简易用法
sns.scatterplot(x='sepal_length', y='sepal_width', data=df, hue='species', style='species')
sns.lineplot(x=np.linspace(0, 1, 10), y=np.random.rand(10))
sns.relplot(x='sepal_length', y='sepal_width', data=df, hue='species', style='species', col='species')
sns.stripplot(x='species', y='sepal_width', data=df, hue='species', size=4)
sns.swarmplot(x='species', y='sepal_width', data=df, hue='species', size=4)
sns.boxplot(x='species', y='sepal_width', data=df, hue='species')
sns.violinplot(x='species', y='sepal_width', data=df, hue='species')
sns.barplot(x='species', y='sepal_width', data=df, hue='species')
sns.distplot(df.sepal_length, bins=50, rug=True)
sns.kdeplot(df.sepal_length, df.sepal_width, shade=True, cbar=True, cmap='Reds')
sns.jointplot(df.sepal_length, df.sepal_width, kind='kde')
sns.pairplot(df, hue="species")
sns.heatmap(np.random.randn(8, 8), annot=True, annot_kws={'size':9,'weight':'bold', 'color':'w'}, fmt='.2f')
sns.clustermap(df.iloc[:, :4])
Relational plots(关系图)
scatterplot(散点图)

sns.scatterplot(x='sepal_length', y='sepal_width', data=df, hue='species', style='species')
lineplot(线图)
sns.lineplot(x=np.linspace(0, 1, 10), y=np.random.rand(10))
relplot(关系图)

sns.relplot(x='sepal_length', y='sepal_width', data=df, hue='species', style='species', col='species')
Categorical plots(分类图)
Categorical scatterplots(分类散点图)
stripplot(分布散点图)

sns.stripplot(x='species', y='sepal_width', data=df, hue='species', size=4)
swarmplot(分布密度散点图)

sns.swarmplot(x='species', y='sepal_width', data=df, hue='species', size=4)
Categorical distribution plots(分类分布图)
boxplot(箱线图)

sns.boxplot(x='species', y='sepal_width', data=df, hue='species')
violinplot(小提琴图)

sns.violinplot(x='species', y='sepal_width', data=df, hue='species')
Categorical estimate plots(分类估计图)
barplot(条形图)

sns.barplot(x='species', y='sepal_width', data=df, hue='species')
Distribution plots(分布图)
distplot(直方图)

sns.distplot(df.sepal_length, bins=50, rug=True)
kdeplot(核密度图)

sns.kdeplot(df.sepal_length, df.sepal_width, shade=True, cbar=True, cmap='Reds')
jointplot(联合分布图)

sns.jointplot(df.sepal_length, df.sepal_width, kind='kde')
pairplot(变量关系组图)

sns.pairplot(df, hue="species")
Matrix plots(矩阵图)
heatmap(热力图)

data = np.random.randn(8, 8)
sns.heatmap(data, annot=True, annot_kws={'size':9,'weight':'bold', 'color':'w'}, fmt='.2f')
clustermap(聚类图)

sns.clustermap(df.iloc[:, :4])