4801.py

houses = pd.read_csv('data/melb_data.csv')

# Calculate pairwise-correlation
matrix = houses.corr()

# Create a mask
mask = np.triu(np.ones_like(matrix, dtype=bool))

# Create a custom diverging palette
cmap = sns.diverging_palette(250, 15, s=75, l=40,
                             n=9, center="light", as_cmap=True)

plt.figure(figsize=(16, 12))

sns.heatmap(matrix, mask=mask, center=0, annot=True,
             fmt='.2f', square=True, cmap=cmap)

plt.show();