effective_data_viz_20.py

# Visualizing 3-D mix data using scatter plots
# leveraging the concepts of hue for categorical dimension
jp = sns.pairplot(wines, x_vars=["sulphates"], y_vars=["alcohol"], size=4.5,
                  hue="wine_type", palette={"red": "#FF9999", "white": "#FFE888"},
                  plot_kws=dict(edgecolor="k", linewidth=0.5))
                  
# we can also view relationships\correlations as needed                  
lp = sns.lmplot(x='sulphates', y='alcohol', hue='wine_type', 
                palette={"red": "#FF9999", "white": "#FFE888"},
                data=wines, fit_reg=True, legend=True,
                scatter_kws=dict(edgecolor="k", linewidth=0.5))