[Python] Reading a huge .csv file

I'm currently trying to read data from .csv files in Python 2.7 with up to 1 million rows, and 200 columns (files range from 100mb to 1.6gb). I can do this (very slowly) for the files with under 300,000 rows, but once I go above that I get memory errors. My code looks like this:

def getdata(filename, criteria):
data=[]
for criterion in criteria:
data.append(getstuff(filename, criteron))
return data

def getstuff(filename, criterion):
import csv
data=[]
with open(filename, "rb") as csvfile:
datareader=csv.reader(csvfile)
for row in datareader:
if row[3]=="column header":
data.append(row)
elif len(data)<2 and row[3]!=criterion:
pass
elif row[3]==criterion:
data.append(row)
else:
return data


The reason for the else clause in the getstuff function is that all the elements which fit the criterion will be listed together in the csv file, so I leave the loop when I get past them to save time.

My questions are:

1. 
   How can I manage to get this to work with the bigger files?
   
   
2. 
   Is there any way I can make it faster?
   

My computer has 8gb RAM, running 64bit Windows 7, and the processor is 3.40 GHz (not certain what information you need).

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