import matplotlib.pyplot as pltimport seaborn as sns ax = reviews['points'].value_counts().sort_index().plot.bar( figsize=(12, 6), color='mediumvioletred', fontsize=16)ax.set_title("Rankings Given by Wine Magazine", fontsize=20)sns.despine(bottom=True, left=True)
Notice that this plot comes with some bells and whistles: a correlation coefficient is provided, along with histograms on the sides. These kinds of composite plots are a recurring theme in seaborn. Other than that, the jointplot is just like the pandas scatter plot.
As in pandas, we can use a hex plot (by simply passing kind='hex') to deal with overplotting: