Saving train and test data in a file

Question

I'm using the following code for splitting up the dataset into a train and test data to save in a file;

import numpy as np
from sklearn.cross_validation import train_test_split

a = (np.genfromtxt(open('dataset.csv','r'), delimiter=',', dtype='int')[1:])
a_train, a_test = train_test_split(a, test_size=0.33, random_state=0)

c1 = open('trainfile.csv', 'w')
arr1 = str(a_train)
c1.write(arr1)
c1.close

c2 = open('testfile.csv', 'w')
arr2 = str(a_test)
c2.write(arr2)
c2.close

However I get the following output in the file;

trainfile.csv:
[[ 675847       0       0 ...,       0       0       3]
 [  74937       0       0 ...,       0       0       3]
 [  65212       0       0 ...,       0       0       3]
 ..., 
 [  18251       0       0 ...,       0       0       1]
 [1131828       0       0 ...,       0       0       1]
 [  14529       0       0 ...,       0       0       1]]

That is the entire content of trainfile. I'm facing the same issue with the output for testfile.csv as well. What I want is the entire training and test data to be stored inside the file instead of periods denoting extra data. Suggestions?

Answer 1

This is because you are calling the string method str on the numpy array. Use the numpy function numpy.savetxt instead. It would look something like

with open('testfile.csv', 'w') as FOUT:
    np.savetxt(FOUT, a_test)

Note that the format would not necessarily be readable by a CSV reader. If that is your intention, you can use https://docs.python.org/2/library/csv.html.