我用seaborn做了一个分组箱线图。我有两个子图，描述不同类型的数据，为了比较类型（我想保持组的原样），我想在类型1的箱线图上绘制类型2的数据框的中位数，反之亦然。这是我的脚本

import seaborn as sns
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import netCDF4 as nc
sns.set_theme(style='ticks', palette='pastel')

fig = plt.figure(figsize=(15,5))

fig.subplots_adjust(hspace=0.12)
fig.subplots_adjust(wspace=0.15)
fig.subplots_adjust(right=0.98)
fig.subplots_adjust(left=0.12)
fig.subplots_adjust(bottom=0.1)
fig.subplots_adjust(top=0.98)

plt.rcParams['text.usetex'] = False
plt.rcParams['axes.labelsize'] = 12
plt.rcParams['font.size'] = 11
plt.rcParams['legend.fontsize'] = 12
plt.rcParams['xtick.labelsize'] = 11
plt.rcParams['ytick.labelsize'] = 11

ax1 = fig.add_subplot(1,2,1)
ax2 = fig.add_subplot(1,2,2)

def grouped_boxplot(axis_type1, axis_type2):
    methods = ['m1', 'm2', 'm3', 'm4', 'm5', 'm6', 'm7']

    df_model1_type1 = pd.DataFrame()
    df_model1_type2 = pd.DataFrame()
    df_model2_type1 = pd.DataFrame()
    df_model2_type2 = pd.DataFrame()
    df_model3_type1 = pd.DataFrame()
    df_model3_type2 = pd.DataFrame()
    df_model4_type1 = pd.DataFrame()
    df_model4_type2 = pd.DataFrame()

    for m in methods:
        df_model1_type1[m] = np.random.randint(1,101,10)
        df_model1_type2[m] = np.random.randint(1,101,10)
    for m in methods:
        df_model2_type1[m] = np.random.randint(1,101,10)
        df_model2_type2[m] = np.random.randint(1,101,10)
    for m in methods:
        df_model3_type1[m] = np.random.randint(1,101,10)
        df_model3_type2[m] = np.random.randint(1,101,10)
    for m in methods:
        df_model4_type1[m] = np.random.randint(1,101,10)
        df_model4_type2[m] = np.random.randint(1,101,10)

    df_model1_type1 = df_model1_type1.assign(Model='model1')
    df_model1_type2 = df_model1_type2.assign(Model='model1')
    df_model2_type1 = df_model2_type1.assign(Model='model2')
    df_model2_type2 = df_model2_type2.assign(Model='model2')
    df_model3_type1 = df_model3_type1.assign(Model='model3')
    df_model3_type2 = df_model3_type2.assign(Model='model3')
    df_model4_type1 = df_model4_type1.assign(Model='model4')
    df_model4_type2 = df_model4_type2.assign(Model='model4')

    df_type1 = pd.concat([df_model1_type1,df_model2_type1,df_model3_type1,
                          df_model4_type1])
    df_type2 = pd.concat([df_model1_type2,df_model2_type2,df_model3_type2,
                          df_model4_type2])

    df_type1_long = pd.melt(df_type1, 'Model', var_name='Method',
                            value_name='var')
    df_type2_long = pd.melt(df_type2, 'Model', var_name='Method',
                           value_name='var')

    axis_type1 = sns.boxplot(x='Model', hue='Method', y='var',
                             data=df_type1_long, showfliers=False, whis=0,
                             ax=axis_type1)
    axis_type2 = sns.boxplot(x='Model', hue='Method', y='var', data=df_type2_long,
                            showfliers=False, whis=0, ax=axis_type2)

    type1_median = df_type1.median().to_numpy()
    type2_median = df_type2.median().to_numpy()

    for xtick, ytick in zip(axis_type1.get_xticks(), type2_median):
        axis_type1.scatter(xtick, ytick, s=20, marker='*', color='red')

    for xtick, ytick in zip(axis_type2.get_xticks(), type1_median):
        axis_type2.scatter(xtick, ytick, s=20, marker='*', color='red')

    axis_type1.legend([],[], frameon=False)
    axis_type2.legend(loc='lower center', bbox_to_anchor=(-0.2,-0.25), ncol=7)

grouped_boxplot(ax1, ax2)

plt.show()
# plt.savefig('the_ultimate_boxplot.pdf')

我设法把中位数绘制到xtick上的箱线图上。

有没有一种方法，使我可以有一个符号的中位数m1（蓝色箱线图）为模型1的类型2上的m1（蓝色箱线图）为模型1的类型1，中位数m2（橙色箱线图）为模型1的类型2上的m2（橙色箱线图）为模型1的类型1 [...]？