correlation coefficient python numpy example
>>> r = np.corrcoef(x, y)
>>> r
array([[1. , 0.75864029],
[0.75864029, 1. ]])
>>> r[0, 1]
0.7586402890911867
>>> r[1, 0]
0.7586402890911869correlation coefficient python numpy example
>>> r = np.corrcoef(x, y)
>>> r
array([[1. , 0.75864029],
[0.75864029, 1. ]])
>>> r[0, 1]
0.7586402890911867
>>> r[1, 0]
0.7586402890911869python calculate correlation
# For a measure the strength of association between two variables;
import numpy as np
from scipy.stats import spearmanr, pearsonr, kendalltau
serie1 = np.array([-2, -1, 0, 1, 4])
serie2 = np.array([-2.5, -.75, 1, 2, 6])
# linear ==> Pearson
pearsonr(serie1, serie2)
pearsonrResult(correlation=0.9964803994464919, pvalue=0.0002505212149642603)
# Non-linear ==> Spearman or kendall
spearmanr(serie1, serie2)
SpearmanrResult(correlation=0.9999999999999999, pvalue=1.4042654220543672e-24)
kendalltau(serie1, serie2)
KendalltauResult(correlation=0.9999999999999999, pvalue=0.016666666666666666)Copyright © 2021 Codeinu
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