Using pandas to efficiently read in a large CSV file without crashing

Question

I am trying to read a .csv file called ratings.csv from http://grouplens.org/datasets/movielens/20m/ the file is 533.4MB in my computer.

This is what am writing in j

Answer 1

try like this - 1) load with dask and then 2) convert to pandas

import pandas as pd
import dask.dataframe as dd
import time
t=time.clock()
df_train = dd.read_csv('../data/train.csv')
df_train=df_train.compute()
print("load train: " , time.clock()-t)