def getDifferentTrainAndTestData(trainDataSize, testDataSize):
data = dataReader.getWholeTrainingData()
if trainDataSize+testDataSize > data.shape[0]: # request more rows than the DF has
print "Getting different train & test data with possible duplicates"
trainData = data.sample(trainDataSize)
testData = data.sample(testDataSize)
else:
print "Getting totally different train & test data"
indexes = np.arange(data.shape[0]) #0->873k
random.shuffle(indexes) # works in-place
trainData = data.ix[indexes[0:trainDataSize]]
testData = data.ix[indexes[trainDataSize+1:trainDataSize+1+testDataSize]]
return trainData,testData
