Хранение в массиве float и int

for k in range(len(X)):
        X[k][0] = float(X[k][0])

#Заменить все 0. и 1. на int
 
#!/usr/bin/env python2
 
import numpy as np
from sklearn import tree
from sklearn.tree import DecisionTreeClassifier
 
X = []
y = []
 
for line in open("ddd.data"):
    line = line.split('\t')
    X.append(map(str,line))
    for j in range(len(line)):
        for i in range(len(X)):
            if X[i][j] == 'yes':
                X[i][j] = 1
            elif X[i][j] == 'no':
                X[i][j] = 0
            if X[i][j] == 'yes\n':
                X[i][j] = 1
            elif X[i][j] == 'no\n':
                X[i][j] = 0
    for k in range(len(X)):
        X[k][0] = float(X[k][0])
 
X = np.array(X)
 
XX = X[:,[0,1,2,3,4,5,6]]
YY = X[:,7]
 
for size in range(6,10):
 
    Xlearn = XX[:len(XX)/10*size]
    Ylearn = YY[:len(YY)/10*size]
 
    Xtest = XX[len(XX)/10*size:]
    Ytest = YY[len(YY)/10*size:]
 
    clf = DecisionTreeClassifier(max_depth=3).fit(Xlearn, Ylearn)   
 
    filename = "dtree" + str(size) + ".dot"
 
    with open(filename, 'w') as f:
        f = tree.export_graphviz(clf, out_file=f)
 
    Ypredicted = clf.predict(Xtest) 
 
    rP = 0
    wP = 0
 
    for i in range(len(XX)/10*(10-size)):
        if Ypredicted[i] == Ytest[i]:
            rP += 1
        else:
            wP += 1
 
    print "TEST SIZE: ", size*10, "%"
    print "right: ", rP
    print "wrong: ", wP
    print "accuracy: ", float(rP)/(rP+wP)

input = '35,5   no  yes no  no  no  no  no'
output = [float(input.split()[0].replace(',', '.'))]+[0 if x == 'no' else 1 for x in input.split()[1:]]
 
print(output) # print(*output) to get a string