumPy - Matlab vs. Numpy comparison

Gabriel Genellina gagsl-py at yahoo.com.ar
Thu Jan 11 05:46:34 CET 2007


At Wednesday 10/1/2007 16:48, oyekomova wrote:

>Thanks for your help. I compared the following code in NumPy with the
>csvread in Matlab for a very large csv file. Matlab read the file in
>577 seconds. On the other hand, this code below kept running for over 2
>hours. Can this program be made more efficient? FYI - The csv file was
>a simple 6 column file with a header row and more than a million
>records.
>
>
>import csv
>from numpy import array
>import time
>t1=time.clock()
>file_to_read = file('somename.csv','r')
>read_from = csv.reader(file_to_read)
>read_from.next()
>
>datalist = [ map(float, row[:]) for row in read_from ]
>
># now the real data
>data = array(datalist, dtype = float)
>
>elapsed=time.clock()-t1
>print elapsed

Replace that row[:] by row, it's just a waste of time and memory.
And see http://www.scipy.org/Cookbook/InputOutput


-- 
Gabriel Genellina
Softlab SRL 


	

	
		
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