<jupyter_start><jupyter_text>Calculate the correlate<jupyter_code>attributes_corr = attributes_pd.corr()
attributes_corr
import matplotlib.pyplot as plt
import seaborn as sns
%matplotlib inline

sns.heatmap(attributes_corr)
plt.show()
sum3 = 0
for i in range(65):
    for j in range(65):
        if j >= i:
            break
        if attributes_corr[i][j] >= 0.3:
            sum3 += 1
print(sum3, 65*64/2)
sum8 = 0
for i in range(65):
    for j in range(65):
        if j >= i:
            break
        if attributes_corr[i][j] >= 0.8:
            sum8 += 1
print(sum8, 65*64/2)
sum1 = 0
for i in range(65):
    for j in range(65):
        if j >= i:
            break
        if attributes_corr[i][j] >= 0.1:
            sum1 += 1
print(sum1, 65*64/2)<jupyter_output>119 2080.0
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