effective_data_viz_27.py

# Visualizing 4-D mix data using scatter plots
# leveraging the concepts of hue and facets for > 1 categorical attributes
g = sns.FacetGrid(wines, col="wine_type", hue='quality_label', 
                  col_order=['red', 'white'], hue_order=['low', 'medium', 'high'],
                  aspect=1.2, size=3.5, palette=sns.light_palette('green', 4)[1:])
g.map(plt.scatter, "volatile acidity", "total sulfur dioxide", alpha=0.9, 
      edgecolor='white', linewidth=0.5, s=100)
fig = g.fig 
fig.subplots_adjust(top=0.8, wspace=0.3)
fig.suptitle('Wine Type - Sulfur Dioxide - Acidity - Quality', fontsize=14)
l = g.add_legend(title='Wine Quality Class')