Using seaborn to plot grouped violin plots of multiple categorical variables
Seaborn is a matplotlib-based visualization library dedicated to creating highly informative, beautiful, and easy-to-understand statistical charts. In Seaborn, the catplot function is a very important function that can be used to create various types of charts based on categorical variables. This article will introduce how to use the catplot function to create grouped violin plots (Categorical Plots) under multiple categorical variable combinations.
First, we need to import the required libraries and datasets:
import seaborn as sns
import matplotlib.pyplot as plt
# 导入示例数据集tips
tips = sns.load_dataset("tips")
Next, let's use the catplot function to create grouped violin plots. In the catplot function, we need to set the x and y parameters to specify the categorical variable to be plotted, and also need to set the hue parameter to specify another categorical variable. The code below generates a grouped violin plot with "day" and "sex" as categorical variables, "total_bill" as the y-axis variable, and "smoker" as the color variable.
sns.catplot(x="day", y="total_bill", hue="smoker", col="sex",
kind="violin", data=tips, split=True,
height=4, aspect=.7);
In this example, we use the kind parameter to specify the grouped violin plot to be drawn, and the split parameter is used to split the violin plot to show the two data sets within each grouping. We can also use the col parameter to plot the violin plots in two different columns.
In addition to grouped violin plots, the catplot function can also be used to create