2019-03-08
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皮尔森相关分析
from numpy.random import rand
from numpy.random import seed
from scipy.stats import spearmanr
# seed random number generator
seed(1)
# prepare data
data1 = data['x']
data2 = data['price']
# calculate spearman's correlation
coef, p = spearmanr(data1, data2)
print('Spearmans correlation coefficient: %.3f' % coef)
# interpret the significance
alpha = 0.05
if p > alpha:
print('Samples are uncorrelated (fail to reject H0) p=%.3f' % p)
else:
print('Samples are correlated (reject H0) p=%.3f' % p)
Spearmans correlation coefficient: 0.963
Samples are correlated (reject H0) p=0.000
30.0000
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