I have a csv file that I'm trying to convert its data into Dense Design Matrix using Pylearn2 module. However what causes error is not related to pylearn2 but to my personal implementation.
import csv def load_data(fileName_X, start, stop): with open(fileName_X, 'r') as f: reader_X = csv.reader(f, delimiter=';') X = [] header = True size=0 for row_X in reader_X: if header: header = False continue row_X = [float(elem_X) for elem_X in row_X] size+=1 X.append(row_X) X = np.asarray(X) if __name__ == "__main__": train = load_data(sys.argv[1], 0, 10) Here is some rows of the .csv file:
-1;-0.844511;-0.339286;-1;0.0769231;-0.25;-0.929825;1;1;-0.880597;1;0;-0.92;-0.99 1;-0.796992;-0.8275;-1;0.0769231;-0.25;-0.859649;1;1;-0.671642;1;-1;-0.8;-0.94 1;-0.611429;-0.875;-1;0.0769231;-0.25;-0.929825;1;1;-0.850746;1;-1;-0.84;-0.88446 -1;-0.661654;-0.119286;-1;0.846154;0.75;-0.754386;1;1;-0.820896;-1;-1;-0.6;-0.99084 Normally what I expect is to have all the values of each row which are separated by ; in row_X. But as I run the program, I get this error:
Traceback (most recent call last): File "make_dataset.py", line 68, in <module> train = load_data(sys.argv[1], 0, 10) File "make_dataset.py", line 53, in load_data row_X = [float(elem_X) for elem_X in row_X] ValueError: invalid literal for float(): 1;-0.796992;-0.8275;-1;0.0769231;-0.25;-0.859649;1;1;-0.671642;1;-1;-0.8;-0.94 What I can't find out the reason is that the program works properly with another csv file which contains these rows (just to compare its possible different form with the first one):
7.4;0.7;0;1.9;0.076;11;34;0.9978;3.51;0.56;9.4;5 7.8;0.88;0;2.6;0.098;25;67;0.9968;3.2;0.68;9.8;5 7.8;0.76;0.04;2.3;0.092;15;54;0.997;3.26;0.65;9.8;5 11.2;0.28;0.56;1.9;0.075;17;60;0.998;3.16;0.58;9.8;6 
csv.readerwhich should be splitting the line correctly.newline=''."