df.describe() # Combination of subplot and histogram plt.figure(figsize=(15,11)) for (i, col) in enumerate(sellers.describe().columns):#["wait_time", "delay_to_carrier", "avg_review_score", "n_orders", "quantity", "price"]): plt.subplot(3,4,i+1) sns.histplot(sellers[col], kde=False, stat='density', discrete=[True,None][col in ['share_of_one_stars','share_of_five_stars','sales']]); #seaborn PairPlot sns.pairplot(df) #plotly Scatter Plot import plotly.express as px fig = px.scatter(data_frame = sellers[sellers['review_score'] < 4], x="wait_time", y="delay_to_carrier", size="sales", color="review_score", size_max = 60, opacity = 0.5 ) fig.show()