effective_data_viz_25.py

# Visualizing 4-D mix data using bubble plots
# leveraging the concepts of hue and size
size = wines['residual sugar']*25
fill_colors = ['#FF9999' if wt=='red' else '#FFE888' for wt in list(wines['wine_type'])]
edge_colors = ['red' if wt=='red' else 'orange' for wt in list(wines['wine_type'])]

plt.scatter(wines['fixed acidity'], wines['alcohol'], s=size, 
            alpha=0.4, color=fill_colors, edgecolors=edge_colors)

plt.xlabel('Fixed Acidity')
plt.ylabel('Alcohol')
plt.title('Wine Alcohol Content - Fixed Acidity - Residual Sugar - Type',y=1.05)