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| import pickle
import numpy as np
import matplotlib.pyplot as plt
import pylab
from scipy import stats
data=pickle.load(open("test.pkl","rb"))
var=data.keys ()
mesures_names_int = [ 'v1', 'V2', 'V3', 'V4', 'V5', 'V5', 'V6', 'V7', 'V8', 'V9', 'V10']
print "les mesures utilisée",mesures_names_int
lon_mesure=len(mesures_names_int)
print lon_mesure
for l in range(0,lon_mesure):
stat_mesure1.append(l)
stat_mesure1[0]=['moyenne globale','variance','l ecart type','minimum','maximum','valeur mediane']
print "mesure_name courant : " + mesures_names_int[l]
mesure = data[mesures_names_int[l]]
stat_mesure1[l]=[np.mean(mesure),np.var(mesure),np.std(mesure),np.min(mesure),np.max(mesure),np.median(mesure)]
fig =plt.figure()
pylab.xticks([1,2],[+ mesures_names_int[l]])
plt.boxplot(mesure)
plt.ylim(0,30)
plt.savefig('boite2.png')
plt.show()
print stat_mesure1 |