【2.4.2】密度图(Density Plot)

密度图是一种常用工具，可视化连续变量的分布。 通过“响应”变量对它们进行分组，您可以检查X和Y之间的关系。以下情况，如果出于代表性目的来描述城市里程的分布如何随着汽缸数的变化而变化。

# Import Data
df = pd.read_csv("https://github.com/selva86/datasets/raw/master/mpg_ggplot2.csv")

# Draw Plot
plt.figure(figsize=(16,10), dpi= 80)
sns.kdeplot(df.loc[df['cyl'] == 4, "cty"], shade=True, color="g", label="Cyl=4", alpha=.7)
sns.kdeplot(df.loc[df['cyl'] == 5, "cty"], shade=True, color="deeppink", label="Cyl=5", alpha=.7)
sns.kdeplot(df.loc[df['cyl'] == 6, "cty"], shade=True, color="dodgerblue", label="Cyl=6", alpha=.7)
sns.kdeplot(df.loc[df['cyl'] == 8, "cty"], shade=True, color="orange", label="Cyl=8", alpha=.7)

# Decoration
plt.title('Density Plot of City Mileage by n_Cylinders', fontsize=22)
plt.legend()
plt.show()

参考资料

• https://www.machinelearningplus.com/plots/top-50-matplotlib-visualizations-the-master-plots-python/