

In [ ]:

    
from codefiles.datagen import x_plus_noise
import numpy as np
import seaborn as sns
%matplotlib inline

Correlation Matrix

By calling df.corr() on a full pandas DataFrame will return a square matrix containing all pairs of correlations.

By plotting them as a heatmap, you can visualize many correlations more efficiently.



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df = x_plus_noise(randomness=0)
sns.heatmap(df.corr(), vmin=0, vmax=1)
df.corr()



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df = x_plus_noise(randomness=0.5)
sns.heatmap(df.corr(), vmin=0, vmax=1)
df.corr()



In [ ]:

    
df = x_plus_noise(randomness=1)
sns.heatmap(df.corr(), vmin=0, vmax=1)
df.corr()